Expertise 2 minutesPress coverage by Economie Matin on 10.05.2023 ARTICLE E-retail media is taking on a major role in the retail market. This new way of communicating with consumers is made possible by data technology. Lucky Cart, a French company, is a leader in this field, offering proprietary technologies to predict consumer consumption and expectations…
La Tribune – “E-retail media” : measuring performance beyond ROI
Expertise 4 minutesPress coverage by La Tribune on 15.05.2023 ARTICLE Over the past few years, e-retail media has experienced a boom that continues to attract a multitude of diverse players, and with them, a multitude of equally diverse solutions and campaigns. According to the Observatoire de la Pub (and included in the IAB’s cartography), brand…
Interview of the month: Romain Charles – CEO of Lucky Cart by FEVAD
Expertise 6 minutesRetombée presse par la FEVAD le 09.03.2023 ARTICLE We had the pleasure of interviewing Romain Charles, successful entrepreneur and CEO of Lucky Cart, a cutting-edge technology company offering advanced promotion personalization and performance measurement services. For him, the future will be ultra-personalization. Understanding each shopper’s behavior is the only way to reach them…
Personalizing the customer experience to improve engagemen : trend or necessity?
Expertise 6 minutesVirginie Chollois, Marketing & Communication Manager senior at Lucky cart. 10.05.2023 Customer’s journey Personalizing the customer experience has become the key factor for companies to succeed and stand out from the crowd. As technology advances, consumers expect a personal relationship with their favorite brands. To satisfy this growing customer demand, companies need to…
In-house Machine Learning and the journey towards better performance
Expertise 12 minutesBy Lina Mejia, Data Scientist at Lucky cart. 2022/10/25 Are in-house Machine Learning projects better than on-shelf? The answer is obvious: as with most things, it is preferable to have something custom-made rather than a generic solution. But why exactly? Why is there so much supply and demand for on-shelf pipelines and models?…
What to remember about the practical use of data
Expertise 15 minutesBy Virginie Chollois, Agile Marketing Manager senior at Lucky cart. 2022/10/24 Indeed, we are currently right at the heart of the matter. Data allows us to analyse, to see what the eye cannot see, to predict shoppers’ consumption and therefore has an immediate impact on business.Once the subject has been established, let’s go…
How to process millions of data in real time to hyper-personalize the shopping experience?
Expertise 10 minutesWritten by Vincent Oliveira, Chief Technical Officer at Lucky cart. 2022/10/21 At Lucky cart, we truly believe that every shopper is different. But the reality is that they have an extremely similar shopping experience on every e-commerce website. That’s why Lucky cart was created, a powerful platform that uses Big Data to personalize…
Personalization of offers through targeting vs. ultra-personalization through machine learning?
Expertise 11 minutesWritten by Maxime Antoni, Chief Product Officer at Lucky cart. 202/10/12 Personalization is a strategic issue for the retail sector. Initially considered as a simple tool to improve the relevance of marketing messages sent to shoppers, personalization has over time become an integral part of a successful shopping experience. In recent years, many…
Why measuring performance in E-Retail Media is a must and how to move beyond ROI.
Expertise 9 minutesWritten by Alexandra Caillet, Head of Business Insights and Measurement at Lucky cart. 2022/10/07 Over the last few years, E-Retail Media has experienced a growth that continues to attract a multitude of players and, with them, an increasing number of solutions, as well as a large portfolio of campaigns. This market growth is…
The 3 roles of the data team in the service of our clients
ExpertiseInside Luckycart 9 minutesWritten by Julien Guitard, Chief Sciences & Data Officer and the Lucky cart Data Team. 2022/09/13 Lucky cart’s data team is made up of a dozen people, 1/3 for each role: data scientists, data engineers and data analysts. Its aim is to design, develop, operate and maintain the algorithmic factory of our…