Keith Dawson's Analyst Perspectives

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We offer a portfolio of advisory, research, thought leadership and digital education services to help optimize market strategy, planning and execution.</p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/analyst_relations" rel="noopener">Analyst Relations</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/demand_generation" rel="noopener">Demand Generation</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/services/vendors/product-marketing" rel="noopener">Product Marketing</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/vendor-coverage" target="_self" role="menuitem">Market Coverage</a></strong></p> <p><strong><a href="https://www.ventanaresearch.com/briefing" target="_self" role="menuitem">Request a Briefing</a></strong><br><br><br></p></div> <span id="hs_cos_wrapper_dnd_area-module-2_" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_simple_menu" style="" data-hs-cos-general-type="widget" data-hs-cos-type="simple_menu"><ul></ul></span> <div class="bottom_rich_text"> </div> </div> </div> </div> </div> </div> <script src="https://keithdawson.isg-one.com/hs-fs/hubfs/hub_generated/template_assets/1/90531223305/1740157483881/template_mmenu.min.js"></script> </div> </div> </div> </div> </div> </div> </div> </div> <div id="hs_cos_wrapper_Structured_data" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"></div> <div class="body-container-wrapper"> <div class="blog-header background-image post_page_2" data-bg-color="secondary" style=" background-size:cover; background-position:50%; background-repeat:no-repeat; background-image:url(https://keithdawson.isg-one.com/hubfs/_images/_backgrounds_expertise/Expertise_CX_480329143_1200px.jpg); ">  <div class="row-fluid"> <div class="blog-header__inner dnd-row"> <div class="blog--post__image dnd-section"> <img class="analyst-header-photo" src="https://keithdawson.isg-one.com/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png" style="padding: 10px; "> <br> <h1 class="analyst-header-title">Keith Dawson's Analyst Perspectives</h1>  </div> </div> </div> </div> <div class="content-wrapper-listing blog-single"> <div class="blog-content-wrapper"> <div>   <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/zoho-evolves-portfolio-for-enterprises-using-ai">Zoho Evolves Portfolio for Enterprises Using AI</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">20 February 2025 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=200&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=100&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=200&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=300&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=400&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=500&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png?width=600&name=Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Zoho’s recent analyst conference was an opportunity to explore how the India-founded software company is faring in its efforts to extend its enterprise business, and to place AI at the center of its product portfolio. It appears the company is having some success on both fronts.</p> </div> <a href="https://keithdawson.isg-one.com/zoho-evolves-portfolio-for-enterprises-using-ai"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a>, <a href="https://keithdawson.isg-one.com/tag/customers-and-cx-business-technologies">Customers and CX - Business & Technologies</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/there-are-gaps-in-the-cx-toolkit-waiting-to-be-filled">There Are Gaps in the CX Toolkit Waiting to Be Filled</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">14 January 2025 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=200&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=100&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=200&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=300&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=400&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=500&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png?width=600&name=There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>The breadth of customer experience (CX) solutions created by software providers in recent years has expanded into new areas, usually related or adjacent to existing, more traditional toolkits. Most providers in the space began as more-or-less pure play contact center software providers, so the CX toolset starts with that set of technologies. Products are grounded in core functions for service delivery, like interaction handling, labor management and customer tracking. Some software providers...</p> </div> <a href="https://keithdawson.isg-one.com/there-are-gaps-in-the-cx-toolkit-waiting-to-be-filled"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a>, <a href="https://keithdawson.isg-one.com/tag/generative-ai">Generative AI</a>, <a href="https://keithdawson.isg-one.com/tag/cxm">CXM</a>, <a href="https://keithdawson.isg-one.com/tag/customer-success">Customer Success</a>, <a href="https://keithdawson.isg-one.com/tag/pre-hire-assessment">Pre-Hire Assessment</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/ai-use-cases-for-field-service">AI Use Cases for Field Service</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">08 January 2025 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=200&name=AI_Use_Cases_for_Field_Service.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=100&name=AI_Use_Cases_for_Field_Service.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=200&name=AI_Use_Cases_for_Field_Service.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=300&name=AI_Use_Cases_for_Field_Service.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=400&name=AI_Use_Cases_for_Field_Service.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=500&name=AI_Use_Cases_for_Field_Service.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/AI_Use_Cases_for_Field_Service.png?width=600&name=AI_Use_Cases_for_Field_Service.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Field service is an often-overlooked area of the service equation, in part because managing its operations involves tools and activities outside of normal contact center models. Field service has a communications component, which is partly handled by contact centers. However, the bulk of field service management activity has to do with organizing the work of technicians and dispatchers. It also requires constant attention to informational resources about products, assets, locations, real-time...</p> </div> <a href="https://keithdawson.isg-one.com/ai-use-cases-for-field-service"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/field-service">Field Service</a>, <a href="https://keithdawson.isg-one.com/tag/generative-ai">Generative AI</a>, <a href="https://keithdawson.isg-one.com/tag/augmented-reality">Augmented Reality</a>, <a href="https://keithdawson.isg-one.com/tag/ar">AR</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/what-open-platforms-mean-for-contact-centers">What Open Platforms Mean for Contact Centers</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">12 November 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=200&name=What_Open_Platforms_Mean_for_Contact_Centers.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=100&name=What_Open_Platforms_Mean_for_Contact_Centers.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=200&name=What_Open_Platforms_Mean_for_Contact_Centers.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=300&name=What_Open_Platforms_Mean_for_Contact_Centers.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=400&name=What_Open_Platforms_Mean_for_Contact_Centers.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=500&name=What_Open_Platforms_Mean_for_Contact_Centers.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png?width=600&name=What_Open_Platforms_Mean_for_Contact_Centers.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Software providers have identified “openness” as a key consideration for contact center buyers. Since there is no generally accepted rule about what makes a system open, it makes sense for us to examine what components contribute to that quality, and why it should be thought of as a good thing.</p> </div> <a href="https://keithdawson.isg-one.com/what-open-platforms-mean-for-contact-centers"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/generative-ai">Generative AI</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/verint-focuses-bots-on-contact-center-outcomes">Verint Focuses Bots on Contact Center Outcomes</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">05 November 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=200&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=100&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=200&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=300&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=400&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=500&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png?width=600&name=Verint_Focuses_Bots_on_Contact_Center_Outcomes.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span><a href="https://www.verint.com/">Verint</a> is operating in quite a different marketplace for contact center and agent management technology than existed five years ago. We have seen tremendous innovation and expansion of the available technologies for running centers and optimizing the performance of the human labor pool, as well as an explosion of tools built to automate customer interactions.</span></p> </div> <a href="https://keithdawson.isg-one.com/verint-focuses-bots-on-contact-center-outcomes"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/agent-management">agent management</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/contact-center-ai-gain-traction-profitable-use-cases">Contact Center AI Gain Traction: Profitable Use Cases</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">29 October 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=200&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=100&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=200&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=300&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=400&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=500&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png?width=600&name=Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>With a flood of artificial intelligence-related tools now available for contact center buyers, it can be helpful to take a step back and review where buyers can expect a quick return on investment and maximum improvement in efficiency and productivity. For now, it appears that there are three broad buckets into which contact center-focused AI applications are clustered. They all relate to agent behavior and activity, including:</p> </div> <a href="https://keithdawson.isg-one.com/contact-center-ai-gain-traction-profitable-use-cases"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/voice-of-the-customer">Voice of the Customer</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/sprinklr-zeros-in-on-a-cxm-platform">Sprinklr Zeros in on a CXM Platform</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">23 October 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=200&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=100&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=200&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=300&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=400&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=500&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png?width=600&name=Sprinklr_Zeros_in_on_a_CXM_Platform.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><span>Sprinklr’s analyst day in September was an opportunity for the company to dive deeply into its progress in pivoting its product offerings to align with a broader perception of the market for contact centers and adjacent customer-related applications.</span></p> </div> <a href="https://keithdawson.isg-one.com/sprinklr-zeros-in-on-a-cxm-platform"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/agent-management">agent management</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/ccaas-cpaas-or-ucaas-for-cx-it-doesnt-matter">CCaaS, CPaaS or UCaaS for CX? It Doesn’t Matter.</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">18 September 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=200&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=100&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=200&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=300&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=400&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=500&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png?width=600&name=CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>It is unfortunate that business-focused digital communications are sold under three different headings: Contact Center as a Service (CCaaS), Unified Communication as a Service (UCaaS) and Communication Platform as a Service (CPaaS). (And that just counts the cloud options—let us acknowledge the huge, continuing, installed base on premises.) These are terrible ways to describe complex, varied and overlapping offerings. What distinguishes them are:</p> </div> <a href="https://keithdawson.isg-one.com/ccaas-cpaas-or-ucaas-for-cx-it-doesnt-matter"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-engagement">Customer Engagement</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a>, <a href="https://keithdawson.isg-one.com/tag/digital-communications">Digital Communications</a>, <a href="https://keithdawson.isg-one.com/tag/ccaas">CCaaS</a>, <a href="https://keithdawson.isg-one.com/tag/intelligent-self-service">Intelligent Self-Service</a>, <a href="https://keithdawson.isg-one.com/tag/cpaas">CPaaS</a>, <a href="https://keithdawson.isg-one.com/tag/ucaas">UCaaS</a>, <a href="https://keithdawson.isg-one.com/tag/cxm">CXM</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/businesses-need-a-more-expansive-view-of-self-services-value">Businesses Need a More Expansive View of Self-Service’s Value</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">20 June 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=200&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=100&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=200&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=300&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=400&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=500&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png?width=600&name=Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p>Self-service has changed immensely in recent years. It has gotten better, qualitatively, in delivering answers and resolutions to customers. But it has also gotten extremely complex, relying on a basket of new technologies to achieve results. It helps to look at it through the eyes of the three main constituencies that are affected by it: customers, contact centers and the businesses they sit in.</p> </div> <a href="https://keithdawson.isg-one.com/businesses-need-a-more-expansive-view-of-self-services-value"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a>, <a href="https://keithdawson.isg-one.com/tag/intelligent-self-service">Intelligent Self-Service</a> <hr> </div>  <div class="blog-index__post-content" style="margin-bottom: 80px"> <div class="post-meta"> <h2 style="font-size: 1.875rem;"><a href="https://keithdawson.isg-one.com/verint-turns-focus-to-cx-automation-and-ai">Verint Turns Focus to CX Automation and AI</a></h2> <div class="author-meta"> Posted by <a href="https://keithdawson.isg-one.com/author/keith-dawson"> Keith Dawson </a> on <span class="post-date">12 June 2024 </span> </div>  <hr> </div> <div class="list-card-p"><div class="wrapingimage"> <img src="https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=200&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png" width="200" !important: srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=100&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=200&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=300&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 300w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=400&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 400w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=500&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 500w, https://keithdawson.isg-one.com/hs-fs/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png?width=600&name=Verint_Turns_Focus_to_CX_Automation_and_AI.png 600w" sizes="(max-width: 200px) 100vw, 200px"> </div> <p><a href="http://www.verint.com/"><span data-contrast="none">Verint</span></a><span data-contrast="auto"> held its analyst conference recently, using the opportunity to flesh out how it is responding to the rapid developments in artificial intelligence (AI) and data-related technologies and to changes in the way enterprises consider the purchasing process for contact center-related tools. </span></p> </div> <a href="https://keithdawson.isg-one.com/verint-turns-focus-to-cx-automation-and-ai"><span class="readmore"> Read More </span></a><br><br> Topics: <a href="https://keithdawson.isg-one.com/tag/customer-experience">Customer Experience</a>, <a href="https://keithdawson.isg-one.com/tag/contact-center">Contact Center</a>, <a href="https://keithdawson.isg-one.com/tag/customer-experience-management">Customer Experience Management</a>, <a href="https://keithdawson.isg-one.com/tag/intelligent-self-service">Intelligent Self-Service</a> <hr> </div> <script> // Check active classes var checkClass = function() { if ( $('.fil_item').hasClass('hide') ) { $('.fil_item').removeClass('hide'); 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If you have any issue with an Analyst Perspective, please email them to <a href="mailto:ChiefResearchOfficer@isg-research.net">ChiefResearchOfficer@isg-research.net</a></p> </li> </ul> <a class="btn-secondary" href="https://www.isg-research.net/analyst-perspective-policy">View Policy</a></span>  <div id="hs_cos_wrapper_module_168621267066296" class="hs_cos_wrapper hs_cos_wrapper_widget hs_cos_wrapper_type_module" style="" data-hs-cos-general-type="widget" data-hs-cos-type="module"><style> </style> <h3 style="color: #255a89;">Our Analysts</h3>  <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://davidmenninger.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png" alt="David Menninger" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=50&name=Menninger.David%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=100&name=Menninger.David%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=150&name=Menninger.David%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=200&name=Menninger.David%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=250&name=Menninger.David%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Menninger.David%20Pic.Circle.png?width=300&name=Menninger.David%20Pic.Circle.png 300w"> <h5 class="analyst_name">David Menninger</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://jefforr.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png" alt="Jeff Orr" width="100" data-constrained="true" caption="false" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=50&name=Orr.Jeff.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=100&name=Orr.Jeff.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=150&name=Orr.Jeff.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=200&name=Orr.Jeff.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=250&name=Orr.Jeff.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Orr.Jeff.Circle.png?width=300&name=Orr.Jeff.Circle.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">Jeff Orr</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://keithdawson.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png" alt="Keith Dawson" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=50&name=Dawson.Keith%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=100&name=Dawson.Keith%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=150&name=Dawson.Keith%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=200&name=Dawson.Keith%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=250&name=Dawson.Keith%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Dawson.Keith%20Pic.Circle.png?width=300&name=Dawson.Keith%20Pic.Circle.png 300w"> <h5 class="analyst_name">Keith Dawson</h5> </a> </div> <div class="span6" style="text-align:center;"> <a href="https://marksmith.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png" alt="Mark Smith" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=50&name=Smith.Mark%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=100&name=Smith.Mark%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=150&name=Smith.Mark%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=200&name=Smith.Mark%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=250&name=Smith.Mark%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Smith.Mark%20Pic.Circle.png?width=300&name=Smith.Mark%20Pic.Circle.png 300w"> <h5 class="analyst_name">Mark Smith</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://mattaslett.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png" alt="Matt Aslett" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=50&name=Aslett.Matt%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=100&name=Aslett.Matt%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=150&name=Aslett.Matt%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=200&name=Aslett.Matt%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=250&name=Aslett.Matt%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Aslett.Matt%20Pic.Circle.png?width=300&name=Aslett.Matt%20Pic.Circle.png 300w"> <h5 class="analyst_name">Matt Aslett</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://matthewbrown.isg-research.net/"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png" alt="Matthew Brown" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=50&name=profile_vr_matthew_brown_circle_900x900.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=100&name=profile_vr_matthew_brown_circle_900x900.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=150&name=profile_vr_matthew_brown_circle_900x900.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=200&name=profile_vr_matthew_brown_circle_900x900.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=250&name=profile_vr_matthew_brown_circle_900x900.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/profile_vr_matthew_brown_circle_900x900.png?width=300&name=profile_vr_matthew_brown_circle_900x900.png 300w"> <h5 class="analyst_name">Matthew Brown</h5> </a> </div> </div>   <div class="row-fluid"> <div class="span6" style="text-align: center;"> <a href="https://robertkugel.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png" alt="Robert Kugel" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=50&name=Kugel.Robert%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=100&name=Kugel.Robert%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=150&name=Kugel.Robert%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=200&name=Kugel.Robert%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=250&name=Kugel.Robert%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Kugel.Robert%20Pic.Circle.png?width=300&name=Kugel.Robert%20Pic.Circle.png 300w"> <h5 class="analyst_name">Robert Kugel</h5> </a> </div> <div class="span6" style="text-align: center;"> <a href="https://stephenhurrell.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png" alt="Stephen Hurrell" width="100" data-constrained="true" caption="false" sizes="(max-width: 100px) 100vw, 100px" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=50&name=Hurrell.Stephen%20Pic.Circle.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=100&name=Hurrell.Stephen%20Pic.Circle.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=150&name=Hurrell.Stephen%20Pic.Circle.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=200&name=Hurrell.Stephen%20Pic.Circle.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=250&name=Hurrell.Stephen%20Pic.Circle.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/_images/_team/Hurrell.Stephen%20Pic.Circle.png?width=300&name=Hurrell.Stephen%20Pic.Circle.png 300w"> <h5 class="analyst_name">Stephen Hurrell</h5> </a> </div> </div>   <div class="row-fluid">  <div style="text-align: center;"> <a href="https://blog.isg-research.net"> <img class="analyst_img" style="width: 100px;" src="https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png" alt="ISG Software Research" width="100" data-constrained="true" caption="false" srcset="https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=50&name=ISG_Bug_Reverse_Transparent.png 50w, https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=100&name=ISG_Bug_Reverse_Transparent.png 100w, https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=150&name=ISG_Bug_Reverse_Transparent.png 150w, https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=200&name=ISG_Bug_Reverse_Transparent.png 200w, https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=250&name=ISG_Bug_Reverse_Transparent.png 250w, https://keithdawson.isg-one.com/hs-fs/hubfs/ISG_Bug_Reverse_Transparent.png?width=300&name=ISG_Bug_Reverse_Transparent.png 300w" sizes="(max-width: 100px) 100vw, 100px"> <h5 class="analyst_name">ISG Software Research</h5> </a> </div> </div>  </div> <div id="hs_cos_wrapper_module_1552944263900179" class="hs_cos_wrapper 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"@context": "http://schema.org", "@type": "BlogPosting", "headline": "Zoho Evolves Portfolio for Enterprises Using AI", "mainEntityOfPage": "https://keithdawson.isg-one.com/zoho-evolves-portfolio-for-enterprises-using-ai", "datePublished": "20/02/2025", "dateModified": "20/02/2025", "articleBody": "Zoho’s recent analyst conference was an opportunity to explore how the India-founded software company is faring in its efforts to extend its enterprise business, and to place AI at the center of its product portfolio. It appears the company is having some success on both fronts. Zoho’s software suite includes nearly 60 applications that extend into almost every facet of business activity, from front to back office. Of those, a significant number are relevant to customer experience professionals in sales, service and marketing. This group of professionals is engaged in work that is critical to company health, but at the same time underappreciated and often under-resourced. They are also operating at a moment when many of the basic processes and underlying assumptions of CX are being reconfigured and reevaluated. It is a strange time to be a CX professional, especially when it comes to contact centers and service delivery. Much of the uncertainty in today’s environment has to do with the development of tools that use AI for process automation. There have been significant productivity gains already in the contact center, with more expected as those centers become more closely connected with other siloed CX teams and processes across the enterprise. Zoho has been developing AI applications and incorporating them into the suite wherever practical, and our research finds these advancements are helping Zoho improve their overall performance, with the company achieving an Exemplary rating in our recent ISG Buyers Guide on advanced contact centers. It’s worth noting that their AI development pre-dates the current industry conversations around generative and agentic AI tools, and this gives them valuable perspective on these current conversations. In the analyst presentations, Zoho executives went out of their way to address the limitations of some approaches to AI in software apps. For example, they noted that introducing AI into certain tools raises issues of compliance—can an LLM be made to “forget” certain pieces of information once they have been learned? It has an impact on information retention policies. They also mentioned the idea of productivity, suggesting that there are subtle limits to the kinds of productivity increases AI can usher in. While 10x or 100x improvements in programming productivity are possible, they argue you can’t necessarily expect that kind of explosion from certain processes that require human intervention to verify the accuracy of unstructured AI output, like creating legal briefs or corporate annual reports. It’s fair to say that the kinds of processes being automated in CX and contact centers have more in common with those human-verifiable activities than with programming, suggesting something of a cap on the improvements to be seen from AI in CX. Assuming that those limitations can be overcome (which is likely), the boom in productivity has other downstream effects that need to be worked through. Zoho used the analogy of previous technology revolutions causing disruptions in ways that the business world at large has trouble digesting. When farm productivity increased massively due to automation and scale, more farmers had to leave the profession, and farm incomes did not keep up; farmers did not reap the benefits of their own productivity. Similarly, the textile industry is now so extremely productive that traditional weavers are effectively gone. Zoho uses these comparisons to suggest that because business models can undergo such radical change in a short period of time, businesses must look for new sources of value in their enterprise software. Zoho locates that value in providing privacy, trust and the assurance of compliance. In their telling, practical usage of Zoho’s AI applications will proceed in three stages. First, the tools are enhancing the user experience by surfacing and executing on contextual business data. That is where things stand so far. (I take “contextual” to mean ensuring that the technology understands the context of the interaction with the user, which requires a finer sense of the business relationship, data and actions while respecting the permissions necessary to have access to information and answers.) The second phase is in creating tools that enact “AI-enabled verifiable actions,” which is a way of describing AI agents and their ability to perform actions that don’t necessarily require human verification. This is where current work is being done. And the third stage, still to come, will ultimately be the aforementioned explosion of productivity, and its unforeseeable consequences. Zoho’s AI platform, Zia, is being described as a bridge that connects LLMs to applications, allowing customers to pick one and let it be the underlying LLM for a specific app. Zia Agent Studio then facilitates creation and deployment of comprehensive agents that live in a unified data platform leveraging a broad set of existing tools and a common trust layer. This suggests that over time, Zoho’s offering should be perceived less as a collection of point solutions, or apps for narrowly defined business functions, and more as a platform company with centralized data, tools for customers to innovate, and a common AI element cutting across the application set. This tracks with our ISG Research assertion that by 2028, enterprises will replace many CX point solutions with broad, interdepartmental, multifunction suites. Zoho’s stated goal is to move from the SMB and mid-markets towards becoming an enterprise software supplier. This has been a strategy since at least 2022. Clearly the company sees the opportunity to use AI as a catalyst to evolve the app collection into a cohesive platform, and to use the platform as a selling point in seizing enterprise-level opportunities. From the point of view of enterprise CX, Zoho can successfully make that argument. Their apps run the gamut from trouble ticketing and help desk to basic contact center voice services, messaging, many CRM functions, automated marketing, and the reporting and analytics needed to support enterprise CX. In short, it’s possible to assemble a bundle from Zoho that contains enough cross-functional, cross-departmental tools to support an enterprise-level effort to manage the customer lifecycle. That puts the Zoho suite on par with other competitive customer experience management toolkits such that in 2024, they were rated Exemplary in the ISG Buyers Guide on customer experience management. Zoho also presented details of the CX roadmap that indicate the company is putting significant investment into enhancing user productivity, communications capabilities, engagement tools and the analytics to support those functions. And the areas of investment appear to be balanced between developing AI capabilities and other aspects of the toolset outside of AI. This builds on top of its work in analytics which propelled the company to an Exemplary rating in the ISG Buyers Guide on Analytics and Data. In light of this, I think enterprise buyers should consider Zoho’s offering for many CX needs. The perception of Zoho as a collection of SMB-focused niche applications is somewhat unfair. Based on the continued evolution of the underlying platform, and the emphasis on tying the disparate components together through AI and data management, I believe the Zoho CX portfolio is well-suited to the needs of many mid-market-to-large enterprises, especially those that are just now taking steps to rationalize and harmonize tools and processes that span CX departments. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://research.isg-one.com/hubfs/Zoho_Evolves_Portfolio_for_Enterprises_Using_AI.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "There Are Gaps in the CX Toolkit Waiting to Be Filled", "mainEntityOfPage": "https://keithdawson.isg-one.com/there-are-gaps-in-the-cx-toolkit-waiting-to-be-filled", "datePublished": "14/01/2025", "dateModified": "14/01/2025", "articleBody": "The breadth of customer experience (CX) solutions created by software providers in recent years has expanded into new areas, usually related or adjacent to existing, more traditional toolkits. Most providers in the space began as more-or-less pure play contact center software providers, so the CX toolset starts with that set of technologies. Products are grounded in core functions for service delivery, like interaction handling, labor management and customer tracking. Some software providers have come into the CX space from other starting points, notably customer relationship management (CRM) and marketing technologies, so they start with a different core toolset, often expanding to add contact center functions. The features aimed at contact center operations are very well-explored and thoroughly understood by both buyers and sellers. Over the years, buying patterns for specific aspects of the portfolio wax and wane, but for the most part someone planning an RFP for a generic contact center knows exactly what they need and (mostly) what features they need to focus on. It is true that the details have changed somewhat in recent years thanks to advances in artificial intelligence (AI) and automation, but the essential service delivery goals remain the same: efficiency, cost control, productivity and CSAT. So, while the basic contours of a CX platform are fairly clear, the bundle of possible components one might find in the suite are shifting. Providers are opportunistically developing or acquiring to feed the gaps that they perceive, mostly around areas that build on the familiar core by adding data management or analytic capabilities that enhance the value of contact center activities. The universe of features thus expands to include tools that don’t focus on the interactions directly, but that add either value to the interactions or help a business understand the ramifications of policies and procedures related to customers. The goal is to help direct customers towards defined outcomes. That’s the path laid out by enterprise CX and Customer Experience Management (CXM)—they take contact center tools and put them into a larger business context to aid marketers and sales teams. It's clear to me that CX software itself (with contact center at the heart) is really the center of an even bigger circle, comprised of tools that hook into those planning and orchestration elements, but that fill a more specific operational need. Field service is a good example: it’s not offered by every contact center or CX provider because it’s not needed in every customer context. It is a specialty, but one that mirrors many of the aspects of traditional service in form and technology, so we can consider it part of the CX toolkit. Which brings us to the key question: what else are we overlooking? More specifically, what else should software providers be considering as expansions (or line-extensions?) to their solution portfolios? There are gaps in the industry’s conception of the CX solution suite that could be filled with niche software acquisitions, partnerships or development, but that are historically left out of the mix. Field service isn’t left out so much as it is chosen or omitted on purpose by providers making strategic decisions about their customer bases. (A similar dynamic is at work with industry-specific versions of tools.) If I were designing a CX solution from scratch, I would include two other areas that are somewhat overlooked. One is customer success tools. This is still an area filled with a mix of niche software and professional services. CX and contact center systems only very rarely directly cover the space in the customer relationship between purchase and service. Can this process be automated and made more efficient? Absolutely, especially with an eye to boosting a customer’s likelihood to expand product usage and ensuring satisfaction. Another area is the agent pre-hire pipeline. Contact centers have long ceded responsibility to the HCM industry to ensure continuous labor flow. They take responsibility for the agent once training and incubation are in place, so most agent management tools haven’t been built to do pre-hire assessment and manage large-scale recruitment. Could this gap be profitable and differentiable for CX and contact center providers? Possibly. If we are now embarking on an industry-wide project to automate just about every process related to customers (which we are), then it makes sense to look for gaps at the operational level that can be filled with niche software or perhaps an AI-based application. The evolution of CX tools so far indicates that providers will eagerly expand their capabilities when three criteria are in play: The additional functions dovetail directly with existing capabilities, as in adding analytics to performance management or using AI to carve out new ways to do existing tasks (e.g., agent assistance). The additions can be made quickly, at relatively low cost and risk, often via partnerships or acquisitions of small niche firms. And the addition allows the software firm to differentiate from some significant subset of the larger CX marketplace. For example, contact center as a service (CCaaS) providers adding CDP or martech firms adding certain agent performance functions (often related to sales efforts, like proactive outbound communications). The faster technology advances, the harder it is for software providers to create differentiation for their solutions. Finding and filling even small gaps like these creates space and time to innovate in core areas. So it’s fair to expect that over the next few years, CX providers will take simultaneous paths that seem contradictory, but are really complementary: beefing up the capabilities of the core interaction handling and measurement while seeking out undeveloped niches in the customer lifecycle where software can improve productivity and unify customer-related activities handled by different enterprise teams. Customer success and pre-hire assessment are two possibilities, and of course there are many others to be explored. By 2028, software for managing customer experiences will focus on automating cross-departmental processes that touch customers. CX buyers should think of this as an opportunity to simplify complex processes under a unified provider’s solution set. When considering how to expand or replace their contact center or CXM systems, they should look at a wider array of providers from across the expanded CX marketplace. And they should press those providers to include more creative applications that don’t leave key CX-adjacent functions isolated as silos. For their part, software providers should be looking left and right at their adjacent markets, and at the niche software that their customers already use, for opportunities to bring smaller software niches into their suites. Not every opportunity will clearly look like a traditional contact center application. But the days when building out contact centers was the easy route to growth are gone and are never coming back. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/There_Are_Gaps_in_the_CX_Toolkit_Waiting_to_Be_Filled.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "AI Use Cases for Field Service", "mainEntityOfPage": "https://keithdawson.isg-one.com/ai-use-cases-for-field-service", "datePublished": "08/01/2025", "dateModified": "08/01/2025", "articleBody": "Field service is an often-overlooked area of the service equation, in part because managing its operations involves tools and activities outside of normal contact center models. Field service has a communications component, which is partly handled by contact centers. However, the bulk of field service management activity has to do with organizing the work of technicians and dispatchers. It also requires constant attention to informational resources about products, assets, locations, real-time conditions and, of course, customers. Use cases for artificial intelligence fall roughly into two categories. One is the group of processes that organize field service from behind the scenes: optimizing the workforce, for example, in terms of shifts or travel, or making sure that a truck roll contains equipment relevant to the specific cases on the manifest for that trip. The second category generally tackles the execution of service contacts: What knowledge resources does the technician draw on to solve the problem, and how do you minimize the time needed to complete the job? AI is impacting this complex mix, as it is everywhere. Some of the best use cases for field service AI are similar to those created for contact centers, and some are unique to the field service environment. In both environments, the goal is to use automated technology to ensure that customer satisfaction is high. For example, services begin with interactions—either communicative ones or those that occur on-site. All interactions require significant amounts of process control and information and often begin with a customer connecting to a chatbot or automated agent to share information about a problem or need. The next steps are to assess the situation, determine recommended actions and urgency, create service tickets and confirm customer entitlements. AI supports these tasks, but these functions just scratch the surface of what is now possible and emerging from field service management applications. In nearly all service cases, customers’ problems need to be analyzed to diagnose the issue, identify potential solutions and compare the issue to past cases across the customer base. These are the things that automation does well, especially scouring knowledge resources to find patterns in problems. Increasingly, AI is applied to the more complex problems of orchestrating the details of interactions. It can predict how long actions will take and help position technicians and their parts, tools and equipment for optimal response times. Field service processes have more moving parts (literally) than contact center processes, and AI is now being tuned to optimize the movement of pieces on the board: grouping work orders by location or priority, for example. All functions that depend on improving efficiency through awareness of resources and context are strong candidates for both automation and AI intervention. By 2026, 4 in 10 enterprises offering field service will start AI automation pilot projects to reduce dispatch requirements and proactively engage customers early in the service process. There are also benefits to applying AI to the work of the technician onsite. The field service industry has talked about augmented reality for some time. Prospects for wider adoption are strong now that software providers are using AI and machine learning to visualize complex objects in two or three dimensions. Applications for AR technology go well beyond field service, including manufacturing, automotive, medical and energy industry applications that are spurring development at a rapid pace. AI also maximizes onsite diagnostics, particularly in combination with predictive analysis of products in situ based on sensor data or Internet of Things information. When used in conjunction with AR and mobile applications for information retrieval, onsite technicians can connect to knowledge bases at the home office, as well as work order details and remote assistance (from humans or automated sources). This makes it faster and more accurate to understand problems and work towards solutions, with better communication to the customer along the way. There are also behind-the-scenes processes that impact the quality and speed of field service interactions. As noted, AI can boost the efficiency and effectiveness of pulling solutions out of knowledge resources. That’s a pretty standard starting point for service delivery in any context. Field service organizations, like contact centers, are also ripe for process improvement in labor management. The dispatch process has a lot in common with the workforce management needs of a contact center—for example, forecasting interaction volume, mapping resources to needs and adjusting based on novel contingencies. In the case of field service, AI can improve how schedules are produced and updated, along with optimizing resources like fleets, parts and tools: the entire process of deciding who should be where, when and with what supplies and information. AI is also being used to dynamically adjust scheduling decisions based on criteria like traffic, weather or new urgent requests. It is especially good at route optimization in real time. Many of those applications fall into the category of improving processes that already exist (and are already pretty efficient). More exotic uses for AI are emerging that might create entirely new paradigms for how complex service requests are delivered. One example is using automation to analyze and understand the context around failure modes in complex products. AI models can be trained to understand where and when failure points emerge and apply that information to other assets where solid data on failure rates may not exist. AI models also have a role to play in assessing sensor data from relatively small training samples to understand how to ensure the continuous functionality of expensive equipment that is hard to service. This can speed the time to value for asset health prediction. AI is not a magic bullet for field service delivery. It doesn’t turn bad processes magically into good ones or create resources where none exist. However, it does provide ways to maximize the outcomes of the resources that do exist and to create new, more efficient processes. As in other areas, service managers are still discovering which processes lend themselves to AI improvements. Many enterprises would like to use their field service operations to generate revenue. This is hard to do when under constant pressure to control costs and deliver top-notch outcomes to high-value customers. Using today’s field service tools that enhance automated processes with AI is a way to turn these risky and complex service interactions into brand-building encounters. When a business can predict a part or machine failure and automatically alert the customer (or fix it remotely), it builds customer confidence and helps justify service relationships and high-end service contracts. The use cases businesses should explore depend on many factors, like the complexity of what’s being serviced and the existing technical maturity of the service organization itself. In other words, an organization with a mature service environment (especially around its contact center) may use tools that lend themselves to AI intervention, like agent guidance, knowledge management and remote diagnostics. These naturally lead to using AI for tasks specific to field service, like automating dispatch and helping customers articulate the true nature of their service needs. Enterprises should be aware that the technology landscape around field service is changing very rapidly. Take stock of the tools used in existing processes and their effectiveness. In evaluating the current generation of field service management tools, enterprises should consider how software providers use AI, for which use cases and how well those providers articulate the ROI and benefits of the technical advances. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/AI_Use_Cases_for_Field_Service.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "What Open Platforms Mean for Contact Centers", "mainEntityOfPage": "https://keithdawson.isg-one.com/what-open-platforms-mean-for-contact-centers", "datePublished": "12/11/2024", "dateModified": "12/11/2024", "articleBody": "Software providers have identified “openness” as a key consideration for contact center buyers. Since there is no generally accepted rule about what makes a system open, it makes sense for us to examine what components contribute to that quality, and why it should be thought of as a good thing. Contact centers have been dealing with the tension between so-called open and proprietary platforms for decades, ever since the development of computer-telephony integration (CTI), which first injected open computing standards into the closed telecom-based world. It has been recapitulated repeatedly ever since. Right now, the industry is exploring what it means to be open in the context of dramatically different technologies for artificial intelligence (AI) and automation. It helps to think of those three ideas as three related concepts: automation is the goal that businesses are striving towards; AI is the enabling technology that makes automation possible; and “openness” is the environmental prerequisite for having both AI and automation. Open platforms are vital for the rapid and broad adoption of generative AI (GenAI) in business because they offer a collaborative environment where ideas can be shared, costs are reduced and innovations are rapidly deployed. There are several important characteristics of an open system. It should be standards-based, rather than built to be proprietary, hindering integrations. It should be, to a large extent, provider-neutral with regard to where those integrations come from, and its working should be transparent, or visible to examination. Those qualities exist on a spectrum and are not always all achievable in every instance. AI tools are an example of systems that are not always perfectly transparent, for example. Buyers should start by equating openness with the ability to move and extract data from a system, to have that system clearly documented and to be able to move from one platform to another without extreme provider lock-in. An open system differs from one that is closed or proprietary in certain important respects: It allows the administrator (or the end users) to perform extensive customization without being limited by provider control. The business can adjust or change features and potentially aspects of the interface. Less open systems provide the business with less control over how the system evolves and how data is managed. Ample integrations are available by default, usually in the form of either built-in connections or extensive APIs. Open systems can have lower upfront costs than proprietary ones, with the caveat that costs rise as a business develops the platform and leverages those ample integrations. (It is also important to note that over time, too much customization can create as much lock-in as a closed system.) In contact centers, open platforms are primarily cloud-based and more recently developed. Open platforms make data about customers and interactions available for analysis by teams outside of the center to understand how to orchestrate outcomes. And openness should lend itself to an array of possible upgrades or enhancements that can be deployed without significant operational disruption or professional services engagements. Openness can also be seen as a proxy for how future-proof a system is. If a business’s goal is to increase the amount of process automation throughout the customer experience (CX), then using AI applications in an open environment creates a hedge against being caught flat-footed with outdated tools. By 2027, customer experiences will be largely driven by processes controlled by automated GenAI tools. The contact center automation process these days often involves efforts to remove variability and error from human work by augmenting people with real time information, agent guidance and other support systems. These work in tandem with front-end automation that speeds and contains interactions within self-service tools. These upgrades to the common operating toolkit are quickly becoming standard fare, but it’s important to remember that they are flatly not possible without the ability to share and move data around, something that was not the default mode of old-school on-premises ACDs and routing platforms. An open technology platform does more than allow for freedom of movement—it fosters flexibility and dynamism within an enterprise that serves to connect the contact center to the rest of the business. And that in turn allows for the development of enterprise CX strategies and programs that drive tangible business outcomes. For the most part, enterprises are adopting openness as a strategy because it provides more options in more contexts and provides a hedge against an uncertain future. Enterprises are not monoliths but are collections of groups and individuals with goals that can be at cross-purposes. So, the relationship between the three ideas (openness, automation and AI) needs to be understood and planned for. Contact centers have long been aggressive about adopting automation, where possible, and are now keen to accelerate that process because of the cost savings that can accrue. In the past, their automation efforts have been confined to their processes, hived off from much of the rest of the enterprise. When you add AI to the mix, though, you find enterprises looking at a much broader effort across departments, ratcheting up the influence of IT. The amount of disruption that enterprises can tolerate appears to be a bit higher than what contact centers are used to, but there appears to be a consensus that both the center and its enterprise must move more quickly to adopt changing tools in order to stay competitive. Moving forward, enterprises should lean into open platforms whenever possible. It may not be possible in certain cases, but those should be thought of as rare and exceptional now. We recommend that enterprises looking to adopt an open system insist that software providers explain clearly both what they mean when they declare platforms “open,” and what we evaluate in our ISG Buyers Guide research in adaptability, including: the extent of the API and integration capabilities; how the platform functions as an onramp to using other applications from that same provider; and how much internal development or customization work is required (or encouraged) to get the most use out of the platform. Buyers should strive to make balanced selections based closely on their real-world usage expectations. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/What_Open_Platforms_Mean_for_Contact_Centers.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Verint Focuses Bots on Contact Center Outcomes", "mainEntityOfPage": "https://keithdawson.isg-one.com/verint-focuses-bots-on-contact-center-outcomes", "datePublished": "05/11/2024", "dateModified": "05/11/2024", "articleBody": "Verint is operating in quite a different marketplace for contact center and agent management technology than existed five years ago. We have seen tremendous innovation and expansion of the available technologies for running centers and optimizing the performance of the human labor pool, as well as an explosion of tools built to automate customer interactions. Agent management tools that were considered fundamental just a few years ago, like call recording, quality monitoring, and even workforce management software, are now heavily commoditized. They have moved into the background as software providers and buyers focus on understanding and deploying much more complex tools built around artificial intelligence. These new offerings are starting to change the way humans and automated systems interact and how enterprises manage both of those labor pools. At its recent analyst conference, Verint laid out the latest steps in its strategy for coping with marketplace changes, including its efforts to pivot from traditional AM tools to software components reflective of its innovations around AI, automation and analytics. Verint noted several important multi-million-dollar deals revolving around its bot products. These are a series of automated “agents” that each focus on a narrowly defined function and slot easily into the overall platform that controls how Verint customers organize data and workflows. Verint’s strategy for bots has been evolving. Two years ago, when bots were new and conversations around AI were fever-pitched, Verint was one of the first providers in the space to separate AI-as-a-platform from AI-as-applications and to discuss contact center AI as a means to achieving specific performance goals on specific tasks. For most of the two years since AI became an industry disruptor, conversations have focused on the best way to implement AI tools for customer experience. Software providers differ in approaches, with some primarily talking about AI as a platform service that enables smart applications and others focusing more on the applications themselves. That is a false duality because buyers can’t be expected to deploy meaningful AI applications without having a solid underlying platform. So, the conversation is really about how to express to buyers the realizable value of the new tools without forcing them to overhaul a sizable portion of operations, which is disruptive. At that early stage, Verint’s approach was to identify specific use cases that could benefit from AI-based automation, and incrementally developed bots as a definitive solution to those problems. That was a smart approach competitively because it indicated to buyers that Verint’s development efforts were focused on problems that were important to contact center managers in the short term: interaction containment, summarization and self-service. As bots were developed, deployed and improved, Verint took its initial argument about identifying specific, immediately helpful use cases and added the critical element of ROI. The provider began to detail exactly what customers were expected to see when using the bots. Verint was among the first to put hard-dollar savings numbers to the potential scenarios. What we saw at the recent conference was the result of this strategy playing out. Verint used real-world examples to describe the experiences of actual contact center customers, who were able to cite actual dollars saved. This authority about customer service outcomes is exactly what buyers need to hear from software providers about these technologies. Verint has also started to differentiate between “copilot” bots and those used for self-service. This distinction got lost in early discussions around contact center AI. Verint and some of its key competitors are now much more up-front about how human labor and automated systems work in tandem, with some applications focused on human productivity and others on interacting with customers. They share common elements, including enabling data and platform solutions, but they are now seen as having different goals expressed in different outcome metrics. (Self-service bots focusing on containment, for example, and copilot bots on boosting human awareness of context and procedure.) In one example, Verint described a sequence of copilot bots working in tandem to support human agents: a Smart Transfer bot, followed by one enabling knowledge automation, then Coaching, plus a bot helping with Wrap-Up. In Verint’s telling, this sequence could significantly reduce average call duration. That helps alleviate fears that improved self-service containment means humans are left with the hardest and longest interactions that machines can’t handle. Verint also demonstrated a new bot called Genie (one of the few to have branding). Genie is an impressive bot focused on advanced business analytics which is aimed at expanding the roster of workers who can get insights without deferring to a dedicated business analyst for data processing. This opens the analysis space to people who wouldn’t necessarily have the time or skills to work with the data but can now get real answers to questions they don’t even know how to ask. Verint executives described the need for this tool in terms of a bottleneck: There are not enough analysts to fill the need for insights. I think it may also be true that there’s too much data touching too many different activities in and around contact centers. It will be interesting to see how Verint quantifies Genie’s value in ROI terms, as it does for the rest of the bot portfolio. Viewed with a longer lens, agent management technology will continue to be upended by AI-focused development. AI applications can dramatically increase human agent productivity and reduce the number of interactions that need to reach those agents. The result has been a shift in the focus of technology away from long-term fundamentals like scheduling and monitoring and towards tools that use more automation to do things like evaluate interactions in bulk looking for performance anomalies. Ventana Research asserts that by 2026, agent training and skill development will be primarily self-directed, using automated scheduling and AI assessments. Agent management in 2024 is more focused on analytics and automation than on enabling shift trading or optimized scheduling. Verint performed very well in ISG Research’s 2024 Agent Management Buyers Guide, with an Exemplary rating and overall leader. The company has considerable capability to provide centers with the core foundational tools while expanding the boundaries of the AM segment with tools that guide, coach and inform agents and then better measure their success. All contact centers are facing dramatic changes in how they structure the labor component of operations. Verint is one of the key software providers capable of helping buyers transition to a more complex model of human/automated hybrid work, including better measuring outcomes and understanding the costs and ROI involved in that transition. Buyers should consider Verint’s contact center platforms, notably the data platform, the array of AI-based bots and the core agent management tools. The core tools are time-tested and well regarded; the new ones come with vendor assertions about ROI. Enterprises should include Verint in any exploration of these systems. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Verint_Focuses_Bots_on_Contact_Center_Outcomes.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Contact Center AI Gain Traction: Profitable Use Cases", "mainEntityOfPage": "https://keithdawson.isg-one.com/contact-center-ai-gain-traction-profitable-use-cases", "datePublished": "29/10/2024", "dateModified": "29/10/2024", "articleBody": "With a flood of artificial intelligence-related tools now available for contact center buyers, it can be helpful to take a step back and review where buyers can expect a quick return on investment and maximum improvement in efficiency and productivity. For now, it appears that there are three broad buckets into which contact center-focused AI applications are clustered. They all relate to agent behavior and activity, including: Front end containment and deflection via self-service, meaning the chatbot/virtual agent universe. Back-end applications that use AI to produce or analyze information that comes from or is delivered to agents. And apps related to measuring quality, coaching, training and other in-center actions. We find a lot of variation and a bit of overlap within each of these three buckets. What's interesting to me is that most of the applications take existing processes or actions that agents deal with and then either add or subtract some motion to improve productivity. For example, chatbots and virtual assistants that raise the containment rate affect the content and quantity of interactions that ultimately reach agents, changing the nature of the skills they need and the key performance indicators that measure success. By siphoning off the bulk of rote, procedural interactions, automated AI systems leave behind longer interactions that often have higher stakes for the customer relationship or higher value transactions that require a human touch. On the back end, we find applications that use enterprise knowledge resources to deliver guidance during interactions and analytics tools that suss out customer sentiment and buying intent. The former moves the needle on standard contact center KPIs like average handle time and customer satisfaction. The latter applications do more for sales and marketing teams that use the information to orchestrate processes leading to desired outcomes—many of which relate to revenue and company health. Finally, the third group is very clearly aimed at reducing the time-costing burden of after-call work, supervisor evaluation, shift trading and agent self-management. New applications for GenAI are emerging all the time: Take any aspect of the agent/supervisor work model and you can find processes that are inherently inefficient, repetitive and time-consuming, and therefore costly and degrading to the customer experience. The vast majority of these processes can—and are—being automated through well-tailored AI applications coming from many providers in the marketplace. When we look at the way AI has been rolled out in contact center tools and platforms, we see an increasing focus on identifying the immediate benefits and return on investment. This has been especially evident in transcription/summarization, compliance monitoring and raising containment rates. Applications with a clear return on investment appear to be the most popular in these earliest days of AI rollouts. But (and there’s always a “but”), the contact center has always been a conservative entity in its approach to technology innovation. It took the better part of a decade to adopt computer telephony integration in the ‘90s. That was a no-brainer, too, but it was significantly disruptive to make it happen. It took about five years to move from time division multiplexing to internet protocol at the turn of the century. It’s taken almost 20 years to get from on-premises to cloud, and we’re still not even halfway to a full conversion. The lesson is that the bulk of enterprises will be slow to invest in AI for contact centers without: A clear demonstration of immediate cost-reduction A pathway to partial or sequential deployment of different apps in different contexts over time Clear examples that identify peer companies across industries with demonstrated success A genuine assessment comparing what the buyer wants to accomplish to the disruption in operations that deployment might cause, and A pitch that includes buyers outside of the traditional contact center and IT groups, especially since marketing and sales are the analytics consumers of the AI learnings about customer behavior. All told, I think contact center buyers want assurance that what’s being created is essential to cost control right now and that it will also provide operational flexibility for the foreseeable future. ISG Research believes that by 2027, customer experiences will be largely driven by processes controlled by automated GenAI tools. One of the most important lessons learned in the past two years is that buyers are genuinely interested in AI applications that demonstrate quick time to value. In other words, show a contact center a tool that automates an agented task or speeds a case to resolution, and you’ll be able to have an extended conversation about how that tool can be integrated into existing technology. On the other hand, start the discussion from the top down, arguing that AI should be everywhere, pervasive across applications in a platform, and the conversation is trickier and likely longer as buyers ponder the potential for disruption and the downsides of transformation. It also suggests that there is common ground between the needs of various teams that weigh in on AI deployments. When decision-makers express a desire for “value optimization,” that’s akin to how contact center managers strive for cost control and productivity improvements. In a recent study (ISG Market Lens, 2024 AI Study, n=200), ISG Research asked enterprise decision-makers to identify specific AI applications currently in deployment; 64% cited customer chat and 57% cited predictive analytics/forecasting. What I take away from these points is that early-stage conversations with customers must emphasize practical, immediate results from specific applications. I believe that after this first wave of successful applications has shown a year or two of real gains, conditions will be ripe for more expansive discussions that take AI from narrow approaches to broader options, making more use of AI as it relates to interdepartmental and back-office workflows. Today’s value-realization proof points grow more apparent every day, and enterprises are increasingly alert to the opportunities. The next step is to use these successful use cases to build consensus among contact center leadership, the IT teams that work with them and executive teams, all based on a shared understanding of how AI creates specific, measurable results in productivity and efficiency. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Contact_Center_AI_Gain_Traction_Profitable_Use_Cases.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Sprinklr Zeros in on a CXM Platform", "mainEntityOfPage": "https://keithdawson.isg-one.com/sprinklr-zeros-in-on-a-cxm-platform", "datePublished": "23/10/2024", "dateModified": "23/10/2024", "articleBody": "Sprinklr’s analyst day in September was an opportunity for the company to dive deeply into its progress in pivoting its product offerings to align with a broader perception of the market for contact centers and adjacent customer-related applications. Sprinklr has described its market as “unified CXM,” or customer experience management. This is nominally aligned with how ISG Research defines the new space emerging from the collision of contact center tools with other systems necessary to manage CX at the enterprise level. For Sprinklr, taking this approach involves a bit of messaging finesse combined with a commitment to building out a very broad set of features in the software. There are indications that the company is having success along both tracks. Of course, messaging along these lines involves persuading a critical mass of buyers that there is no danger or uncertainty involved in taking a non-traditional approach to outfitting contact centers. In other words, it means convincing contact center managers and IT teams that they won't be exposed to a downside by deploying interaction routing that doesn't depend on a standard cloud provider laying down all of the operating software—no penalty in accessing applications, nor future-proofing or in the reliability of the underlying network. ISG Research asserts that by 2028, one-half of the contact centers that replace core platforms will focus that purchase around data tools like CRM or CXM rather than the voice routing engine. This notion has been gaining credence for several years now and was reiterated by several Sprinklr customers who described their experiences using Sprinklr systems to handle high-criticality customer-facing operations. On the product development track, Sprinklr provided analysts with a look at the latest iterations of both contact center and extended CX developments. Some are further down the development road than others. Workforce management, for example, still needs several important features that are currently road-mapped or in development. Sprinklr divides its product set into four related suites, one each for Service, Social, Insights and Marketing. Service now includes a variety of advanced functions like conversational AI, multichannel communications, ticketing and knowledge base management. Some core features of the cloud component include workforce management (still a work in progress) and quality management. It has intriguing analytics and agent-assist features, along with an environment for creating self-service and hybrid bot/human workflows. Sprinklr is one of at least a dozen companies making a serious run at the contact center market from an adjacent segment. The two most relevant adjacent segments are CRM, which provides expertise in tracking customers and managing the data, and marketing technology, which contributes a revenue-centric and analytics-driven approach to customer relations. Sprinklr emerged from the marketing technology segment with tools originally built around managing the marketing components of social media. Coming at contact centers from an outsider position presents both challenges and opportunities. Since most of the core technology needed to run a center is mature and (to some degree) commoditized, competition now rests on being able to differentiate based on elements like analytics, automation, data management and AI applications. These areas allow vendors with more enterprise software expertise (like Sprinklr has in marketing) to achieve quick gains. At the same time, it does put pressure on outside vendors to either create new cloud service tools or build just enough of a portfolio to allow the solutions to ride on top of existing cloud contact center or communication platforms in a bring-your-own-telephony configuration. Sprinklr performed well Exemplary in ISG Research’s recent CXM Buyers Guide, earning a rating as an Exemplary provider. What emerges from our analysis and from spending time with Sprinklr product teams and executives is a picture of a company eager to have the industry adopt its market redefinition as quickly as possible in order to solidify in buyers’ minds this new idea: Building out and running a contact center is inextricably linked to controlling customer behavior through an enterprise-wide CX program. But this requires getting buy-in from a much wider group of potential stakeholders across the enterprise, which can be challenging, while also earning the confidence of the very risk-averse contact center and IT teams who lead contact center buying decisions. The customers Sprinklr featured at its analyst conference expressed confidence in the tools and the integrations Sprinklr provided for building enterprise CX. Even as market definitions remain in flux, buyers should look at Sprinklr’s CXM offerings as one potentially valuable approach to melding contact center and CX operations. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.isg-research.net/hubfs/Sprinklr_Zeros_in_on_a_CXM_Platform.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "CCaaS, CPaaS or UCaaS for CX? It Doesn’t Matter.", "mainEntityOfPage": "https://keithdawson.isg-one.com/ccaas-cpaas-or-ucaas-for-cx-it-doesnt-matter", "datePublished": "18/09/2024", "dateModified": "18/09/2024", "articleBody": "It is unfortunate that business-focused digital communications are sold under three different headings: Contact Center as a Service (CCaaS), Unified Communication as a Service (UCaaS) and Communication Platform as a Service (CPaaS). (And that just counts the cloud options—let us acknowledge the huge, continuing, installed base on premises.) These are terrible ways to describe complex, varied and overlapping offerings. What distinguishes them are: The legacy that provides their point of focus; and How well they provide applications for business purposes. The legacy origins tell us a lot about the strengths and weaknesses of the various platform types. CCaaS, for example, was originally built around the automatic call distributor (ACD), the necessary heart of voice-based customer contact. Similarly, UCaaS’ origin story lies in the business phone system, or PBX, and CPaaS as a platform for mediating between telcos and developers building applications atop telecom infrastructure. CCaaS is the most tightly bound to business outcomes, as one would expect in the heavily measured contact center environment. UCaaS also has a wide range of business use cases at its disposal, many also relevant to contact centers. Those UC use cases are also relevant to efforts to expand the boundaries of the contact center to include knowledge workers and other teams—workers who need communications tools melded with data management in pursuit of enterprise customer experience (CX). So, you can make an argument that the same UC and CC tools (or at least the same underlying platforms) can support the marketing and sales and back-office functions of CX. CPaaS is another story altogether. CPaaS has a problem: It is poorly defined as both a product and a market segment, and it’s focused on being useful to developers and IT teams rather than on its value to business users. As a result, CPaaS risks being crowded out of the market by other types of communications platforms and by customer engagement suites coming from outside the telecom space. Modern business buyers are looking for digital communications platforms that feature an integrated suite of data management and artificial intelligence (AI) applications. CPaaS software providers have been slower to incorporate those applications into their platforms than CCaaS and even UCaaS. Contact center software providers, which compete for many of the same enterprise deployments as CPaaS software providers, have been faster to incorporate AI and workflow automation into their platforms. They have also been aggressive in building out APIs that go well beyond messaging. CCaaS often now incorporates critical tools like knowledge management, AI self-service and automation into the platform, with APIs to support them. This leaves CPaaS software providers behind the technology curve at precisely the moment when enterprises are evaluating the avalanche of new tools available. I think the market needs to be prepared for a spate of mergers, acquisitions and partnerships that connect the three kinds of communications platforms, further erasing the differences and boosting the business value of all of them. This will provide the necessary foundation for the true CX application suites that focus less on the communications aspects than on engagement management, and on driving revenue from customers. In effect, the industry will see two types of platforms that absolutely must be made to play well together: customer experience management (CXM) systems at the top, directing customer orchestration, tracking and interaction management, and communications platforms below that, integrating with telecom networks and knitting business users across the organization together with messaging, voice, video and other baseline needs. There will be overlap between those, of course. And what we may see come out of this is a unified set of tools, with software providers collaborating via huge ecosystems and API connections, sitting atop giant cloud hyperscalers and telcos, ensuring reliability and scalability. Maybe we can call it something cool, like CXaaS, or CX as a Service? The key takeaway here is that the industry is in the process of disconnecting some of the basic aspects of customer engagement from the mechanics of communications. When significant portions of customer engagement have been diverted to automated systems (chatbots or IVAs, primarily), then from the customer’s point of view what they are doing is directly akin to working with an app or a website. This is amplified further by the ongoing shift from voice to digital communications channels. ISG Research asserts that by 2028, most customer communications, both inbound and outbound, will be created and overseen by conversational AI systems. All of this changes the way service and engagement are perceived by the customer in unpredictable ways. From the enterprise perspective, that moves decision-making and process creation farther away from the contact center, which is healthy. And it suggests that the future of the contact center itself will depend less on the underlying communications infrastructure than on the quality of process integrations that link engagement to business goals like revenue and growth. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/CCaaS_CPaaS_or_UCaaS_for_CX_It_Doesnt_Matter.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Businesses Need a More Expansive View of Self-Service’s Value", "mainEntityOfPage": "https://keithdawson.isg-one.com/businesses-need-a-more-expansive-view-of-self-services-value", "datePublished": "20/06/2024", "dateModified": "20/06/2024", "articleBody": "Self-service has changed immensely in recent years. It has gotten better, qualitatively, in delivering answers and resolutions to customers. But it has also gotten extremely complex, relying on a basket of new technologies to achieve results. It helps to look at it through the eyes of the three main constituencies that are affected by it: customers, contact centers and the businesses they sit in. Customers are clearly warming up to modern self-service. When all you got was an IVR or a hold queue, there was almost no value to it from the customer point of view. The limited range of things that it could resolve up to about five years ago made it the go-to customer whipping boy for as long as there has been service. But with the options expanded and “smart,” customers can use it to transact, research, purchase and effectively take control of their side of the relationship. Contact centers are also beneficiaries. When you care about costs, and your costs are largely based on how many agents you employ, then doubling the rate of interactions handled by the automated system can potentially save a lot of money. But it’s at the company level that things get weird. First, because when you raise the rates of interactions deflected away from agents, the business then expects the costs associated with the contact center to decline, and that decline is expected to be manifested in a reduction in headcount. But the resources required to achieve those cost reductions are significant: deflection rates are going up because artificial intelligence (AI), knowledge management and automation tools are being deployed. Those represent a cost increase for the general contact center tech stack. And until a business can fully build out those systems, populate them with appropriate information and determine how agents will interact with a differently informed set of customers, that business can’t cut costs within the center. You need to spend widely on technology and process reform before you can expect to see the benefits and then reduce costs. It’s something of a catch-22, in that you have to spend more to save more, and no one yet knows whether that’s a good deal for customer management in the long term. Contact center buyers (including IT and business teams) are growing increasingly concerned about the cost impacts of embedding AI and automation into the customer experience (CX) application stack. One way through this trap is to see self-service as a bigger opportunity for monetizing customer engagement than most organizations realize. Even if contact center leadership sees it as an engine of deflection, others (CX teams especially) should be viewing it as a window to capture information about customers, including using it for surveys and voice-of-the-customer research, or as an engagement mechanism that allows them to put different, personalized offers and information in front of customers based on data. In addition, when you step back from the center and look at self-service as a CX project, you can see that the same information reservoirs and systems that power front-end chatbots can also work with other customer modes that don’t, at first blush, come to mind as “self-service”—retail kiosking, for example, or web content that dynamically adjusts based on customer intent and behavior. It is notable that a lot of these extended contexts in which customers work with self-service don’t actually look like self-service, which in the customer’s mind still means “talking to an agent.” These engagements look more like research, or shopping, or account management. Doing an automated password reset on a shopping website is certainly self-service, but it’s not the kind of self-service that annoys a customer because they can’t talk to a human. The point here is that depending on what lens you use to look at the changes in self-service, you can perceive it as either a cost-saver, a cost-sink, an engagement opportunity or a monetization strategy, or some combination of all of those. That’s why I think companies need to look well beyond containment to understand the real benefits of self-service. Contact centers still have control over many of the specific interactions via the communications modules that agents use, but others, like marketing teams, are using and providing the information that flows through that communication, like knowledge resources in service contexts, AI platforms and data tools. Today’s self-service is more likely to be multi-modal, longer lasting and seem less like “service” and more like a process of finding something out (pre- or post-purchase) that ultimately leads to greater engagement with the customer, including more agent involvement. That agent involvement ultimately comes at a different point in the process and requires a different skill set than a typical first-tier triage agent. Looking again at those three constituencies that are impacted by the changing landscape, businesses should view self-service more expansively. They should lean heavily on these new communications mechanisms to increase the value of their customer relationships. The key to this is to educate customers on the value they gain from engaging with automated systems. They get faster, more accurate answers that are consistent across channels. They can take their time to ask and re-ask and explore what interests them without being exposed to the call center pressure of time and cost that forces interactions into predefined times and procedures. Contact center leadership needs to understand the complex dependencies among previously separate types of technologies. Modern self-service depends on the careful integration of customer data, company data, transaction processing, knowledge management and conversational AI, and that counts just what is relatively new in the toolkit. Those who decide on tools for the contact center need to adjust their views: given how complex and costly AI and automation projects are, the rationale for self-service must go well beyond containment and the possibility of headcount reduction. Decisions around use cases and deployments need to build in revenue enhancement opportunities and greater access to meaningful data that can be used to predict customer behavior and guide it in the direction they choose. This is how contact center and broader CX teams should be coming together to coordinate plans and goals. They need to bring a solid understanding of how much more expansive today’s self-service is, and how much more valuable to the organization when it is made intelligent and integrated into broader engagement processes. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Businesses_Need_a_More_Expansive_View_of_Self-Services_Value.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script> <script type="application/ld+json"> { "@context": "http://schema.org", "@type": "BlogPosting", "headline": "Verint Turns Focus to CX Automation and AI", "mainEntityOfPage": "https://keithdawson.isg-one.com/verint-turns-focus-to-cx-automation-and-ai", "datePublished": "12/06/2024", "dateModified": "12/06/2024", "articleBody": "Verint held its analyst conference recently, using the opportunity to flesh out how it is responding to the rapid developments in artificial intelligence (AI) and data-related technologies and to changes in the way enterprises consider the purchasing process for contact center-related tools. The market for contact center technology is changing very quickly. It has historically focused on traditional routing-based systems, starting with the automatic call distributor (ACD). ACDs have long functioned as the engine for connecting consumers to centers, even in the digital channel era. Increasingly, buyers are taking a more expansive approach to organizing their contact center tech stacks, and not always using the ACD as the core component upon which to build those stacks. This is especially notable in enterprises that are seeking to use their centers to drive growth and revenue, not just in a reactive call-handling role. In response to that shift, software providers have been keen to develop more complex software portfolios that reflect the innovations around AI, automation and analytics. (The shift is also derived from the fact that commoditization of core contact center tools, like the ACD, forces providers to examine their growth in adjacent technologies.) For many providers, it has been difficult to articulate the benefits of those technologies to contact center buyers specifically, largely because the contact center still operates as a silo relative to other customer experience (CX) teams. Verint has been dealing with both of those elements: steadily developing innovative tools that boost contact center performance while also establishing the contact center as a more integrated part of an enterprise CX program. At the analyst conference, Verint explored a new conception of the market for the contact center (and its adjacencies) that focuses on CX automation. I think that after watching them evolve their message over recent years, in tandem with their technology, they have finally landed on an effective way to present the combination of core contact center technology and extended tools that coordinate data and enhance the capabilities of a mixed contact center/CX team. It is with some satisfaction that I note that the framework Verint is using maps very well to the Customer Experience Management market view expressed by Ventana Research since 2022. It’s clear that Verint has been looking for ways to translate very complex interdepartmental technologies into use cases and benefits for people in specific roles. That has been part of their messaging as well as product development. With regard to AI, for example, Verint has been very clear about identifying the specific use cases in which to deploy AI, and put dollar figures on the proposed benefits and ROI. The company is using the phrase “CX Automation” as a way of describing the functions of its products in the center and the connections that the technology enables the contact center to build with other departments and processes. The reason CX Automation resonates as a way to describe this evolving market is because it focuses on outcomes, rather than activities. CX Automation explicitly acknowledges the changed landscape: new and different buyers, competing visions of a CX tech stack and providers with different priorities replacing the uniformity of the traditional contact center ACD-focused product set. When I look forward 3-5 years, I see a contact center landscape very far removed from the one where a handful of contact-center-as-a-service (CCaaS) and legacy prem companies deliver routing as the core product. It will be an environment in which data is central and communications tools are taken for granted. One can argue whether CX Automation is the best name for a market segment, but it’s a very accurate description of the combined universe of functions that start in the call center and radiate outward to affect every business action that impacts customer behavior. By 2027, 90% of customer interactions will combine automated conversational self-service and live agents, reducing costs, time and enabling agents to focus on high-value interactions.  Another example is the way Verint has developed its Engagement Data Hub, which is the fundamental platform resource that drives just about every other component. Clearly, control of customer and interaction data is a precursor to successful AI outcomes. Identifying the Data Hub as the substrate through which to achieve those AI results is a smart move, and a differentiated one, because not all of Verint’s competitors have this capability. To make the point even clearer, the Data Hub is presented as the place where its AI bots go through continuous training, using current and updated data. This helps clarify the value amid the complexity. Another AI tool that Verint has developed in the past year is a Data Insights Bot that puts relevant insights into the hands of people one step removed from the center, allowing them to see relationships between actions and outcomes and understand the interconnectedness between what happens in the center and the wider world of business goals and outcomes. That’s the difference between this bot and the other, more narrowly defined bots—this one is open-ended and designed specifically for users to “have a conversation with their data.” This could potentially distinguish it from even advanced analytics by its proactivity in surfacing relevant insights before users even ask direct questions. There is clearly value in the way Verint is bundling its offerings. CEO Dan Bodner shared the details of a number of seven- and eight-figure deals that were closed already in 2024, with more potentially to come. That signals an appetite for complexity among serious enterprises and an acknowledgement that the traditional basket of routing and associated tools is no longer sufficient for running a modern contact center. Enterprises should look at the technology model Verint is offering and consider it for its openness, its focus on control of data and the resolute way the company associates ROI with specific use cases in both contact centers and broader CX. Regards, Keith Dawson", "image": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/Verint_Turns_Focus_to_CX_Automation_and_AI.png", "height": 400, "width": 750 }, "author": { "@type": "Person", "name": "Keith Dawson", "url": "https://keithdawson.isg-one.com/author/keith-dawson", "sameAs": "www.linkedin.com/in/keith-dawson-b17b71" }, "publisher": { "@type": "Organization", "name": "ISG", "url": "keithdawson.isg-one.com", "logo": { "@type": "ImageObject", "url": "https://www.ventanaresearch.com/hubfs/ISG_Software_Research_Logo_Color@2x.png" } } }</script>  <script data-hs-allowed="true" src="/_hcms/forms/v2.js"></script> <script data-hs-allowed="true"> var options = { portalId: '2035844', formId: 'fa276fc9-9a16-4673-a644-1fcbedcc3c24', formInstanceId: '4575', pageId: '35458235910', region: 'na1', inlineMessage: "Thanks for subscribing!", rawInlineMessage: "Thanks for subscribing!", hsFormKey: "8a6c37be2ece519d856f775a0d8e127c", css: '', target: '#hs_form_target_module_1552944263900179', contentType: "listing-page", formsBaseUrl: '/_hcms/forms/', formData: { cssClass: 'hs-form stacked hs-custom-form' } }; 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Keith Dawson's Analyst Perspectives