European B2B venture capital firm Hi inov is leading the funding round, with pre-seed investor, tech investment firm Axeleo Capital, increasing its stake.

Actionable will use the funding for hiring in product, engineering and sales, and developing internationally through a network of reseller partners and expansion in the US market.

Founded in 2024, Actionable ingests a company’s raw customer data and reconstructs the customer journey inside a data model specific to its industry. It then predicts customers’ behaviour using predictive models and causal AI, assigning customers a score for churn, satisfaction, serious-complaint risk and repeat purchase.

The company’s work with retailer Carrefour, for example, has found that past six minutes and 12 seconds of a customer waiting at a click-and-collect point, the NPS score drops. 

Actionable is also working with French state railway SNCF and utility company Engie.

The customer data models also factor in the operational reality of businesses, dependent on the sector, including waiting times, loyalty cards, pricing or delivery times. Actionable says this combination of customer data and business context offers the infrastructure needed by AI agents.

The company was co-founded by former Criteo executive Nicolas Rieul and Nans Thomas, formerly of food service digital solutions business Innovorder. The two had observed that large companies were using NPS and other customer measurement programmes but experienced a lack of context about why metrics were changing.

Nicolas Rieul, co-founder and co-chief executive at Actionable, said: “For 15 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.”

Valérie Gombart, co-founder and chief executive at Hi inov, said: “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.”