Actionable secures $10M to transform customer data into behavioural insights

French customer intelligence startup Actionable has raised $10 million in funding to expand its platform, which helps businesses predict customer behaviour and understand the factors driving it. The funding round was led by Hi Inov, with existing investor Axeleo Capital also participating.

Founded in 2024 by co-CEOs Nicolas Rieul and Nans Thomas, Actionable helps large companies predict customer churn, satisfaction levels, complaint risks and repeat purchases.

The startup aims to address gaps in traditional customer satisfaction surveys and predictive marketing tools. Surveys usually capture feedback from only a small share of customers, while predictive marketing platforms often depend mainly on transaction and CRM data. Actionable combines these sources with operational data collected throughout the customer journey to make predictions for individual customers and identify the factors influencing their behaviour.

Its platform combines transaction records, CRM data, web analytics and operational information into industry-specific customer data models. These models can include factors such as waiting times and order preparation in retail, delays and load factors in transport, and delivery times in e-commerce. The company currently serves businesses across retail, financial services, insurance, transport, energy, telecoms and automotive.

By analysing this data, Actionable can identify operational issues that affect customer satisfaction and predict which customers may become dissatisfied. This allows businesses to improve their services or intervene before complaints occur.

Customers provide raw tabular data, which Actionable uses to reconstruct customer journeys and build a standardised model that reflects the business context behind the data. According to the company, this approach can reduce data engineering work that would normally take months to just a few days.

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 Nans Thomas, co-founder and co-CEO.

The company has also developed Actionable Intelligence, an AI agent that uses its customer data model to analyse information while preserving the business context behind the data.

Actionable will use the new funding to grow its product, engineering and sales teams, while supporting international expansion through reseller partnerships and entry into the US market.