The Forrester Wave™: Customer Feedback Management and Analytics Solutions, Q3 2026 finds a market in transition. Just as the “Amazon effect” raised expectations for customer experience, the “ChatGPT effect” is raising expectations for the software that helps organizations understand them.

This is a deliberately selective Wave: With only a small set of vendors included, the evaluation itself serves as a first-level market screen. For buyers, inclusion signals that Forrester views these providers as among the most relevant options in the CFMAS market.

The key takeaways from the evaluation are:

  • Omnichannel customer analytics remains an aspiration for many organizations. We launched this new market coverage to help our clients solve their biggest customer experience problem: merging data from different sources to understand customers more holistically. In researching this new market, we’ve learned two important things: 1. The biggest barriers to CX measurement program success are often data and organizational challenges rather than analytics limitations and 2. Not all vendors offer configurable unified data models, robust customer/profile/entity stitching using unique identifiers, and other features to support this key use case.
  • AI Is Raising The Bar, Not Creating An Easy Button. Many organizations have experimented with large language models to analyze customer feedback. The results are often impressive. They are not always reliable. The most promising approaches combine generative AI and machine learning with business rules, taxonomies, ontologies, knowledge graphs, and other forms of contextual intelligence. This hybrid approach takes advantage of the efficiencies and speed of AI balance with consistency, explainability, and trust and limiting the risk of inaccurate conclusions.
  • Build only where differentiation justifies the burden. Generative AI may tempt organizations to create their own CFMAS, but an enterprise-grade platform requires far more than summarization, sentiment detection, or conversational interfaces. Buyers need scalable ingestion, data model flexibility, identity and entity stitching, governance, analytics, AI controls, integration, and change management. The Wave evaluation includes more than 100 criteria for a reason: These capabilities are hard to assemble, sustain, and evolve. Before choosing a build path, pressure-test whether your team has the funding, skills, roadmap discipline, and executive mandate to match what mature vendors already deliver. Build where it creates durable advantage; otherwise, buy from a proven vendor and focus your scarce resources on adoption, integration, and insight activation.
  • A converged market does not mean converged vendors. While increasingly compete for the same budgets, their histories still shape their products, priorities, and strengths. Some excel at measuring experiences. Others shine in understanding customer conversations at scale. Still others are betting that AI and automation will fundamentally change how insights are generated and acted upon. That’s why this Wave is best read from the inside out. The graphic provides a useful snapshot, but the real story lives in the criterion-level scores.  Remember that your ideal vendor might be “down and to the left” — potentially a Contender that doesn’t have as broad a feature set as others but specializes in exactly what you need.

While every Wave evaluation is a point in time snapshot, the timing of this Wave is especially important context. The evaluation period (June/July 2026) overlapped with the Medallia change in ownership and came just on the heels of Qualtrics’ finalized acquisition of PG Forsta (and with it, InMoment). And just last week, Qualtrics announced a major pivot to focus on simulation and prediction.

What to do next: Request a session with us to discuss the latest developments in this market and understand how the included vendors can help you.

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