Descripción del proyecto
Una solución innovadora que ayuda a garantizar que los clientes sean premiados al comprar
Las ofertas vinculadas a la tarjeta son una tecnología que conecta una oferta especial con la tarjeta de crédito o débito de un cliente. El cumplimiento de una oferta vinculada a la tarjeta está limitada por su capacidad de obtener el historial de las transacciones de la tarjeta. Para abordar esta cuestión, la pyme francesa PayLead ha desarrollado un nuevo método llamado «account-linked offer» (ALO®), u oferta vinculada a la cuenta, que recopila todos los datos de la transacciones y allana el camino para programas de fidelidad inteligentes basados en patrones precisos de gasto. El proyecto financiado con fondos europeos PayLead está realizando un estudio de viabilidad para validar la solución ALO® en cuanto a su viabilidad comercial y su estrategia de derechos de propiedad intelectual y financiera.
Objetivo
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
Ámbito científico
- humanitieshistory and archaeologyhistory
- natural sciencescomputer and information sciencesdata sciencebig data
- social scienceseconomics and businessbusiness and managementbusiness models
- natural sciencesbiological sciencesecologyecosystems
- natural sciencescomputer and information sciencesartificial intelligencemachine learning
Programa(s)
Convocatoria de propuestas
Consulte otros proyectos de esta convocatoriaConvocatoria de subcontratación
H2020-SMEInst-2018-2020-1
Régimen de financiación
SME-1 - SME instrument phase 1Coordinador
33000 BORDEAUX
Francia
Organización definida por ella misma como pequeña y mediana empresa (pyme) en el momento de la firma del acuerdo de subvención.