Paris-based Actionable raises €8.6 million to scale its predictive customer experience platform

Actionable, a Paris-based startup specialising in predictive analysis of customer satisfaction using artificial intelligence, has raised €8.5 million ($10 million) to tell large enterprises which of their customers are about to leave, complain, or buy again, and why.

The round was led by Hi inov, alongside pre-seed investor Axeleo Capital, which is increasing its stake. In September 2024, the company announced its €2 million pre-Seed funding round.

“Value is moving from collecting data to intelligence. Enterprises still pay heavily to store and to measure data, when what is missing is the layer that explains and proposes a plan of action, for teams and for AI systems alike. Actionable owns that layer on customer data, and that is an asset no enterprise outsources,” said Valérie Gombart, co-founder and CEO of Hi inov.

Founded in 2024 by Nans Thomas and Nicolas Rieul, Actionable is a predictive customer experience platform. With its platform, the company states that it enables businesses to predict the satisfaction of their entire customer base on a daily basis.

Rieul, after several general management roles at Criteo and a term as chair of Alliance Digitale, the French digital industry association, said he repeatedly encountered similar Net Promoter Score (NPS) and customer churn programmes across large French companies, with no one able to act on them.

Thomas, former CPO at Innovorder and founder of Wino, a technology platform for local retailers, brought the product experience needed to develop a potential solution.

“For fifteen years, I sat in the same Monday morning meeting: a dashboard says satisfaction or revenue is down two points, everyone around the table looks for an explanation, and nobody can say which customers to call the next day or what to decide right now. The measurement existed. The granularity a decision needs did not. That is the layer we built,” said Rieul, co-founder and co-CEO of Actionable. According to the company, when the client sends its raw tabular data, Actionable automatically reconstructs the customer journey inside a “Common Customer Data Model” specific to its industry, covering transactions, operations, CRM and web analytics, for retail, financial services, insurance, transport, energy, telecoms, and automotive.

The French startup states that the model carries the operational reality of each business: waiting times, loyalty cards, pricing and order-preparation software in retail, load factors and delays in transport, and delivery times in e-commerce.

“Putting an LLM on top of a data warehouse is not enough: without business context, an AI reads raw tables very badly. The hard part is turning hundreds of tables and in-house definitions into a customer model a machine can use without getting it wrong. That is what we spent two years building, industry by industry,” said Thomas, co-founder and co-CEO.

Actionable claims that by unifying, documenting, and enriching customer data with its business context, it provides the infrastructure AI agents need to reshape CRM, customer service, and customer insight.

The company noted that its clients already use Actionable Intelligence, an agent that serves as a data analyst on that model and produces analyses in just a few hours that it claims would take a human analyst several weeks to complete.

Actionable states that its approach is to work with 100% of the customer base across the entire purchase journey, including operational data: every customer gets a score for churn, satisfaction, serious-complaint risk, and repeat purchase, with the cause attached.

The company maps the journeys of 117 million consumers for large enterprises in retail, financial services, insurance, transport and energy. Notable clients include Carrefour, the French state railway SNCF, the utility Engie, and the employee-benefits group Edenred.

Actionable said that at OUIGO, SNCF’s low-cost rail brand, it predicts passenger satisfaction for each traveller, allowing the company to send a goodwill gesture to travellers likely to be dissatisfied before they complain. The company reported that, within weeks, the incremental revenue generated had covered the platform’s cost.

The company plans to use this capital to finance hiring in product, engineering, and sales, and to support international development through a network of reseller partners and the build-out of the US market.