Paris-based customer intelligence startup Actionable has raised €8.5 million in fresh funding, with plans to expand its product and engineering teams, strengthen sales and push into international markets, including the United States.
The financing was led by Hi inov, with participation from existing pre-seed investor Axeleo Capital, which is increasing its stake in the company. Actionable had previously announced a €2 million pre-seed round in September 2024.
Founded in 2024 by Nans Thomas and Nicolas Rieul, Actionable is building a predictive customer experience platform aimed at giving large companies something traditional dashboards often struggle to provide: an indication of which individual customers may leave, complain or make another purchase, along with the factors driving that behaviour.
Rather than limiting customer analysis to surveys or aggregated satisfaction scores, Actionable says its platform can assess an organisation’s entire customer base each day.
That distinction sits at the centre of the company’s pitch.
Rieul said his experience in senior management roles at Criteo and as chair of French digital industry association Alliance Digitale repeatedly exposed the same problem inside large companies. Businesses were collecting Net Promoter Score and churn data, but managers still lacked enough detail to decide which customers needed attention and what action should follow.
“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,” Rieul said.
Turning scattered company data into customer-level predictions
Actionable’s technology starts with raw tabular data supplied by a client. The platform then reconstructs the customer journey using what it calls a Common Customer Data Model, bringing together information from areas including transactions, operations, CRM systems and web analytics.
The company has built industry-specific models for sectors including retail, financial services, insurance, transport, energy, telecommunications and automotive.
This industry context is important to Actionable’s approach. A customer journey in retail, for example, can involve waiting times, loyalty programmes, pricing and order preparation. Transport businesses may instead need to account for load factors and delays, while e-commerce operators may focus on delivery times.
Thomas argues that simply putting a large language model on top of an existing data warehouse does not provide enough business understanding.
“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,” Thomas said.
Actionable says the resulting data layer can also support AI agents used across CRM, customer service and customer insight functions. Its own Actionable Intelligence agent works as a data analyst on top of that model, producing analyses that the company says can be completed in hours rather than the several weeks they might otherwise require from a human analyst.
Every customer receives a risk and behaviour score
One of the more unusual elements of Actionable’s model is its attempt to analyse the full customer base rather than a sample.
The company says every customer can receive individual scores covering churn, satisfaction, serious-complaint risk and repeat purchase likelihood, with an explanation of the underlying cause attached to each prediction. The assessment can incorporate operational information from across the customer’s purchasing journey.
Actionable says its platform currently maps the journeys of 117 million consumers for enterprise customers operating across retail, finance, insurance, transport and energy.
Its named clients include Carrefour, SNCF, Engie and Edenred.
One deployment offers a clearer picture of how the technology is intended to work in practice.
At OUIGO, SNCF’s low-cost rail brand, Actionable says the platform predicts satisfaction at the individual passenger level. That enables OUIGO to identify travellers who are likely to be dissatisfied and potentially offer them a goodwill gesture before a complaint is made.
Actionable says the additional revenue generated from the programme covered the cost of its platform within weeks.
Fresh capital to support hiring and US expansion
The new funding gives Actionable additional resources to move beyond product development and deepen its commercial reach.
The company plans to recruit across product, engineering and sales, while developing international operations through a network of reseller partners. It is also preparing to build out its presence in the US market.
Hi inov co-founder and CEO Valérie Gombart described Actionable’s opportunity as part of a broader shift from simply storing and measuring enterprise data toward extracting intelligence that can directly guide decisions.
For Actionable, the challenge now is to turn that proposition into a larger international business. Its bet is that companies already possess plenty of customer information. What they are missing is a reliable way to convert those records into an answer to a much more immediate question: which customer needs attention next, and why?
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