Data & Analytics
An Acxiom survey of 4,000 U.S. and UK consumers and 700 business leaders reveals that 80% of brands find it challenging to manage customer experiences across multiple platforms, partners or providers. The issue stems from departmental silos that need better connection and poor coordination with external partners. Sean Muzzy, global president of Acxiom, advises CX leaders to create connectivity across IT, customer service and marketing teams, especially as enterprises adopt AI. Many companies still haven't fully connected backend systems, making it harder to provide seamless experiences and roll out AI agents. Signs of siloed data include customers being transferred between agents, inconsistent answers, and continued marketing after cancellation. A KPMG survey found only 5% of companies have fully integrated customer-facing functions. Acxiom's study also notes challenges in using AI to orchestrate customer interactions, including accountability and maintaining trust across providers.
Navy Federal Credit Union partnered with Qualtrics to conduct a synthetic data pilot, testing its similarity to and differences from real respondent data, and found that synthetic data performed well in rational judgment and bias reduction, but still fell short in emotion and empathy.
An increasing number of brands are using AI-generated synthetic data to simulate the real world in order to understand customers. According to a Qualtrics report, 41% of market researchers already use synthetic data to supplement or replace human respondents, and 62% plan to use it. However, experts caution that synthetic data still has limitations in accuracy and applicable scenarios, and customer experience teams need to evaluate it carefully.
Voice of the Customer (VoC) programs may seem simple, but truly effective ones require deep exploration of customer needs, going beyond surface-level data. This article draws on insights from Community Health Network and West Monroe experts to discuss how to achieve dual improvements in experience and operations by broadly collecting feedback, integrating employee input, and optimizing presentation methods.
CRM, journey analytics platforms, and AI-driven insights are ubiquitous, yet many enterprise growth leaders still face a persistent pain point: these intelligences have not been effectively converted into revenue across the full customer lifecycle. This is not an insight problem, but an execution problem. The article points out that data silos, disconnection between service and sales, and an overemphasis on acquisition while neglecting existing customer value are the three main causes of revenue leakage. It proposes that embedding AI into CRM and frontline workflows, enhancing rather than replacing employees through a human-in-the-loop model, treating service interactions as potential revenue moments, and shifting metrics from acquisition to customer lifetime value are key paths to bridging the execution gap.
When AI customer service knows nothing about customer history, and real-time conversation demands collide with overnight batch processing architectures, enterprises face a paradigm crisis in data infrastructure. Qualtrics data shows that AI customer service has a failure rate nearly four times that of other AI applications, with 88% of organizations having deployed AI, but only about one-third achieving true scale. This article provides an in-depth analysis of the transformation logic from 'customer data platforms' to 'contextual data platforms,' pointing out that enterprises need to build a real-time data layer to support conversational experiences while retaining their existing CDPs.
Survey data released by Dunnhumby on Wednesday shows that most consumers are open to retail media influencing their grocery shopping decisions and are most likely to respond to tailored messages based on their shopping behavior. About 70% of respondents trust personalized product recommendations based on previous purchases, but only 30% trust recommendations based on 'similar people.' Consumers hold positive attitudes toward technologies like personalized pricing that offer tangible benefits, but find emerging technologies such as agentic shopping 'intrusive or unnecessary.'
The latest research by Watermark Consulting indicates that from 2016 to 2024, national banks rated by JD Power as leaders in customer experience achieved cumulative total stock returns of 251%, compared to only 104% for laggards. Experts suggest banks start improving experience by addressing 'low-hanging fruit' such as long wait times and opaque fee disclosure.
T-Mobile has long been customer-centric, but in optimizing its digital experience, it once overlooked behavioral data and relied too heavily on surveys. Senior Consumer Insights Manager Carly Rintisch drove cross-departmental collaboration, combining behavioral data with survey data, and adjusted the survey language style, reducing survey length from 10 minutes to 2 minutes. With Qualtrics AI, the team was able to precisely identify pain points such as difficulty finding benefit activation information, and drove website content optimization.
AI deployment is forcing enterprises to confront knowledge management issues they have long avoided. Experts point out that uncleaned knowledge bases can cause AI to deliver incorrect information to customers, damaging trust. Enterprises need to resolve data cleaning and integration issues before vectorization, and establish governance mechanisms and human fallback strategies.