Company mission
Founded by Guy Mercier,
MMBD offers cutting-edge expertise in analytical marketing (Python, R, SAS), including enrichment, modelling and data analysis transactional, data compiled from different contact points and customer interaction.
Customer data is omnipresent
- Invoices, transactions and data from contact points with the clientele ... the « touchpoints »
- Data from Geolocation mapping and where customers come from
- Data from the telephone call register (incoming, outgoing) of customer service
- Chronological data of inventories (SKU) and movements of store customers
- Data, traces of our daily newspaper compiled from social media
- Visitor data on your WEB site IP geolocation and domain name
- Data from your direct marketing campaigns, mailings and flyers, etc.
In fact, what data should we prioritize?
What types of analyzes are useful and profitable in the short and medium term?
How much does it all cost?
Faced with these unknowns, it is important to keep our bearings firmly anchored in our business reality ...
Trend: Change in sales by industry (%)
Industry sample, Seasonally adjusted data — June 2021 vs June 2020
Bulletin Board (RSS) : Articles for the Dadas of Data
Analytics Vidhya
SQL: A Full Fledged Guide from Basics to Advance Level This article was published as a part of the Data Science Blogathon. Introduction According to the Bureau of Labor Statistics, … 2022-01-19 11:41
Interesting Python Projects With Code for Beginners – Part 2 This article was published as a part of the Data Science Blogathon. Introduction In my previous article, I discussed three … 2022-01-19 11:10
Which is Better for Machine Learning: Flask vs Django? This article was published as a part of the Data Science Blogathon. Introduction We all know how popular the Python … 2022-01-19 10:48
Min Heap in Python and its Operations This article was published as a part of the Data Science Blogathon. Introduction We will learn in-depth about the min-heap … 2022-01-19 10:36
Different Types of Regression Models This article was published as a part of the Data Science Blogathon. Introduction Regression problems are prevalent in machine learning, … 2022-01-19 10:23
Build a User Authentication System with QR Code Scanner using OpenCV This article was published as a part of the Data Science Blogathon. Computer Vision has opened up a plethora of … 2022-01-19 09:36
A Super Helpful Month-by-Month Plan to Become a Data Engineer in 2022 Overview This article will help you to achieve your career goal to become a Data Engineer in 2022 We will … 2022-01-18 14:56
Flight Fare Prediction Using Machine Learning This article was published as a part of the Data Science Blogathon. Overview In this article, we will be analyzing … 2022-01-18 14:23
Hacking Into Nvidia Nemo Script(Download Common Voice) This article was published as a part of the Data Science Blogathon. Introduction to Nvidia Nemo Script   Credits: Nvidia … 2022-01-18 13:42
Microsoft Malware Detection This article was published as a part of the Data Science Blogathon. Introduction As a part of writing a blog … 2022-01-17 12:11
Secure network access requires username and password : Secure network access .
Make your data talk
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 : Analytic Marketing: Significant Gaps Between Customer Needs and the agency offer? 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.
Expertize and mandates
Our main area of expertise relates to enrichment and database modelling, transactional data, data compiled from different customer contact points, social media.
We use a range of powerful models and tools that allowto quickly and inexpensively analyze commercial databases (Python, R, SAS).
Data analysis mandates
- Exploratory Data Analysis (EDA); Data and Text Mining
- Enrichment and optimization of customer data
- Customer profiling (socio-demographic, behavioral, transactional,RFM / B2B vertical)
- Creation of metrics and key performance indicators (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)
- Design of custom WEB applications to capture, enrich and analyze real-time customer data at touch points (Django, JQuery, AJAX, REACT, REST framework, CSS, etc.)
- Company training
MMBD also offers services to point and select the best candidates for rental lists :
- Retail stores
- Philanthropic industry
- Magazines and newspapers
- Financial sectors, insurance, banking, credit cards, etc.
... Lear to Make your data talk