CRM Analysis at La Centrale Using the Datama Extension in Tableau

Context: Monitor the performance of customer search alerts

La Centrale, France’s 1st 100% auto marketplace, specializes in bringing vehicle buyers and sellers together. Its platform offers a wide catalog of used and new cars, motorcycles and commercial vehicles, from both private and professional buyers.

A key reference in the sector, La Centrale is recognized for the reliability of its advertisements and its decision-making tools (car ratings, advanced filters, comparisons), which support users throughout their purchasing process.

With a view to optimizing customer engagement, La Centrale has rolled out a new feature enabling registered users to receive an email alert when a vehicle matching their criteria becomes available. The aim is clear: to maintain the link with prospects, encourage their return to the platform and rekindle their intention to buy.

Given the importance of this functionality to our business, our CRM teams keep a close eye on changes in performance indicators.

However, the data needed for this tracking was previously siloed in different tools: the CRM (Braze) for the number of e-mails sent, the Web tracking tool (Piano) for the traffic generated, and finally the backend (fed into Redshift for BI) for the resulting contacts to owners.

La Centrale’s data engineering team first carried out extensive work:
data flows were developed in DBT, in order to consolidate and harmonize data from multiple sources. The result was a reliable, structured data set in Tableau, now ready for analysis.

The company already relies on Tableau for daily performance monitoring, with data coming from several platforms and internal systems.

It was against this backdrop that La Centrale called on Datama Compare en viz extension Tableau, to analyze precisely the impact of this functionality on CRM performance and revenues generated.

Approach: Gathering data

To measure the real impact of alerts on user behavior, the teams sought to analyze the correlation between :

• • the volume of email alerts sent,

• • user activity after receipt,

• • and the number of contacts generated.

The approach adopted is based on the construction of a market equation, enabling CRM performance to be broken down into the various stages of the funnel.

The following equation has been defined:

This equation models the user journey from receiving an availability email alert to contacting La Centrale. Each component corresponds to a key stage in the funnel and can be analyzed independently.

By integrating this equation into Datama Compare, teams can continuously monitor the variation of each lever and precisely identify the points of contribution to overall performance.

Datama provides you with a market equation generator here to help you customize the breakdown of your KPIs according to your business sector.

Results

Integration in Tableau

Thanks to this upstream preparation, the results can be rapidly exploited directly in Tableau via the Datama Compare extension, which makes it possible to precisely explain variations in contact volumes between two periods, by breaking down the variation by funnel stage (Sent > Click > Contact) and being able to easily break down each stage by campaign in particular.

(Please note that the data below is fictitious – you can find an example dataset here)

The breakdown of the gap by step in Tableau

The drill down of mail volumes sent per campaign

One of the major advantages is accessibility: as Tableau is shared between the teams concerned, Datama analysis is immediately available to all stakeholders, without dependence on the data team for each new question.

Going further: flexible, customized analysis

For more in-depth analysis, the dashboard can be enriched with Table parameters:

• • change analysis periods

• • filter by CRM campaign type

• • or focus on certain phases of the funnel

In this case, Datama adapts dynamically, displaying only the relevant elements according to the parameters selected. Business users thus retain control over their analysis conditions, without the need for new developments or additional preparation time (see this article to understand how to create parameters in Tableau that impact Datama).

An example of date selection and end-user filtering

Benefits

Thanks to this approach, La Centrale has strengthened :

• • the effectiveness of its CRM analyses via
    
    • • Reconciliation and centralization of CRM campaign performance tracking data
    • • accelerated access to key insights

• • enabling teams to make faster, better-informed decisions by giving them greater autonomy thanks to Datama

The integration of Datama Compare into Tableau has accelerated the understanding of performance levers, improved the responsiveness of CRM teams and, ultimately, optimized the business impact of the email alerts functionality.