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5 Advanced Analytical Constructs for Optimizing Trade Promotion Fund Allocation in the CPG Industry

Originally published November 23, 2010

Trade promotion is a very important marketing vehicle used by consumer packaged goods (CPG) companies to stimulate demand for their categories across their channels. In many cases, trade promotion is the second largest expense after the cost of raw material and finished goods itself. By many estimates, CPG companies spend anywhere between 8-14 % of their turnover and up to 60% of their marketing budgets on stimulating demand on channels. Typical examples of trade promotion investments include:

  • Buying strategic shelf spaces that have high visibility in department stores

  • Price cuts for convenience stores to increase share of shelf for high margin products

  • Investments in in-store signage assets such as danglers

  • Gifts bundled with the products at duty free stores

  • In-store sampling at select stores for the new ice cream flavor
Advanced analytical constructs like optimization, regression, “what if” analysis, geospatial modeling and text mining can provide significant visibility into the effectiveness of these trade promotion spends. The information attained can provide insights in terms of sales uplift contributions and can help in optimizing the same in the face of many real world constraints during the fund allocation process.

Before examining how these constructs can be applied, however, it’s important to understand the various business scenarios and unanswered questions that channel managers, brand managers, category managers and financial analysts (CFO office) need to address while evaluating promotions on which they have spent millions of dollars. Most of the questions, as seen in the examples below, probe the impact of the promotion on the overall category/product uplift and the resulting ROI achieved in addition to its effect on other products and categories.
  • Based on historical promotion data, which are the top 3 promotion vehicles that have maximized uplift and helped launch/re-launch a product?
  • If I want to increase my sales uptake in the West Coast market for my organic products, do I purchase more strategic shelf space at Walmart or do I give a 5 % price cut at Shoprite?
  • What’s the percentage uplift in sales during a seasonal period compared to a non-seasonal period?
  • Can we quantify the rate of cannibalization of private label brands on our premium flagship products as consumers become more price sensitive during tough economic conditions?
  • Did promoting a sachet package of a shampoo cannibalize a strategic SKU that is a “cash cow” for us?
In answering the questions above, CPG organizations may find the advanced analytical constructs of optimization, regression, text mining, geospatial and “what if” very useful. Each offers its own strength in helping evaluate trade promotions as outlined below.
  1. Optimization construct
    If a channel manager wants to allocate his trade promotion funds between shelf space procurement and price cuts, he needs to determine the appropriate ratio to maximize category uplift. Factors that need to be taken into account include the seasons when a promotion can be run, fund constraints for each particular promotion, channel constraints, etc. An optimization tool can be configured to discover the best possible breakdown of funds given these factors.

  2. Regression construct
    A regression construct can help pinpoint both positive and negative drivers of category uplift. A sudden spurt in private label sales or a competitive product could be a negative contributor to a strategic SKU that had been the leader in its category.  For example, let’s say a category manager has a hunch that the newly launched pink colored cold cream, which is heavily promoted on select channels using the shelf-space vehicle, is beginning to cannibalize the traditional cash cow, which is a white colored cold cream. A regression construct can be used to model the cannibalization and statistically confirm the presence of the same. It can also ascertain the impact of individual trade promotions on the sales uplift and rank the highest contributors to volume uplift.

    (Mouseover image to enlarge)

  3. Text mining construct
    Imagine a scenario where a crucial trade promotion investment decision needs to be made to promote the launch of new shampoos for Latino markets. The product/category manager wants to dive deep into the key learning themes of past promotions of similar nature by examining comments that were entered into a digital promo post-harvest application. An unstructured text mining process can be run on those comments to synthesize the top 5 themes and distill the essence of the learnings by providing a theme map, such as the one pictured below.

  4. Geospatial construct
    If one has outlet-level granularity for promotion and store data, then the information regarding store promotion metrics can be rendered on a geospatial map. This helps the channel and category manager ascertain if location and store catchment  information can explain behavior regarding promotion effectiveness.

    (Mouseover image to enlarge) 

  5. “What if” construct
    Let’s say a perfume manufacturer wants to heavily promote a particular perfume in all airport duty-free stores using varying price cuts. The effects of these price cuts can be effectively modeled using the “what if” construct, which can provide estimated incremental volume uplift to be expected from promotions/pricing scenarios planned in the upcoming season. A pricing "what if" scenario can provide clear visibility into unwarranted price concessions for selected channels/categories.
In addition to having the power of advanced analytical tools, it is important to implement three organizational best practices that influence a CPG company’s efforts to wisely allocate expensive trade promotion funds:

Set Up Trade Promotion Analytics Cell

Some of the analytical outputs are very complex for business users to draw insights from as they are more focused on running their business as opposed to reading complex outputs. Creation of a trade promotion analytics cell can catalyze the usage of uplift/promotion related insights to redirect funds. For example, a channel manager torn between price cuts and shelf space investment decisions for a shampoo product can call up the trade promotion analytics cell to discern past contributions and investment guidance from the trade promotions cell before operationalizing the promotion plan.

Collaborate to Collect More In-Store Data Points

One of the critical best practices for optimizing promotions is to intensify the information exchange and collaboration between retailers and CPG companies to collect more store data points such as POS scanner data and shelf space related data points. Organizations like the Promotion Optimization Institute (www.p-o-i.org) are involved in creating frictionless conditions for an ecosystem of retailers and CPG companies to collaborate and learn from promotions.

One example of a collaborative effort between CPG companies and retailers is the sharing of data from a retailer's store video. This video footage can provide crucial information such as how many people walked past a shelf or how many people stretched their arms to explore a product. This is valuable information that CPG companies traditionally have not had access to, but through collaboration with the retailer, the shared information can help CPG companies align shelf space investment decisions.

Institutionalize a Structured Post Harvest Process for Learning from Trade Promotions

Have a formalized "post harvest" analysis to capture learnings from a promotion (What went well? What could be improved?). For example, digitally capturing promotion learnings and making it available via an application could reduce the instances where a suboptimal trade promotion allocation decision is made.

James Joyce, the Irish novelist was very right when he said,  “A man's errors are his portals of discovery.”  

Creating a trade promotion cell to methodically learn from successful and not so successful promotions using advanced analytical tools can be a game changer. The trade promotion cell can provide promotion related insights and guidance to channel managers, category/brand managers and financial teams to help allocate their multimillion trade fund dollars wisely (instead of blindly allocating it based on gut feel or past allocation patterns). And this change could make the difference between profitable CPG firms and not so profitable CPG companies since trade promotion is the second largest component of cost and can help reduce margin leakage.

Note: The author would like to thank R.Geetha, Anil Kumar, Reshma Dash, Neha, Geetha and Pratibha for their valuable input for this article.

  • Derick JoseDerick Jose

    Derick Jose is the vice president of Advanced Analytics/Research within MindTree's Data & Analytic Solutions (DAS) Group, one of the world’s largest information management practices, which offers customers a one-stop-shop to capture, analyze, enhance, and view their business information. The DAS practice combines MindTree’s proven analytics, business intelligence, information management and research services for customers in the consumer packaged goods (CPG), retail, financial services, insurance, travel and media markets. Derick has 20 years of experience spanning consulting, advanced analytics and business intelligence solutions. He has worked extensively in the CPG, banking, telecom and retail industries. Derick can be contacted at Derick_Jose@mindtree.com.

    Editor's Note: More articles and resources are available in Derick's BeyeNETWORK Expert Channel. Be sure to visit today!

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