A consumer goods brand and its variant were once growing across Asia, but were losing sales due to aggressive competition. It also had a typical problem - not knowing clearly what marketing inputs work across market clusters. RainMan's task was to identify the brand's key sales drivers and help effectively allocate resources to maximise ROI.
RainMan built an econometric model by carefully choosing relevant marketing variables, including distribution, advertising, pricing, variants, marketing inputs and competition inputs. Multivariate regression, along with Bayesian shrinkage estimation process then estimated the short-term and long-term impact of various inputs.
The study found various drawbacks and, importantly, prioritized action points to correct them. Distribution quality was the first area, followed by a revamp of the brand's TV creative and media strategies, which were delivering low lift and high decay. Price sensitivity also indicated where prices could be safely raised, where they needed to stay stable and where other sales drivers could negate the decline in sales due to pricing.
The implementation of the new strategy resulted in an increase of marketing ROI by 20% across all market clusters, with a significant growth in sales numbers.
An Alco-Bev major wanted to understand the sizes of each of the categories of alcohol such as Whisky, Vodka and so on into the future for a plan strategy for a 5 year period.
The advantage of this methodology is that ROI of key digital channels can be compared and spends optimized in line with these insights, significantly improving overall efficiency.
The problem this CPG brand was faced with was a typical problem- Brand had presence across multiple connect points, paid media, owned media ( website, Facebook page etc) and earned media ( Twitter and other social mentions) but not knowing clearly what works across market clusters, and the interrelations between these connect points.