• ABM (Account Based Marketing)

ABM is the acronym for Account Based Marketing (ABM). This marketing strategy consists of focusing sales and marketing resources on a defined set of key target accounts.

  • API (Application Programming Interface)

This acronym refers to a set of functions designed to facilitate the creation, exchange and integration of services and data between applications using a programming language.

  • BI (Business Intelligence)

Business Intelligence (BI) defines the technologies, applications and practices for collecting, integrating, analyzing and presenting data to support better decision making in the business, sales, marketing and finance verticals. BI systems are essentially data-driven decision aids.

  • Bigdata

The term Bigdata first appeared in 1997 in an article about the technological challenges of visualizing "big data". It refers to information resources whose characteristics in terms of volume, velocity and variety dictate the use of particular technology and analytical methods.

  • CRM (Customer Relationship Management)

CRM (Customer Relationship Management) is a strategy that advocates the centralization, storage, analysis and exploitation of an individual's interactions with a company in order to optimize the management and quality of the customer relationship. It also designates a computer solution intended to exploit data collected during exchanges between a prospect/customer and the company for commercial purposes.

  • CDP (Customer Data Platform)

A CDP or Customer Data Platform in marketing centralizes and orders the online and offline data of its customers in order to exploit them more efficiently. Thus, the company can segment, target and personalize its marketing campaigns to improve its customer relationship. This tool allows the diffusion of information (customer data) to other tools.

  • Customer knowledge through segmentation

The principle is to create a typical customer profile based on exogenous criteria (qualification not based on the relationship with the customer). This segmentation can also be used in prospecting. Segmentation, through the identification and categorization of key accounts, will be essential, for example, for the implementation of a

  • Data Driven marketing

It's about enabling marketers to make decisions based on accurate data and information rather than opinions or hunches.

  • Data Quality  

Data Quality refers to a company's ability to implement actions to ensure that the data in its information systems is correct and durable over time. Data quality control is an important issue for companies. It is about providing correct, complete, up-to-date and consistent data to all users of the data.

The notion of data quality is a generic term describing both the different characteristics of the data and all the processes used to guarantee these characteristics. A data is said to be of good quality when it meets the requirements of its use.

  • Data science

Data Science refers to a set of disciplines of data inference, algorithm development and technology. These are aimed at solving complex analytical problems. Data science is about using data creatively to generate business value through insights, with the goal of helping companies make smarter decisions.

  • Data Visualization

Also called Dataviz, this term covers a set of tools designed to translate raw data into simplified visual representations in order to facilitate analysis and understanding, the objective being to allow companies to analyze a very large volume of data in order to communicate quickly and efficiently about them and to make decisions.

  • Contextual data

Less often used because it is more difficult to collect, contextual data will provide information on the environment of the company or contact. The typical case of contextual data is that obtained during a market study or a survey. Contextual data can also come from very specialized data from private databases (drug databases, vehicle registrations, etc.) or public databases (census, risk zones, etc.).

  • External data

External data is data that is not generated by one of the components of the company's internal information system, or that is not captured internally.

There is no major difference between internal and external data. The only difference is that the company has less control over the external data, when it is entered or generated by an external application. The data quality verification phase will be all the more important in the case of external data, which may have been corrupted during its entry or generation.

External data can be management data, such as sales feedback from a network of partners, or peripheral data, such as weather, stock market prices, or price quotes from competitors. In the context of marketing and advertising, the notion of external data generally refers to third party data.

  • Internal data

Internal data is data entered in the company or generated by one of the components of the information system. There is no major difference between internal data and external data. We tend to have more confidence in the quality of internal data, because it comes from a system that we control.

  • Relational and behavioral data

The relational data will categorize the relationship between the seller and the buyer. Beyond the simple act of buying, it will categorize the "quality" of the relationship: number of contacts, status of the buyer (VIP, exceptional), number of interactions in the year, propensity to open communications...

This data is mostly fed by the buyer's behavior on digital media (website, social networks ...). The problem with this type of data is to be able to link a behavior to a specific contact. This is what Data Management Platforms (DMP) are all about.

  •  Transactional data

As the name suggests, transactional data is information about a transaction and is characterized by at least two key elements: an amount and a date. The most common transaction is the purchase, but it can also correspond to inventory, salaries, sales, etc. This type of data is often hosted in ERP systems.

  • Socio-demographic data

These are all the data that will qualify the profile of the contact: age, gender, place of residence, socio-professional category, function ...

This is generally the easiest data to obtain and the one that will be used for basic customer segmentation or to build a file of prospecting targets. In B2B, this data will be completed by information about the contact's company: sector, size, location. This is typically the type of data that can be found quite easily in open data.

  • DMP (Data Management Platform)


Is an offline and online data management software (cookies and third-party services) that centralizes, sorts, stores, manages and analyzes information about website visitors and company customers. It allows to develop effective and more targeted marketing campaigns, optimized and strategic on all channels for a better ROI.

  • Data Enrichment or Data Appending


Data enrichment is a procedure that consists in completing a database with new information. In short, it is about providing more value to existing data.

Data enrichment is one of the steps in Data Quality.

  • ERP (Enterprise Resource Planning)

ERP is a software package that allows to manage all the operational processes of a company by integrating several management functions: order management solution, inventory management solution, payroll and accounting management solution, e-commerce management solution, BtoB or BtoC business management solution ... in a system. In other words, the ERP is the "backbone" of a company.

  • Funnel

This is the customer journey, most often illustrated by a funnel, which represents the process of converting a prospect into a customer.

This acquisition tunnel is a marketing audience analysis tool that breaks down the customer journey into different stages.

  • First party data

In the field of Internet advertising, first party data or first party data first referred to potential targeting data that is collected directly by the publisher site supporting the advertising. First party data is generally behavioral or declarative data recorded on the support site during previous visits and which is associated with the visitors using a cookie.

The term "first party data" was then extended to all Internet players and therefore refers to all "proprietary" data available to a company or advertiser.

The notion of first party data originally referred mainly to data collected online, but it now also includes CRM / offline data, especially when these are reconciled with Internet data within a DMP.

  • Generative AI

Generative AI is one form of artificial intelligence that is capable of creating new content autonomously, using learning data to mimic human creations (Machine learning).

Generative AIs are used in many fields such as art creation, content creation, data generation, video game content generation, chatbots, content creation for social networks and automatic code generation. Example: ChatGPT, Bards ...

  • Commercial Pipeline

A sales pipeline, or its synonym "sales pipeline", is a sales tool that allows you to visualize your sales process, from contact to closing. The objective of these processes is to transform a prospect into a customer. This overview allows you to measure your conversion rate, and to obtain a lot of information about the duration of the sales cycle.

  • Predicitve analysis

Predictive analysis is a branch of statistical analysis. It consists of analyzing a series of data in order to develop predictive hypotheses. It helps companies to develop and react quickly to changes. It is established in several steps:

  • 1st step which allows to focus on a specific category of data to be collected.
  • 2nd step which is focused on data collection. A very large amount of data is needed for a high accuracy.
  • 3rd step which is the data processing.

In business, predictive analytics can establish patterns, determine trends, detect opportunities, and make optimal decisions to take the right actions at the right time. Data science and machine learning are key technologies for companies looking to leverage massive amounts of information.

  • Data qualification

Database qualification is an operational marketing technique that consists in increasing the value of your data. To do this, you need to "enrich" your database by collecting valid, relevant and functional information about the contacts in it.

Data qualification is one of the steps in Data Quality.

  • Open data

Open data are digital data whose access and use are left free to users, which can be of private origin but especially public, produced in particular by a community or a public institution. They are disseminated in a structured way according to a method and an open license guaranteeing their free access and reuse by all, without technical, legal or financial restrictions.

Access to data aims on the one hand to allow citizens to better control the administration, and on the other hand to exploit these data, which implies that this right of access is accompanied by a right to re-use the data.

Open data is thus at the same time a philosophy of access to information, a movement for the defense of freedom and a public policy.

  • RNVP (Restructuring, Standardizing and Validating Postal Addresses)

This is the acronym for the procedure (usually computerized) used to restructure, standardize and validate the postal addresses contained in a file. This procedure is essential in direct mail marketing, not only to limit the number of undeliverable mailings for one reason or another, but also to limit the cost of this non-delivery. In concrete terms, it consists firstly (restructuring) in ensuring that the descriptive information of the recipient's address is presented in the right sequence: name of the recipient, possible additional address, street, post office box, zip code, town. In a second step (standardization), it will check the length of the lines of text, as well as the possible use of standardized abbreviations, the punctuation or the required use of capital letters for the name of the locality... The national service of the address of La Poste manages the file of the referential of the 36 000 communes of France, the localities, the zip codes and the cedex...

  • Second party data

The term second party data generally refers to data relating to customers or prospects, or even external environmental data, which comes from a partner and which therefore enriches and completes the proprietary data that the company already has.

Second party data is usually collected or exchanged in the context of a partnership or possibly purchased. The line is sometimes blurred with the term third party data.

  • Third party data

Third party data is generally advertising or Internet marketing targeting data that is provided to the advertiser by a third party company other than the publisher used as the carrier site for a campaign.

Third party data is mainly provided by advertising agencies, data specialists or through marketplaces. This behavioral or declarative data is collected and associated with visitors using cookies.

On an e-commerce site, third party data can be used to personalize the offer when it is the first time the user visits the site.

The notion of third party data has been popularized by the uses of digital marketing, but external data can also have an offline origin (partner checkout data, B2B enrichment data, etc.).