CASE STUDY
AI Price Pack Architecture Nets A Brewing Company Projected 8% Increase in Market Share
More acceptance and more sales garnered by smart SKU recommendations.
Our client, a brewer of German-style beers, wanted to establish itself as a market leader by driving volume growth. In particular, it wanted to focus on two brands currently in the market and determine the best price-and-size combination for each brand. It also wanted to understand how introducing a third SKU would impact their market share.
To provide the needed insight, we used AI-enhanced data analysis to:
Determine the probable volume and market share for different price variations
Identify which price point would improve market share, optimize volume, and drive revenue for each brand
Evaluating More than Just Price
Our analytics team decided to use a discrete choice-based conjoint study to meet the above objectives. They started with an online quantitative search, then moved into a deeper analysis that focused on developing optimized brand strategies. Calculations showed that if the client followed the recommended scenario, they could expect to realize a projected 8% increase in market share for their portfolio.
During the study, a new SKU (with its own new price pack) was explored and its possible brand cannibalization was also analyzed. The introduction of this SKU was well supported; after its launch, it showed an even greater increase in market share than predicted.
Capturing Customer Reaction with AI
During the conjoint study, we analyzed consumer reactions, survey results, and derived customer preferences to answer questions like “How will consumers respond to a change in price? Brand? SKU? What additional factors (such as distribution and marketing campaigns) will impact volume changes?” To get a real feel for the possibilities, we did trade-off exercises in a simulated market environment and calibrated the results of our study to reflect actual market scenarios.
Armed with this insight, the client was able to understand much more than just the impact of price changes. We worked with them to develop an actionable strategy for brands and their SKUs that included category dynamics, top competitors’ actions, and price index evaluation. We also analyzed historical data to see the impact previous price change had on volume. Finally, we located opportunities to optimize margins by playing on price.
AI Recommendations Boost Price Pack Architecture
AI provides a much easier and more efficient way to view a problem – such as price pack architecture – from multiple angles. By allowing our client to get a realistic view of customers’ reaction to price changes and a new SKU, it paved the way for them to realize their goal: increasing market share and positioning their company as a market leader.
