The concept of Big Data is as old as computing itself. Crunching massive amounts of data is what computers do best. Yet automation in and of itself is not sufficient for accurately analyzing and extracting workable solutions from data — be it Big or otherwise.
Case in point. Using data as a guidepost we were able to generate sales lift of better than 27% across a Consumer Package Goods (CPG) company’s product portfolio. Some products experienced as high as 38% lift during the test period. The results are all the more remarkable considering the category grew by just 1.5% over the same period. In addition, prior to this campaign the firm was mired in a trend of flat to slightly decreasing sales volume spanning the previous five years.
Data aggregation, analysis, and triangulation played a significant role in reversing the downward trend and putting the firm on track for consistent short- and long-term growth—underscoring the importance human insight, intuition, and expertise plays in effectively capitalizing on Big Data.
Our first step was gathering five-years of sales data. We segmented the information by region and channel [retail versus foodservice in this case] to help understand the impact of sales and marketing programs on sales revenue. IRI category development data provided another key element in discovering product demand and consumption behaviors in comparison to the firm’s overall ACV levels. Product potential models were developed, identifying markets, retail partners, and even individual stores where the organization’s products had the highest probability of generating the efficient turns category buyers covet.
After identifying common denominators impacting sales we were able to isolate and quantify relationships between ad, promotion, and sales spending across the product portfolio. Understanding how a change in spend impacted sales in all channels armed us with the knowledge needed to direct investment where it would have the greatest positive impact on the bottom line—and thus, the 27% boost in sales.
Understanding Big Data was crucial to both recognizing the problems hamstringing this firm and coming up with and rationalizing valid solutions and that could be tested, tweaked, and refined for continuous improvement.
MindMeld Analytics has developed proprietary processes and technologies for extracting workable solutions from your data, no matter how onerous the task. We also have a solution that can query structured, unstructured, and completely disparate data sets.
If you would like to learn more about how you can use data to make better, more informed business decisions then please contact me at doug@mindmeldmarketing.com.