How Renault Group reduced data analysis time with Contentsquare's AI agent

Key metrics

The company

The Renault Group is a major player in the automotive industry, with an international presence and a digital ecosystem that covers several brands (including Renault, Dacia, and Alpine) and a multitude of digital journeys: model discovery, configurators, new and used vehicle inventories, and financing, to name a few.

Within the group, the Performance and Growth team drives digital performance: defining KPIs, collecting data, analyzing user behavior, and experimenting through A/B testing. 

A true ‘command center’ for performance, the team supports brands in understanding user journeys and activating high-impact initiatives.

Since 2013, Renault has been collaborating with fifty-five, a consulting firm specializing in data marketing, to manage and improve the performance of its digital ecosystem.

Renault worked with fifty-five, Contentsquare, and experimentation platform provider Kameleoon to set up a CRO AI Challenge. The goal of this challenge was to fully integrate AI agents to serve digital performance and customer experience.

“Our goal is to support teams, from brands to products, from defining performance indicators to activating insights and experimentation.”

Alexandre Perruche

Head of Performance & Optimization

The challenge

Despite a strong data culture and an existing experimental framework, Renault Group still faced several challenges:

• The difficulty of data analysis: millions of sessions, hundreds of paths, and potential points of friction make behavioral analysis difficult and time-consuming without automation

• Relying on data experts for analysis: digital teams in UX, product, or marketing required support from data and analytics teams to decipher data. They needed a way to make insights more accessible and actionable for everyone.

• A need to accelerate experimentation: Renault Group wanted to identify high-impact optimization use cases more quickly, particularly on ecommerce vehicle journeys.

“Data and performance can seem complicated for UX, product, or brand teams. Our challenge is to empower them to use data more independently.”

Alexandre Perruche

Head of Performance & Optimization

To solve these challenges, Renault Group, along with fifty-five, Contentsquare, and Kameleoon, designed and implemented the CRO AI Challenge—an innovation challenge around AI. The main goal was to empower CRO teams to use AI and test the value of AI agents, so the team could analyze behaviors, generate test ideas, and prioritize actions on the group's sites.

The solution

The CRO AI Challenge was centered around 2 AI-powered platforms :

• Contentsquare's Sense Analyst: an autonomous AI agent that does the heavy lifting of analysis by automatically mapping sites, comparing journeys, summarizing findings, and recommending next best actions—helping teams save hours of manual effort

• Kameleoon's PBX: an experimentation-oriented conversational agent that transforms insights into A/B test ideas, and generates the code needed to implement them quickly

1. Sense Analyst: making data actionable for everyone

Sense Analyst enabled the teams to:

• Access and analyze complex data on user journeys using everyday language. For example, using prompts such as: "Where do we observe the most abandonments in the ecommerce funnel?" or "What behavior differentiates visitors who convert?"

• Get guided and structured analyses without having to directly manipulate complex dashboards

• Identify friction points and optimization opportunities faster and easily share them with business teams

“Sense Analyst is a real accelerator for teams that aren’t familiar with data. They can interact directly with an AI agent, understand behaviors, and formulate actions without always going through expert teams.”

Alexandre Perruche

Head of Performance & Optimization

2. PBX: turning insights into A/B tests, faster

Once the insights were identified with Sense Analyst, PBX took over to:

• Generate concrete A/B testing ideas aligned with the identified challenges

• Produce the variation code to save time on implementation

• Help prioritize tests based on expected impact, traffic, and implementation complexity

The combination of Sense Analyst and PBX made it possible to move faster from observation to action, by relying on a common base of behavioral insights. It covered the entire value chain, from behavioral analysis to test ideation, and even enabled the implementation of experiments on the group's sites.

Use case: building buyer confidence throughout the ecommerce journey

Among the 10+ use cases identified, one of the most promising concerns was optimizing the ecommerce funnel and supporting potential buyers in their decision.

Sense Analyst highlighted friction in the online vehicle purchase journey: some users selected a vehicle but hesitated to continue their process, abandoning the purchase.

Based on this insight, Renault and fifty-five, in collaboration with Kameleoon's PBX, designed a test aimed at:

• Reassuring users at the key moment by displaying customer reviews from other buyers on the selected vehicle

• Making these reviews visible at the right place in the journey to build trust, remove barriers, and encourage conversion

« Ce cas d’usage, qui consiste à proposer des avis clients sur les véhicules identifiés par l’utilisateur, nous a particulièrement marqués. C’est une information clé pour réassurer et engager davantage l’utilisateur dans son acte d’achat. »

By making social proof (reviews, testimonials) more easily accessible at the time of decision, Renault Group expects to increase engagement in the funnel (continuation of steps, clicks on key actions), reduce abandonment on critical steps, and improve the ecommerce conversion rate on the vehicles concerned.

The results

Results after 5 weeks of the challenge:

• 50% time saved on generating insights and recommendations: Sense Analyst automated a large part of behavioral analysis, enabling teams to produce insights and recommendations much faster

• 10+ optimization use cases identified in 6 weeks: the challenge resulted in the design of more than 10 AI-driven use cases surrounding key journeys, with 7 shortlisted recommendations and 3 flagship tests selected for live deployment.

• Data is more accessible for business teams: digital UX, product, and brand teams use Sense Analyst more independently, and data teams are less involved in basic analyses, in favor of more strategic topics

“Since we started using Sense, we’ve seen more people using the solution, and our data expert teams are less frequently called upon for basic analyses.”

Alexandre Perruche

Head of Performance & Optimization

What’s next

The CRO AI Challenge is just the first step. Based on initial feedback, Renault Group is already planning to:

• Deploy winning use cases across the group’s websites (Renault, Dacia, etc.)

• Extend the challenge to a wider audience to multiply ideas and embed the use of AI agents in daily optimization processes

• Explore new paths (after-sales, financing, connected services) using the same AI building blocks

• Explore the uses of Sense Analyst to go further in multi-session analysis, understanding recurring behaviors and detecting weak signals

“Thanks to this new approach, I am convinced that we’ll gradually transform our approach to performance. First, by fostering much stronger adoption from the digital product teams. Second, by improving efficiency between the moment we seek performance information and the achievement of desired results. But what’s most important to me is that this approach truly places data-driven decision-making at the heart of the digital product teams’ strategy.”

Alexandre Perruche

Head of Performance & Optimization