Médiamétrie launches its Data Checking solution to validate client database quality

Press release
Less than one year after creating its Data Committee, Médiamétrie brought to fruition one of its ambitious plans with the launch of its ‘Data Checking’ solution

Less than one year after creating its Data Committee, Médiamétrie brought to fruition one of its ambitious plans with the launch of its ‘Data Checking’ solution.
Data Checking can validate the quality of publishers’, operators’ and advertisers’ databases (CRM and transaction) by crossing them with Médiamétrie’s reference panels. Audited by the CESP (Centre d’étude des supports de publicité) and containing over 320,000 qualified contacts (age, gender, SPG, etc.), these panels are set up in accordance with the General Data Protection Regulation (GDPR).
Validation by Médiamétrie provides two indicators:

the quality diagnosis or ‘Kappa number’ established by variable and that allows, on any criterion shared by 2 bases, calibrating the quality of the studied base in comparison to a standard;

the strict Direct Agreement Rate with Médiamétrie’s reference base.

With this solution, Médiamétrie clients can thereby:
Prioritise their internal databases according to quality
Control and compare the quality of databases from partners, providers, etc.
Validate bases that may contain many millions of users with guaranteed statistical accuracy
Improve their data by deleting their least relevant databases
Earn the Médiamétrie ‘label’, a guarantee of quality and trust for advertising or commercial use
Estelle Duval, Data Business Director at Médiamétrie, added: “We have just finished verifying four very different types of databases (deterministic, modelled, CRM, transaction*). The companies with which we work are convinced of the necessity of a tool like this to develop trust of the market. With Data Checking, the Data Committee moves towards its goal of establishing a Data quality standard in France, (through a trusted, independent third party).”
* CRM data (Customer Relationship Management): data collected in the context of a company’s relationship with its clients
Deterministic data: individual data gathered declaratively, often sociodemographic: gender, age, municipality
Modelled data: data estimated from models operating on deterministic or behavioural data
Transaction data: data owned by merchants on their clients resulting from purchasing behaviour
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Confidence interval calculus

Sample size or target in the sample

n =

Proportion observed in the sample or on a target in the sample

p =

%

Warning: only applies to a proportion. The Average Rate is an average of proportions and the Audience Share a ratio of proportions. This tool is provided for information purposes. It cannot be applied for professional purposes without further precautions.

Test of significance of the differences between two proportions

Used to assess whether the difference between 2 proportions is significant at the 95% threshold

Proportion

Sample size

1st sample

%

2nd sample

%

Warning: only applies to a proportion. The Average Rate is an average of proportions and the Audience Share a ratio of proportions. This tool is provided for information purposes. It cannot be applied for professional purposes without further precautions.

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