Traditional market segmentation strategies not yielding an expected return on marketing investments.
A large bakery and confectionery products manufacturer relied heavily on the traditional customer segmentation strategies and was facing issues with effective segmentation. As a result of this, the company was not able to achieve expected returns from the marketing investment.
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Unable to derive granular insights from vast customer data.
The client had access to vast customer data, but it was getting tough for them to analyze them through its existing tools and processes, in order to develop insights. Traditional methods were unable to classify the customers at a granular level based on profitability, and create effective segments for the deployment of targeted marketing strategies.
Predictive modeling to classify customers based on profitability.
We assessed the client’s existing strategies to identify gaps and propose an improved scheme for better customer segmentation. We developed a predictive modeling based solution for the assessment of profitability levels of customers and segment them accordingly. Recommendations were provided on which segments to focus more on, and which segments to be treated lightly.
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Improved marketing ROI through targeted marketing strategies.
The client was able to gain insights on customer segments and sub-segments that provided them maximum profitability. Using this information, they devised a new customer segmentation strategy which helped them in channelizing marketing and promotions spend on these identified segments. High priority was given to the profitable segments, while the segments with less profitability were given less importance.