Key Takeaways
- The KPMG CEE 2025-2026 barometer evaluated 240 brands in France across 7,061 consumers on 6 pillars of customer experience — the results confirm that the quality of human interactions remains the top differentiating factor
- Empathy is the fastest-growing pillar (+0.14 pts) and Integrity remains the most impactful (19.5% of the CEE score) — two dimensions impossible to manage without analyzing what is actually said in conversations
- Agentic AI is identified as the next disruption: KPMG describes a B2A2C model (Business to Agent to Consumer) where analyzing behaviors, emotions, and conversational signals becomes the foundation of customer experience
- Companies are moving beyond the "POC era": the 2026 challenge is to demonstrate measurable ROI on every AI investment — first contact resolution rate, service cost reduction, response quality
- Conversational analysis emerges as the missing link between brand promises and the reality experienced by the customer: it makes the pillars that matter most measurable
What Does the KPMG 2025-2026 Barometer Reveal About Customer Experience in France?
Every year, KPMG publishes its Customer Experience Excellence (CEE) study, one of the most comprehensive references on the state of customer experience. The 2025-2026 edition, titled "The Search for Value: Reconciling Meaning, Performance, and Impact in Customer Experience", examines 240 French brands evaluated by more than 7,000 consumers.
The central finding is clear: in a context of economic pressure, pricing tensions, and the rise of generative AI, perceived customer value is no longer measured solely by the quality-price ratio. It now integrates usage, reliability, convenience, the emotional dimension, and environmental impact. Consumers are no longer simply looking for "the cheapest" option, but rather a fair balance between price, real utility, lived experience, and consistency of commitments.
What stands out in this edition is the central role that human interactions play in building this value. At a time when chatbots, AI agents, and automation dominate the conversation, the brands that top the ranking — Puy du Fou, Novotel, Chanel, Aroma-Zone — are those that invest in the quality of every conversation with their customers.
The 6 KPMG Pillars: A Framework for Contact Centers
The KPMG model is built on 6 hierarchical pillars that make up the customer experience. Their relative weight on the CEE score is calculated by regression (Shapley Value model):
| Pillar | Weight on CEE Score | Change vs 2024 | What It Measures |
|---|---|---|---|
| Integrity | 19.5% | +0.08 pts | Consistency between brand promise and delivered reality |
| Personalization | 18.3% | +0.08 pts | Ability to adapt the journey to individual needs |
| Expectations | 16.9% | +0.10 pts | Anticipation and understanding of customer expectations |
| Resolution | 16.1% | +0.10 pts | Effectiveness in problem resolution and listening |
| Time & Effort | 14.9% | +0.11 pts | Journey fluidity, elimination of friction |
| Empathy | 14.3% | +0.14 pts | Understanding of the customer, their concerns, and priorities |
All pillars progressed in 2025 — a positive signal reflecting a collective awareness. But the key finding lies elsewhere: the most impactful pillars are those that play out in the conversation.
Integrity means verifying that what the agent tells the customer aligns with the brand promise. Personalization means adapting the discourse to the customer's profile and history. Resolution means listening, understanding, and finding the right solution. Empathy means perceiving frustration or hesitation in the customer's voice and responding appropriately.
In other words, four of the six most impactful pillars on the CEE score are directly measured in interactions between agents and customers. And yet, the vast majority of contact centers only analyze 2 to 5% of these interactions.
The Empathy pillar paradox. Empathy records the highest progression of all pillars (+0.14 pts) and is emerging as a growing differentiator. It is also the most difficult pillar to manage with traditional metrics (NPS, CSAT, AHT). How do you measure whether an agent truly understood their customer's concerns? Only systematic conversation analysis — detecting tone, rephrasing, interruptions, talk-time ratio — makes this pillar actionable.
Agentic AI: The Disruption Described by KPMG and Its Implications for Contact Centers
The KPMG report dedicates an entire chapter to what it calls agentic AI — a paradigm shift from traditional AI. The difference is fundamental:
| Criterion | Traditional AI | Agentic AI |
|---|---|---|
| Operating mode | Predefined tasks, fixed rules | Detection, reasoning, independent action |
| Adaptability | Limited to programmed framework | Dynamically adapts to context |
| Role in customer experience | Executor (chatbot, FAQ) | Orchestrator or active participant |
| Data used | Structured (CRM, tickets) | Structured + unstructured (conversations, emotions, weak signals) |
KPMG identifies two roles for these AI agents in customer experience. The "orchestrator" coordinates functional teams, channels, and journeys, ensuring consistency and personalization without the customer perceiving the behind-the-scenes complexity. The "participant" interacts directly with customers, employees, or partners, answering questions, recommending actions, or completing transactions.
The report goes further by describing five dimensions of the integral experience that agentic AI must serve:
| Dimension | Description (KPMG) | Implication for Contact Centers |
|---|---|---|
| Consumer Centric | Adapt services to individual needs and preferences | Personalize every interaction based on profile and history |
| Data-driven Insights | Real-time signal processing to anticipate needs | Analyze conversations to detect recurring friction patterns |
| Seamless Ecosystem Integration | Connect cross-functional processes | Link conversational analysis to CRM, QM, and training |
| Employee Empowerment | Provide teams with timely insights | Give supervisors immediately actionable agent scorecards |
| Technology Activation | Connect every touchpoint to decision-making processes | Transform every conversation into continuous improvement data |
What clearly emerges from this KPMG analysis is that agentic AI is not limited to chatbots that talk to the customer. It also includes — and perhaps above all — systems that analyze behaviors, emotions, and conversational signals to drive experience quality.
The report explicitly notes that these AI agents "analyze the behaviors, goals, and emotional state of their users, are capable of anticipating their needs, and suggesting or making independent decisions." This is exactly what conversational analysis applied to contact center interactions does: detect frustration, hesitation, satisfaction, commercial opportunity — and transform these signals into coaching and improvement actions.
The B2A2C era. KPMG describes the emergence of a B2A2C model (Business to Agent to Consumer) where the AI agent becomes a major player in the relationship. In this new paradigm, a brand's value will be "less defined by its emotional resonance than by the integrity of its data, its operational transparency, and the perceived fairness of its systems." Contact centers that do not measure what is said in their conversations will be blind in this new world.
Moving Beyond the "POC Graveyard": The Imperative of Measurable ROI
One of the most striking passages in the report concerns the tension between innovation and profitability. KPMG is direct: "Many companies today find themselves with a graveyard of costly POCs whose real impact is difficult to trace."
The diagnosis is harsh but lucid. After two years of excitement around generative AI, leadership teams are demanding results. The 2026 challenge is no longer "what can we do with AI?" but "what value are we truly creating, and how do we prove it?"
KPMG identifies two strategies for demonstrating value:
| Strategy | Description | Example |
|---|---|---|
| "Small Steps" (proof by example) | Small-scale initiatives — assistants, agents, verbatim analysis — to build trust and prove operational gains | At Groupama, AI deployment was driven by measurable business gains: improved internal information retrieval and quality of responses to policyholders via conversational assistants |
| "Big Bang" (global transformation) | Large-scale programs with immediate restructuring | Massive launch of transformative programs whose value is measured after the fact |
In both cases, the report insists on the need for AI-specific metrics: AI-assisted first contact resolution rate, service cost reduction, additional revenue generated, response quality via conversational assistants.
What This Means for Contact Centers
Contact centers are on the front line of this ROI requirement. They were among the first to deploy AI (chatbots, voicebots, intelligent routing), but many struggle to demonstrate impact beyond AHT reduction.
Conversational analysis offers a decisive advantage in this value demonstration: it produces metrics directly linked to business KPIs.
| Business KPI | Associated Conversational Metric | Causal Link |
|---|---|---|
| First Contact Resolution Rate (FCR) | Resolution score per agent, callback reason detection | An agent who doesn't resolve the issue generates a costly callback |
| Regulatory Compliance | Mandatory disclosure compliance rate, consent collection | Every non-compliance is a legal and financial risk |
| Customer Satisfaction (CSAT/NPS) | Empathy score, interruption ratio, active listening time | The correlation between conversational empathy and CSAT is direct |
| Conversion / Upsell Rate | Commercial opportunity detection, closing techniques used | Top performers use identifiable and replicable patterns |
| Agent Turnover | Evaluation fairness, measurable progression, personalized feedback | An agent who perceives their evaluation as fair and useful stays longer |
From Excel spreadsheets to value proof. KPMG notes that "it becomes essential to concretely translate this technological power into the customer experience, to make it a tangible lever of differentiation and no longer just an internal productivity tool." For contact centers, this means that conversational analysis should not remain confined to a quality dashboard: it must directly feed the business indicators that senior leadership tracks.
To learn more about AI-powered quality monitoring KPIs, read our article on AI QM in contact centers.
Integrity: Top Pillar by Impact, and the Most Dependent on Conversational Analysis
Integrity accounts for 19.5% of the CEE score — it is the pillar that most impacts customer perception. KPMG defines it as the ability to "act with integrity, inspire trust through action in relation to society and its environment, deliver on brand promise, and uphold values aligned with those of its customers."
Put differently: is what the brand promises actually what the customer experiences?
In a contact center, this question arises with every interaction. Does the agent follow the brand's messaging? Does the agent provide accurate information? Does the agent honor commitments made by marketing? Is the agent transparent about conditions and limitations?
The report illustrates this requirement with several concrete cases among the Top 10 brands:
| Brand | Integrity Score | What Drives the Integrity Pillar |
|---|---|---|
| Puy du Fou (No. 1) | 8.37 | Promise of wonder and quality kept at every visit — total consistency between communication and lived experience |
| Chanel (No. 3) | 8.30 | AI deployed "behind the scenes, serving the back-office, transparent to the customer, supporting the human" — the Maison ensures that technology never undermines the experience |
| Aroma-Zone (No. 4) | 8.18 | Radical transparency on ingredient origins, formulation methods, and selection criteria — "from producer to jar" |
| Hermès (No. 6) | 8.12 | Total consistency between discourse and reality: French production, craftsmanship, sustainability — every commitment is verifiable |
What do these brands have in common? They don't just promise — they verify that the promise is kept at every touchpoint. And the most critical touchpoint, the hardest to control at scale, is the conversation.
The Chanel Case: AI in Service of Conversational Integrity
The report precisely describes how Chanel uses AI in its contact centers: "Behind the scenes, the use of generative AI serves the back-office, transparent to the customer, and in support of the human. It is deployed in customer service tools to enhance responsiveness and service quality. It is also making its way into clienteling applications to complement and strengthen the action of Advisors, accelerate the capture and analysis of weak signals for continuous improvement."
This is a textbook case for conversational analysis: using AI not to replace the advisor, but to continuously verify that every interaction aligns with the brand promise and to identify areas for improvement.
Integrity cannot be decreed, it must be measured. A brand can invest millions in its communication, positioning, and CSR commitments. If the agent on the phone gives incorrect information, makes an untenable promise, or omits a mandatory disclosure, all that brand value collapses in 3 minutes. Conversational analysis is the only way to verify, across 100% of interactions, that conversational reality is aligned with the brand promise.
To dive deeper into the topic of compliance in interactions, read our article on sales compliance in regulated industries.
Personalization: From Marketing Promise to Conversational Reality
Personalization accounts for 18.3% of the CEE score and 17.2% of the impact on perceived value. KPMG and the Fevad dedicate a full dossier to it, identifying hyperpersonalization as the new strategic lever for e-commerce.
The report describes a shift: "The conversational experience is replacing traditional website navigation. Clicks and scrolling give way to a more immersive interaction, guided by text or voice exchange. This dynamic enhances journey fluidity and relevance."
Three steps are identified for implementing this personalization mechanism:
| Step | Description (KPMG) | Implication for Conversational Analysis |
|---|---|---|
| 1. Collect | Collect customer and usage data in compliance with regulations and without betraying trust | Conversational analysis enriches CRM data with signals expressed verbally by the customer: latent needs, frustrations, unformalized preferences |
| 2. Analyze | Understand behaviors to define near-unique segments as close to the customer as possible | Identify conversational patterns by segment: a loyal customer doesn't have the same expectations as a prospect, a complaining customer doesn't have the same tone as one seeking information |
| 3. Activate | Activate this information across all channels, directly facing the customer | Conversational insights feed agent coaching: adapt the discourse, pace, and level of detail to each customer's profile |
The report notes that this conversation-driven personalization increases the average basket by 10 to 15% according to the e-retailers surveyed, and "also strengthens engagement and loyalty."
Brands That Excel at Personalization Analyze Their Conversations
Among the Top 10 brands, those that dominate the Personalization pillar share a common trait: they invest in a deep understanding of what their customers say.
| Brand | Personalization Score | How Conversation Drives Personalization |
|---|---|---|
| Novotel (No. 2) | 8.09 | Personalized QR codes in rooms, content adapted to expressed preferences, individualized follow-up |
| Chanel (No. 3) | 8.15 | "Le Miroir" program in-store, clienteling applications that capture preferences at every exchange |
| Aroma-Zone (No. 4) | 8.21 | Personalized assessment on the website, scientific diagnostics in-store, recommendations adapted to each profile |
| Amazon (No. 9) | 8.27 | "Rufus" assistant with cross-channel memory integrating conversational history |
Personalization starts with conversational data. The brands that personalize best don't limit themselves to transactional data (purchase history, web browsing). They leverage what the customer says — their words, hesitations, objections, and specific requests. Conversational analysis transforms every interaction into a source of customer knowledge, far richer than a click or a page view.
Struggling Sectors: Where Conversational Analysis Has the Greatest Impact
The KPMG barometer's sector ranking reveals contrasting dynamics. While Fashion & Beauty, Specialty Retail, and Entertainment & Leisure lead, other sectors struggle to renew their customer experience. These are precisely the ones with the highest interaction volumes and the greatest conversational stakes.
| Sector | CEE Rank 2025 | Change | Weakest Pillars | Interaction Volume | Key Conversational Challenge |
|---|---|---|---|---|---|
| Banking | 7th (-1) | +0.01 pts | Resolution, Empathy | Very high | Regulatory compliance (MiFID II, IDD), complaint management, duty of advice |
| Insurance | 6th (-2) | +0.05 pts | Resolution, Time & Effort | High | IDD compliance, claims management, empathy in difficult moments |
| Telecommunications | 9th (=) | +0.15 pts | All pillars at rank 9 | Very high | Retention, sales compliance, complaint management |
| Energy & Natural Resources | 10th (=) | +0.05 pts | Personalization, Expectations | High | Pricing explanation, dispute management, energy transition support |
Why Do These Sectors Struggle?
The report provides interesting insight: in these sectors, "access to data is structurally limited" and companies are "forced to focus on partial indicators." Measurement tools are fragmented — NPS by channel, CSAT by touchpoint, overall AHT — without a unified view of what actually happens in the interaction.
Yet it is in these sectors that conversations are most critical. A customer calling their bank to dispute charges. A policyholder filing a claim who expects empathy. A telecom subscriber threatening to cancel. A consumer who doesn't understand their energy bill. Each of these interactions is a moment of truth where brand perception is built or destroyed.
Conversational analysis enables these sectors to move from partial, declarative measurement ("what does the customer think?") to exhaustive, factual measurement ("what actually happened in this conversation?").
To go further on quality monitoring in call centers, read our complete guide.
Specialty Retail: When the Quality of Human Advice Makes the Difference
In contrast to struggling sectors, Specialty Retail gained one position in 2025 (2nd) thanks to massive investment in human advice quality. The report is explicit: "After several years of hyper-digitalization, retailers are now prioritizing experience consistency and the quality of the relationship."
The report cites several revealing examples:
- Krys establishes itself among the most popular retailers thanks to "the quality of advice, the human dimension, and trust built over time"
- Fnac Darty modernizes its points of sale "to transform them into spaces for support and service"
- BackMarket tests "revaluing direct contact" to strengthen its legitimacy
- Leroy Merlin invests in training programs for sales advisors
The message is clear: in a world where products are becoming standardized and AI automates simple interactions, the quality of human advice becomes the top differentiating factor. And to manage this quality at scale, you need to be able to analyze it.
Human expertise, an irreplaceable competitive asset. The report notes that "as products become standardized and artificial intelligence automates certain interactions, specialty retailers are reaffirming the irreplaceable value of the human." For contact centers, this means the challenge is not to replace agents with bots, but to make every agent as good as the best among them — something only exhaustive conversation analysis can identify and replicate.
AI and Conversational BI: Self-Service Reinvented Through Data
The report dedicates a dossier to the transformation of Business Intelligence, driven by conversational AI. The initial finding is harsh: "Traditional Business Intelligence, focused solely on dashboards, is now showing its limitations: proliferation of dashboards, heavy maintenance, low actual usage. A recent study notes that only 25 to 30% of dashboards are actually used."
The solution described by KPMG? Conversational analytics — the ability to query your data in natural language rather than navigating through static dashboards.
This paradigm applies directly to contact centers. Instead of reviewing a 50-page monthly report, a supervisor should be able to ask: "Which 5 agents struggled the most with price objections this week?" or "What is the most frequent callback reason for product X since launch?"
The report identifies four pillars for making this conversational analytics work:
| Pillar | Description | Contact Center Application |
|---|---|---|
| Action Performance | Track action performance in real time | Track agent score trends after each coaching session |
| Data and AI Role Convergence | Merge data and business skills | Supervisors directly leverage insights without going through data teams |
| Access to AI-Powered Self-BI Tools | Provide data access in natural language | Query conversational data through simple questions |
| Adapted Sector Approach | Adapt KPIs to the business context | Sector-specific evaluation grids (insurance, telecom, banking) |
What the KPMG Barometer Means for Your Contact Center
5 Actionable Takeaways
| KPMG Takeaway | What It Means for You | Concrete Action |
|---|---|---|
| Integrity is pillar No. 1 (19.5%) | Your agents must deliver information consistent with the brand promise on 100% of calls | Implement systematic conversational compliance analysis |
| Empathy is the fastest-growing pillar (+0.14 pts) | Your agents' ability to understand and respond to customer emotions is a growing differentiator | Measure conversational empathy: rephrasing, interruptions, listening time, tone |
| AI must prove its ROI (end of the POC era) | Every AI investment must be tied to a business KPI | Connect conversational analysis to FCR, churn, conversion, and compliance indicators |
| Personalization goes through conversation (18.3%) | Conversational data is richer than transactional data | Leverage conversational signals (expressed needs, objections, preferences) to enrich the CRM |
| Lagging sectors (Banking, Insurance, Telecom) have the greatest potential | Interaction volumes are massive but under-analyzed | Move from 2-5% of calls evaluated to 100% through automated conversational analysis |
Where to Start?
The KPMG report says it clearly: the winning strategy is that of "Small Steps" — targeted initiatives that prove their value before scaling up.
For a contact center, this means:
- Choose a pilot scope — a campaign, a team, a specific call reason
- Analyze 1 month of conversations on this scope to establish the baseline: scores per pillar (empathy, compliance, resolution, sales techniques), top performer vs bottom performer patterns
- Identify the 3 priority coaching areas revealed by the analysis — those that will have the greatest impact on business KPIs
- Launch targeted coaching sessions with concrete examples drawn from the analyzed conversations
- Measure progress month after month, pillar by pillar, agent by agent
To learn more about implementing AI-powered quality monitoring, read our AI QM guide. And to understand how conversational analysis can transform your agent coaching, read our article on data-driven coaching.
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The KPMG CEE 2025-2026 barometer confirms what customer relationship professionals observe in the field: a brand's value is built — or destroyed — in every conversation. The 6 pillars of customer experience are not abstract concepts: they materialize in an agent's tone, the accuracy of information, the ability to understand frustration, the relevance of a recommendation. The brands that top the ranking are those that understood that mastering customer experience means first mastering what is said in conversations. AI-powered conversational analysis makes this possible — not by replacing the human, but by giving supervisors, managers, and leadership the visibility they need to manage the quality of every interaction, across 100% of exchanges, continuously.
Source: KPMG France, Customer Experience Excellence Barometer 2025-2026 — "The Search for Value: Reconciling Meaning, Performance, and Impact in Customer Experience", 7th Edition, 2025-2026.