Marketing Mix Modeling for CPGs in international markets: A Case Study with Dr. Scholl’s

Marketing Mix Modeling for CPGs in international markets: A Case Study with Dr. Scholl’s

MEET Keary Phillips
Keary Phillips

Measurement Strategist

TAG - The Aspen Group, Allstate, Fidelity, Discover, Angie’s list

 

The Brand

Dr. Scholl's is a renowned foot care and orthopedic footwear brand with over a century of history. Founded in 1906 by podiatrist William Mathias Scholl, the company has become a global leader in foot care products and solutions. With over $600MM in international retail sales between the Dr. Scholls brand in the US and the Scholl brand internationally


 

The Challenge

The brand lacked a good sense of what media was driving in terms of retail sales and wanted to understand where the opportunities were to invest and drive efficient growth. The company was also embarking on a Performance Marketing initiative and needed to understand what measurement could look like in that context. 

The brand operates in a multi-channel retail environment that includes brick-and-mortar retailers like pharmacies and supermarkets, Amazon and its own D2C channel.


Exploratory Data Analysis

As part of the exploratory analysis, marketing measurement teams have to frame outcomes that marketing can be reasonably tasked to drive, but also contemplate certain marketing investments in the context of their business relationship with retail partners. This is particularly the case with trade and promotional investments with specific retailers.

The M-Squared team had several data sets to assess and synthesize. These datasets included media investment and delivery data across a diverse mix of channels and tactics going back 2 years. The data also included retailer-specific trade and promotional investment. The media channels evaluated included Google Search (brand and non-brand), Facebook, Retail Media Networks (RMN), Digital Display, TV+VOD, and Out of Home (OOH).


The Approach

These large and diverse datasets needed to be processed and transformed to build the Analytics plan. The analytics plan developed as part of a structured Advanced Attribution Audit was designed to address the questions inspired by the business and entailed:

  • Data Harmonization: Collection of the historical data (2 years) on units sold, retail sales, and media spend/activity which was reviewed and processed as per modeling needs.

  • Preliminary Analysis: Performing trend analysis, correlations, and a basic MMM to understand the fit of individual variables driving units sold and retail sales. Further reviewed the retail store categories and created a hypothesis to determine the number of MMMs to run.

  • Media Mix Modeling: Running 1000’s of iterations and 100’s of tranches for the different segments to come up with the best-fit models explaining the drivers of retail sales - the result of which was a 6-model structure based on retail category groupings. 

  • Triangulation: Using the MMM decomps, did a triangulation exercise to understand the impact of media, promotions, and the value they bring in driving units sold and retail sales.

The Marketing Accounting Framework (MAF) was oriented around incremental retail sales (revenue) driven by media across the retail category groupings. This was distilled into incremental ROAS (iROAS) by media channel/platform. This was a 6 P&L structure - meaning 6 different models were built - one for each of the retail categories.

Learn about Marketing Accounting Frameworks with this short course from M-Squared:


The Results

  1. Media drives incremental impact/revenue - nearly  12% of retail sales were driven by media and promotions on an incremental basis with a iROAS range of 0.2 - 2.4.

  2. Trade and promo spend had nearly  double the investment  as National Media & RMN’s but  less than half the iROAS. An opportunity to optimize trade and promo spend based on top-performing tactics.

  3. Amazon and other retailer-specific trade and promotional spend  have a halo on sales in other retail categories.

    1. National media influences  nearly all retail categories.

    2. Amazon RMN exhibits significant  cross-retailer halo  which suggests consumers are potentially  using Amazon to comparison shop.

    3. Retailer-specific promos have an impact outside the specific retailer running them. This may also be a comparison shopping situation.

Overall, the insights suggested there was growth opportunity within the existing budget based on making some investment shifts to higher-performing (based on incremental retail sales & iROAS) media tactics. There also appeared to be an opportunity to optimize spend within trade and promo spend understanding investment there is required to maintain the relationship and is something of a “cost of doing business”. Working with individual retail chains to invest in the highest performing tactics based on their incremental contribution and ROAS is a branded or presented recommended approach.


The Conclusion

The model outputs and Triangulation surfaced some interesting and actionable insights. The project also raised some additional hypotheses and questions. What might this look like across different regions/geography? Would different product segments perform differently based on media-influenced retail sales? These are questions that can be answered through testing and model iterations to contine to refine the insights and decision-making information. As the Scholl brand continues to diversify and modernize its media mix, M-Squared will continue to identify opportunities to leverage advanced attribution as a competitive advantage, make smart bets, and identify growth opportunities. This is just the first step in the beginning of a journey.