The CX industry is having a reckoning. Recent CX industry news around Medallia, Qualtrics, and private equity-backed SaaS has put a spotlight on something many retail and hospitality leaders have already known for a while. Traditional customer experience platforms are under pressure, not just financially, but structurally.
When Reuters reported in April 2026 that Thoma Bravo was nearing a deal to hand Medallia over to its lenders, the story was framed as a private equity problem and Medallia’s ability to repay debt financing. Qualtrics has also drawn attention after reports that the banks paused a $5.3 billion debt deal linked to its planned Press Ganey Forsta acquisition, with investor concern tied partly to AI disruption in enterprise software.
But the deeper story is about more than just debt financing issues. It raises a harder question for the customer experience industry: what happens when the model for enterprise CX platforms comes under scrutiny? These platforms are increasingly struggling to gather sufficient customer representation, becoming more contaminated with fake responses, and lacking the depth and reliability needed to power the new world of AI. This isn’t just a SaaS valuation problem — it’s the erosion of a legacy industry methodology.
From the beginning, TruRating built its approach to circumvent these issues.
What’s all this mean for CX?
The short answer is that the category is growing, but the old model is showing strain. The customer experience industry market size continues to expand. Grand View Research estimated the global customer experience management market at $15.55 billion in 2025 and projected it to reach $47.72 billion by 2033. Similar projections from Fortune Business Insights put the 2025 market at $22.35 billion, with projected growth to $84.22 billion by 2034. So, the issue is not demand.
Fundamentally, businesses still need to understand customers. They still need better insight into what happens in stores, and still need faster ways to detect friction, while having proof that their customer experience program drives revenue.
The issue is whether legacy CX models can meet those needs. The latest news about Medallia and Qualtrics suggests the market is asking that question more seriously. Both of these companies are positioned as cloud platforms that manage survey feedback and web scraping, process this data at scale, and deliver it through enterprise dashboards. As AI-based coding makes it easier than ever to replicate these systems internally, that SaaS model is now under financial pressure.
That does not mean these companies lack value. Medallia and Qualtrics both have strong enterprise footprints, experienced teams, and deep customer relationships. These are opportunities for them to refocus on their core offerings. But the market is changing, and the companies that win the next phase of CX will need more than more dashboards. They will need better data to begin with.
From SaaS to DaaS
What we’re seeing today is the start, not the end of the story. Jason Lemkin’s from SaaStr wrote: “Medallia is just the opening act,” which makes a broader point that Medallia may not be an isolated case. It may be one signal in a wider reset for PE-backed SaaS companies bought at peak valuations and financed with debt that is now harder to service.
That financial backdrop is important. Traditional CX was built to solve a software problem: how do I collect feedback, process it, and share it back? Most customer feedback systems hear from a tiny fraction of customers. Receipt surveys, email follow-ups, web intercepts, and post-visit forms often capture only the most motivated respondents, e.g. the delighted, the angry, or the incentivised. Survey data is collected independently from other data sources, and merged after the fact.
All of this is now under pressure from AI – whether it’s from bots contaminating the feedback coming in, or programmers empowered with alternative ways to rapidly build a better mousetrap. Dashboards can now be created, customized, or automated far faster than before. What once looked like a defensible software interface is starting to look more like a roadmap for someone else’s AI project.
It’s worth noting that TruRating was founded to solve a different problem: how to collect real-time validated, enriched customer truth at scale.
For TruRating, the data is the unique thing: the ability to pair every response with 50 points of transaction information; to collect responses from over 80% of all customers in real time; and to validate that every response is from a genuine customer.
In order to do this well, TruRating had to partner with all the major payment providers in order to be deeply integrated into the payment stack, be ready to deploy out of the gate, and able to ingest and process customer feedback and payment and POS data through a modern, real-time data architecture. It took years to build the connections and partnerships, but with a steady focus on creating quality data stream, TruRating did it.
This type of data provides retailers and hospitality companies with a unique proprietary first-party data set that’s ready to power the real-time agentic AI that many companies are already building. That’s why we think of TruRating as Data as a Service (DaaS), not SaaS.
AI is raising the cost of weak data
Is your data set like the Emperor with No Clothes? In the old model, bad data mostly went under the radar. The insight was incomplete, but you could get by just saying that the data was “directional” or “indicative,” as long as you didn’t need to make strategic decisions with it.
AI changes that. When systems start generating recommendations, updating tools, ranking priorities, and making operational decisions, weak data becomes much more dangerous. A model trained on a small, self-selecting group of survey respondents only reinforces biases. It may miss a regional execution gap because the sample is too thin to see it. Or worse, it may confidently tell you that you have a problem with your new store format when, in fact, it’s great — your AI just made an assumption from a single out-of-bounds response.
The quality problem doesn’t stop there. According to Statista, bad bots accounted for 37% of global web traffic in 2024, a 12% increase year-over-year. With that trend, as much as half of all web-scrapped data today could be erroneous or intentionally false; feeding this data to AI to make decisions can only portend bad things.
Moreover, both survey data and web-scraped data is backward looking – happening days to months after the fact. AI moves in the moment; unless it’s fed validated, real-time data on what’s happening now, the decisions it makes are already out of date. In retail and hospitality, in-moment matters. The store, restaurant, hotel, or venue is where the brand promise becomes real. Service, staffing, layout, availability, wait time, and associate behavior in the moment of customer interaction all shape whether a customer spends, returns, or walks away.
That is why TruRating’s transaction-linked feedback captured at the point-of-sale matters. It gives brands a signal from a real customer, in a real location, at the moment the experience happens and from the majority of customers. That’s the quality of signal AI needs if it is going to help businesses make better decisions.
CX industry revenue is growing, but ROI pressure is growing too
Customer experience industry revenue is still growing, but budgets are facing more scrutiny. That is especially true in retail and hospitality, where leaders need to connect experience investments to conversion, ATV, retention, and location performance.
This is where traditional CX programs often struggle. A promoter score can show that sentiment has moved, but it rarely explains what caused the shift. They may tell leaders whether a customer is likely to recommend the brand, but they do not give a store manager clear coaching guidance for tomorrow’s shift. They also make it hard to see whether performance is changing by shift, daypart, store, or region. And when budgets are under review, that gap becomes difficult to defend.
CX leaders are under pressure to prove that customer experience is not just a reporting function. They need to show that CX drives commercial outcomes, supports operational execution, and connects clearly to the P&L.
The next generation of CX will not be judged only by data volume, sentiment dashboards, or reaching out to a single disgruntled customer. It will be judged by how well customer signal helps all teams act, how well the data feeds internal AI workflows, and what reliable outcomes the data enables.
Customer feedback now needs to work at the speed of operations
Promoter scores have a place, but they were never enough for retail operations, nor did they fully satisfy the needs of senior executives. They can help brands understand broad advocacy and sentiment. But they were never designed to run a store, test a strategy, or validate a marketing initiative.
Retailers and hospitality brands need more information to test the uptake of self-checkout, confidently change layouts, optimize staffing and training, measure the impact of promotions, improve product quality, launch loyalty initiatives, and roll out new service behaviours. Each change needs quick validation. Waiting weeks for survey results is no longer good enough.
A single “likelihood to recommend” question, or a single customer’s experience journey, does not tell a regional leader why conversion dropped last weekend, it does not tell a store manager whether associates are offering help, it doesn’t measure memorability and effectiveness of the latest ad campaign region by region, and it does not show whether one checkout model is creating friction in a specific region.
Retail and hospitality teams need a more operational layer of customer truth data. They need to understand what happened, where it happened, when it happened, and what products and customer behaviours it impacted, down to the store and shift level. C-suite leaders need measures beyond NPS: they need to immediately understand the revenue impact of investments, the success of new initiatives and pricing strategies, and shifts in consumer product preferences day by day.
That means connecting customer feedback to the transaction and point-of-sale data at the moment it happens, measuring specific experience drivers, and giving putting that data into the hands of frontline teams, as well as the C-suite, every minute of every day.
What comes next for the CX industry?
The CX industry is not going away. It is becoming more important, but the category is shifting from measurement to action. The winners will not be the companies with the longest surveys or the most complex dashboards. They will be the companies that help businesses hear from more real customers, faster, and turn that signal into better decisions.
For retail and hospitality brands, that means asking harder questions about their current CX platform:
- Are we hearing from enough real customers?
- Is our feedback representative?
- Can we trust the data?
- Do we have enough data to react by store, region, shift, or daypart?
- Can we connect experience to spend in real time?
- Are we able to act on this in the moment?
- Is our dataset ready to train AI agents to act confidently?
These are no longer technical questions; they are commercial ones. Because when customer feedback is merely directional, it becomes easy to cut, but when it is reliably and immediately connected to sales, conversion, ATV, retention, and strategic validation, it becomes a growth lever.
The shakeup was always coming
The Medallia and Qualtrics headlines may look like finance stories. In part, they are. But they also point to a wider reset in the customer experience industry.
The old model asked too much of too few customers, too late after the moment that mattered. It gave leaders scores, but not always answers. It helped teams report on experience, but not always improve it.
TruRating was built on a different belief: that the data quality is the main thing; that the best customer signal is captured in the moment, from the majority of real customers, linked to real transactions, and delivered quickly enough for teams to act.
That belief is becoming harder to ignore. Businesses need a clearer signal, and in the next chapter of CX, that may be what separates platforms that report on what happened in the past from those that shape what happens next.
See how TruRating helps retail and hospitality teams turn real-time customer signal into action — book a demo today.
