PayLead
Smart Loyalty Program: Using Data Science to Inspire the Next Purchase
Total Cost €
0EC-Contrib. €
0Partnership
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0PayLead project word cloud
Explore the words cloud of the PayLead project. It provides you a very rough idea of what is the project "PayLead" about.
Project "PayLead" data sheet
The following table provides information about the project.
| Coordinator |
PAYLEAD
Organization address contact info |
| Coordinator Country | France [FR] |
| Project website | http://www.paylead.fr |
| Total cost | 71˙429 € |
| EC max contribution | 50˙000 € (70%) |
| Programme |
1. H2020-EU.3. (PRIORITY 'Societal challenges) 2. H2020-EU.2.3. (INDUSTRIAL LEADERSHIP - Innovation In SMEs) 3. H2020-EU.2.1. (INDUSTRIAL LEADERSHIP - Leadership in enabling and industrial technologies) |
| Code Call | H2020-SMEInst-2018-2020-1 |
| Funding Scheme | SME-1 |
| Starting year | 2019 |
| Duration (year-month-day) | from 2019-06-01 to 2019-09-30 |
Partnership
Take a look of project's partnership.
| # | ||||
|---|---|---|---|---|
| 1 | PAYLEAD | FR (BORDEAUX) | coordinator | 50˙000.00 |
Map
Project objective
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
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The information about "PAYLEAD" are provided by the European Opendata Portal: CORDIS opendata.
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