Determine the contributions of media and the drivers of sales
The Big Picture
A leading technology company was looking to break down the sales of their gaming product into contributions from marketing and promotional activity, and those coming from other base activity. It also wanted to identify the drivers of sales in general and to understand their marketing mechanics. In order to optimize future planning, it was also looking for marketing recommendations.
Two primary areas of focus were involved in the solution. The first was to look at the company’s marketing mix modeling (MMM) to evaluate the performance of various marketing levers and identify their contribution to sales over the years. The Bayesian belief network (BBN) was used to create a network of media variables and redistribute the media contribution. The data used was sourced from POS, the promotional calendar, and paid media, along with earned and owned media. The second focus area was to assess the ROI of the commercial programs currently in place.
The solution approach revealed that 35.7% of media volume contribution was driven directly by TV, 25% of total media contribution came from social media, and 54.1% of social media contribution was driven by PR.
From all of this, an optimization engine was built over the MMM results in order to run different spend-based “what if” analyses. The approach input baseline sales (in absence of TV GRPs) across a series of weeks and the total budget for TV ads (or total pool of GRPs available). The optimization elements assessed were based on the resources available, the constraints and the main objective. The output was then able to determine the optimized allocation of GRPs across the selected weeks.
As a result, the optimization engine generated an additional volume of 7% using the same spends with superior spends allocation. Using BBN, TV flighting was optimized, increasing sales of the product by 5.6%, and it was determined that prioritizing TV support within key seasonal periods increased effectiveness. Digital laydown was another significant variable per the BBN. Optimizing it helped boost the sales of the product by 2.5%, and prioritizing continuity over short, high impression bursts drove higher sales.