Marketing Mix Modeling: From Marketing Origins to HR
Marketing Mix Modeling was developed in the 1990s by consumer goods companies to optimize their marketing mix and allocate their financial, human, or logistical marketing resources. This method remained largely confined to this sector until recently.
Two phenomena have brought this Machine Learning method to the forefront in many companies, regardless of their sector, beyond consumer products:
The limitations shown by traditional digital performance measurement systems (the end of third-party cookies, challenges in direct attribution measurement, lack of visibility into the impact of competitive strategies, etc.)
The clear impact on business, more generally, of more or less predictable exogenous phenomena like economic or sectoral crises, pandemics, inflation, etc.
Similarly, Applying Customer Marketing Techniques to HR Marketing
However, this method had never been applied to optimizing recruitment marketing.
That has changed with the French Navy!
For over a year now, it's a global first: with the support of Insign's data teams, they are using Marketing Mix Modeling methods and tools to continuously optimize the allocation of its marketing resources with artificial intelligence. By better understanding and addressing the seasonality of its recruitment, saturation phenomena, base effects, latency times of its actions, the marketing teams of the French Navy’s recruitment service can simulate the resilience of their marketing and actions in a changing recruitment environment.
How MMM Optimizes Recruitment with AI
To achieve this, the French Navy integrates all its marketing actions (advertising investments, recruitment fairs, field actions of recruiters, etc.) and compares them to data from its recruitment environment (marketing activities of other major recruiters in the region, macro-economic data, unemployment figures, geopolitical events, seasonality, etc.).
This method now allows them to better understand the phenomena and actions to which their recruitment results are most sensitive, enabling them to adjust their strategies accordingly. Moreover, the insights gained allow them to simulate new scenarios for the evolution of their recruitment environment and plan their actions accordingly, making their attractiveness more resilient in the long run.
The application of Marketing Mix Modeling to recruitment topics, symmetrically to commercial marketing, is thus largely validated by the case of the French Navy!
For more information, check out our interview with the French Navy in eMarketing magazine
