Multiplicative Decomposition from a Product Perspective
In the world of marketing analytics, customer-centricity and product-centricity represent two fundamentally different approaches to understanding and driving business success. We highlighted how important customer-centricity was in the previous blog entry
Customer-Centricity versus Product-Centricity
The customer-centric viewpoint focuses on understanding, segmenting, and analyzing customer behaviors, preferences, and lifetime value. It uses analytics to determine how to best engage and retain customers while fostering long-term relationships. We cannot overemphasize the importance of studying customer cohorts.
In contrast, product-centricity emphasizes products and their performance, using metrics like sales volume, profitability, and market share. It aligns with traditional marketing analytics approaches, where the success of individual products or portfolios takes center stage.
Why Data Limitations often Favor Product-Centric Analytics
Despite the growing recognition of customer-centric strategies, data limitations often tether analytics to a product-centric perspective. Customer-centric analytics requires granular, longitudinal customer data that may not always be accessible due to fragmented data systems, privacy regulations, or incomplete records.
Product-centric data, however, is more readily available from transactional systems, distribution logs, and sales reports, making it the default choice for many organizations.
Multiplicative Decomposition
As explained in the earlier blog, The Customer-Base Audit introduces the multiplicative decomposition methodology to customer-centricity. This provides a structured and insightful framework to break down complex sales dynamics into measurable and actionable components, offering clarity in understanding performance drivers from a customer-centric perspective.
To match this powerful approach and mimic Coca-Cola’s PITA model (see prior post for details), Middlegame has developed a multiplicative decomposition formula tailored to the retailer-vendor interaction, which encapsulates key product-centric metrics. For beverages categories like those Coke competes in, the formula is as follows:
The underlying components of Sales Revenue from product-centric data are defined as these metrics:
Items Available – The total number of items a vendor offers.
Retailer Stocking Rate – The proportion of items available that the retailer carries and are found on the shelf.
Turns per Item Stocked – Measures velocity, calculated as units sold per item stocked.
Litres per Item – The average volume (litres) per unit sold.
Price per Litre – Sales revenue divided by volume sold, reflecting the value (dollars, euros, pesos, rupees, etc.) per litre.
This formula offers a robust framework for identifying areas where vendors or retailers can optimize performance. For example, improving stocking rates may unlock new distribution opportunities, while enhancing turns per item could highlight operational inefficiencies in inventory or demand generation.
Generating Insights
Our partners at NielsenIQ track sales revenue by EAN (similar to UPC in the US) on a weekly basis for Ireland as well as many other markets across the globe. Below are the recent sales results of four different alcoholic beverage categories in Irish Off-License Retailers. We are comparing the current week versus the same week in the previous year:
The product-centric multiplicative decomposition provides far more insights than simply observing that sales for ALES are up while STOUT, CIDER, and LAGER are down. The formula allows us to understand that the ALE result is really 107% = 88% × 119% × 97% × 96% × 110%. By understanding this formula, we can quickly explain the source of the +7% change as well as the differences for the other categories:
The sum of the bars (both negative and positive) will equal the net change, e.g., all the bars for ALE will add to +7% aligned with the data in the table above. ALE demonstrates the most volatile outcome with significant changes in Items Available and the subsequent Retailer Stocking Rate. LAGER is the most concerning from a shopper response perspective with a significant decline in Turns per Item Stocked.
Unlocking Brand and Portfolio Opportunities
This analytical approach helps uncover the true underlying opportunities for brands or portfolios. By dissecting each component of the formula, brands can pinpoint specific actions to drive sustainable growth, i.e., introducing larger pack sizes, refining pricing strategies, or improving assortment management with retailers.
While customer-centricity remains the gold standard in marketing analytics, the structured insights of product-centric frameworks like Middlegame’s decomposition formula provide essential tools to navigate data limitations and propel success in today’s competitive landscape.
Middlegame is the only ROMI consultancy of its kind that offers a holistic view of the implications of resource allocation and investment in the marketplace. Our approach to scenario-planning differs from other marketing analytics providers by addressing the anticipated outcome for every SKU (your portfolio and your competitors) in every channel. Like the pieces in chess, each stakeholder can now evaluate the trade-offs of potential choices and collectively apply them to create win-win results.
Contact us at middlegame.com