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Smart Loyalty Program: Using Data Science to Inspire the Next Purchase

Project description

An innovative solution helping to ensure customers are rewarded when they buy

Card-linked offers (CLOs) is a technology that connects a special offer to a consumer’s credit or debit card. CLO performance, however, is limited by its ability to obtain card transaction histories. Addressing this, the French SME PayLead has developed a new approach called account-linked offer (ALO®), which collects all transaction data and paves the way for smart loyalty programmes based on precise patterns of spending. The EU-funded PayLead project is carrying out a feasibility study to validate the ALO® solution in terms of its commercial viability and financial and intellectual property rights strategy.


Credit and debit card transaction histories are a valuable source of information about their owners’ purchase patterns. This information can be used to accurately address promotional offers, called Card Linked Offers (CLO). Today, CLO performance is limited due to the nature of accessible information from credit cards: it is often fragmented and and is not customer-centric as it does not take into account habits / historic of purchase to develop personalized recommandations. It is basic coupon with no intelligence.
PayLead is a French SME founded in 2016 developing a new approach - called Account-Linked Offer (ALO®) - that allows all transaction data to be collected, not only bank card payments. ALO is based on cross-checking transaction data with several external sources making it possible to improve prediction relevance and accuracy. This allows us to create smart loyalty programs based on precise patterns of spend propensity.
The bidding of offers is based on profiling and targeting resulting from customer payment flow analysis at both the bank level and external partners (merchants, third-party solutions).
Profiling is done on the basis of big data principles through machine learning algorithms and non-linear classifiers. The first commercial partnerships have been finalized to allow speed, critical mass of customers, users and partners in order to legitimize the offer in a very competitive market in terms of marketing and loyalty solution.
We have validated our model, developing a profiling and decision-making engine for merchant based on machine learning, and we prepared us for scaling. We have built our tech platform and we are now ready to take off through the consolidation of stakeholders.
We are currently deploying our solution with a major bank (BNP Paribas) and a major insurance group (Groupama). In 2023 we expect the have €23M of revenue and €13M of EBITDA.
This phase I project will support further the development of our go-to-market strategy in Europe

Call for proposal


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Net EU contribution
€ 50 000,00
24 cours du maréchal foch
33000 Bordeaux

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The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.

Nouvelle-Aquitaine Aquitaine Gironde
Activity type
Private for-profit entities (excluding Higher or Secondary Education Establishments)
Other funding
€ 21 429,00