The Analytic Marketing is a term that encompasses a large number of processing techniques and analysis of customer information with primary objective to optimize the implementation and monitoring of marketing actions.

The digest of a study carried out by the firm Deloitte in collaboration with The Institute of Communication Agencies (ICA) to 300 Chief Marketing Officer (CMO) tells us :

• 71 percent believe that one of the biggest challenges is the use of data analytics which they have to face
• 66 % use analytics to make key marketing decisions
• 51 % do not have the internal skills to take advantage of data
• 44 % some of them do not use agencies for support relative to data analysis.

Source : Marketing analytique : écarts importants entre les besoins du client et l’offre des agences ? François Nadeau, Isarta.

You have in your hands a valuable dormant resource ... a little gold mine of information you can use to : 

• know and understand your customers better
• Better target your marketing efforts
• Increase your clientele and your sales

We offer you a personalized approach where we take the time to listen to you, understand your needs and offer you solutions adapted to your reality.

Our expertise is in the development of open source WEB applications, ensuring real-time data entry, management and analysis of companies data

WEB Application Development

• Application for collecting feedback and level of customer satisfaction following the order delivery
• Application for collecting data and evaluating the work of representatives in real time following their customers visit
• Data management of health and safety equipment with dynamic tables of audit schedules
• Migrating paper forms to an electronic format
• Application to collect relevant information from customers in store or at events
• Playful application, the taster game used to entertain customers and evaluate their amateur talent during wine and cheese tastings

Data analysis mandates

• Exploratory Data Analysis (EDA); Data and Text Mining
• Enrichment and optimization of customer data
• Customer profiling (socio-demographic, behavioral, transactional,RFM / B2Bvertical)
• Création des métriques et indicateurs clés de performance (KPI)
• Geomatics and provenance analysis
• Multivariate analyzes and predictive modelling: appetite score, risk and customer attrition
• Customer segmentation analysis
• Shopping Basket Analysis: Market Basket Analysis (MBA)
• Customer Lifetime Value: Customer Lifetime Value (CLTV) and Customer Equity (CE)
• Company training