Leveraging Innovation to Improve CX and EX is a Top Priority
20-Nov-2025
Global
Customer Research
KBE4-01-00-00-00
IT_2025_34112
The last four years have been a roller coaster for the retail industry. Dominant themes that have both rankled and engendered creativity include the effects of the COVID-19 pandemic, the continued movement to the cloud, the maturation of next-level AI technology, and dramatic geopolitical upheaval. Each component has presented both significant challenges and opportunities.
The contact center industry has been leveraging AI for years across all segments. This has greatly accelerated since 2022, first with conversational AI, then generative AI (GenAI), and now agentic AI. AI is being used extensively in retail customer care, encompassing:
-Onboarding and training
-Performance management
-Forecasting & scheduling, agent assistance
-Transcription
-Language translation
-Process automation
-Self-service
-Analytics
The use of AI is essential in retail, with variations based on specific use cases. AI is primarily used for generating content. In contrast, the primary purpose of agentic AI is reasoning, not content creation. Agentic AI results are driven by achieving goals. It can carry out a complex series of activities, including reasoning to create its own workflows and evolve based on feedback. With this subtle difference, solution providers and retailers are learning when to apply which type to further operational and CX goals.
The primary goals of this study are to determine implementation plans of interaction channels, applications, and solutions in the contact center environment in the retail industry and to understand purchase trends. It also investigates the factors that influence product selection.
Decision-makers and purchase decision influencers of retail contact centers (total n=166) were surveyed across business functions, including CXOs, managing directors, owners, senior management, middle management, and others.
Countries include Australia/New Zealand, Brazil, Germany, France, India, Mexico, the Philippines, the UAE, Israel, the U.K./Ireland, and the U.S.
Field work: January to February 2025
Respondents: Decision makers from the 106 Retail organizations
Study period: 2025 to 2027
Author: Alpa Shah
An Integrated Approach Provides a 360-Degree Perspective
Research Objectives and Methodology of Customer Survey
The State of Retail
Global Consumer Trends Disrupting The Retail Industry
The State of Retail Customer Care: 2024–2029
The State of Retail Customer Care – The Prominence of AI
Tariff-Induced Macroeconomic Risks and Growth Opportunities
Retail Decision-maker Priorities
Voice Call and Chat with a Live Agent for Communication are a Popular Choice Among Retail
Voice Reigns and Agents Require Coaching
Retail Organizations Plan to Upgrade AI Voice and Chat Agents in the Next Two Years
Enhancing CX is a Top Priority for Retail Organizations
Delivering Customer Service Proactively is a Top CX Priority
Top Critical Decision-Making Factors When Selecting a CX Solution Provider
Customers Demand Hyper-personalization to Feel Looked After
All Investments Across the Contact Center Solution Suite
Key Areas Improved by Generative AI Technology
AI Virtual Agents Need Some Tweaking
Omnichannel Customer Journey Capabilities Lag Far Behind Customer Expectations
Key Findings
Growth Opportunities Fuel the Growth Pipeline Engine™
Why is it Increasingly Difficult to Grow?
The Strategic Imperative 8™
Benefits and Impacts of Growth Opportunities
Next Steps
List of Exhibits
Legal Disclaimer
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The contact center industry has been leveraging AI for years across all segments. This has greatly accelerated since 2022, first with conversational AI, then generative AI (GenAI), and now agentic AI. AI is being used extensively in retail customer care, encompassing: -Onboarding and training -Performance management -Forecasting & scheduling, agent assistance -Transcription -Language translation -Process automation -Self-service -Analytics
The use of AI is essential in retail, with variations based on specific use cases. AI is primarily used for generating content. In contrast, the primary purpose of agentic AI is reasoning, not content creation. Agentic AI results are driven by achieving goals. It can carry out a complex series of activities, including reasoning to create its own workflows and evolve based on feedback. With this subtle difference, solution providers and retailers are learning when to apply which type to further operational and CX goals.
The primary goals of this study are to determine implementation plans of interaction channels, applications, and solutions in the contact center environment in the retail industry and to understand purchase trends. It also investigates the factors that influence product selection.
Decision-makers and purchase decision influencers of retail contact centers (total n=166) were surveyed across business functions, including CXOs, managing directors, owners, senior management, middle management, and others.
Countries include Australia/New Zealand, Brazil, Germany, France, India, Mexico, the Philippines, the UAE, Israel, the U.K./Ireland, and the U.S.
Field work: January to February 2025 Respondents: Decision makers from the 106 Retail organizations Study period: 2025 to 2027
Author: Alpa Shah
| Deliverable Type | Customer Research |
|---|---|
| Industries | Information Technology |
| No Index | No |
| Is Prebook | No |
| Keyword 1 | retail cx market |
| Keyword 2 | customer experience retail |
| Keyword 3 | retail engagement insights |
| Podcast | No |
| Predecessor | KA16-01-00-00-00 |
| WIP Number | KBE4-01-00-00-00 |