Analysis and Interpretation — Retail Tracking

Exhibit 28.11   Retail tracking data is three dimensional. (click to view demo).

Retail tracking data is essentially 3-dimensional — product, market and time (refer to Exhibit 28.11), and each dimension has a hierarchical structure. For instance the product dimension can be broken down to category, segment, sub-segment, manufacturer, brand, variant and item.

The following are some metrics or facts supported by the retail index:

  • Sales Volume.
  • Sales Value.
  • Year-to-date (YTD) Sales Volume and Value: The sum of sales volume/value from the beginning of year to the latest period.
  • Moving Annual Total (MAT) Sales Volume and Value: The sum of the total sales volume/value for the 12 months ending with latest period.
  • Average Price:  Sales Value ÷ Sales Volume.
  • Retailer Purchases Volume and Value.
  • Forward Stock: Stock in the store’s selling area which can easily be accessed by customers. Includes stock placed on shelf, on special display, on the shop floor space, inside chillers, freezers, cabinets and so on.
  • Total Stock: Stock in the store’s selling area plus stock in the store room (aka backroom or stock room).
  • Stock Cover (Stock Cover Days): Number of days that stock would last, assuming sales continue at the same rate.
    Example: If stock is 300 units and sales is 600 units per month, then stock cover days = 300/600 = half a month.
  • Out of Stock: Percentage of stores in the universe that sold the product in the audit period but having no stock at the time stock was counted.
  • Numeric Distribution: Percentage of stores handling product. A store is considered a product handler during an audit period, if it stocked that product at any time during that period.
  • Weighted Distribution: Percentage of stores handling product weighted by product category store sales (equal to share of category sales by handlers).

Numeric and Weighted Distribution

Exhibit 28.12   What is the numeric and weighted distribution of brands X, Y and Z? (Universe is shops A, B, C and D).

Consider the example in Exhibit 28.12. Brand X is handled by shops A, B and C; its numeric distribution therefore is three out of four or 75%. Its weighted distribution is the total weight of shops A, B and C in terms of category sales, which is equal to 50% (5 + 20 + 25). Note also that the brand’s weighted distribution (50%) is the same as the trade share of shops A, B and C, which handle brand X.

Unless otherwise specified, distribution is weighted in terms of category value sales. Defined as a percentage of where money is spent on the product category, it reflects the quality of distribution.

Considering that brand X’s weighted distribution (50%) is lower than its numeric distribution (75%), one may conclude that the quality of the brand’s distribution is relatively weak. In comparison brand Z with 50% numeric and 70% weighted distribution is handled by stores that contribute more to category sales.

Occasionally categories are weighted in terms of ACV (i.e. sales value of all categories sold by store). This is advisable in case of small, new/growing categories with few brands. For such categories, ACV weighted distribution provides a better reflection of the quality of distribution.

In-Stock and Out-of-Stock Distribution

Exhibit 28.13   Stockout and loss of distribution.

In the context that a product handler may run out of stocks, what is required, is a clear distinction between in-stock distribution, out-of-stock (OOS) distribution and loss of distribution.

Consider Exhibit 28.13, which depicts a brand’s incidence of purchase and stocks over four time periods. The brand has in-stock distribution in January and February, and it has out-of-stock (OOS) distribution in March. The brand lost distribution in April because there are no sales, no purchases and no stocks — it did not exist in the store at any time during the month.

Now suppose there was some closing stock in March, and as before, no purchases in April and no stocks by end of April. In this case (Exhibit 28.13b), the status in March changes from OOS distribution to in-stock distribution.

Exhibit 28.13b   Stockout and loss of distribution.

Is this store still considered a non-distributor in April?

No, because the stocks at the end of March are opening stocks for April. These stocks would have sold during the month. So, in this scenario, the store is a handler that is experiencing stockouts for the product.

Benefits — Market Understanding

As it capture the most fundamental market information, retail tracking data is essential to formulating marketing strategies and sales plans. Its scope encompasses all of the following areas:

  • Market Structure: The information on size and growth of category, segments and brands provides an understanding of the opportunities and threats. Consumer trends such as, for instance, in convenience and health, are spotted first by the retail index.
  • Channel Performance: The size, growth and development of channels and chains, feeds into channel strategies.
  • Brand Health: Brand growth, share, distribution, price are some of the key metrics that help assess the health of a brand.
  • Competition: The index reveals the activities of competitors, as also their strengths and weaknesses.
  • Sales Evaluation: With metrics like distribution, stocks, stock cover, OOS and so on, the retail index is ideal for sales evaluation and distribution diagnostics.

Analysis and interpretation of this data, in the context of sales and distribution, is the topic of Chapter Sales and Distribution.

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