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A Guide to Optimizing Your Competitor Shop List

By January 22, 2021 February 10th, 2021 No Comments
Engage3: A Guide to Optimizing Your Competitor Shop List
Engage3: A Guide to Optimizing Your Competitor Shop List
Engage3: A Guide to Optimizing Your Competitor Shop List

Sub-Optimal Choices

When building an optimal Competitive Intelligence program, one of the most important decisions you will make is which competitors to include and their store locations to shop.  Many retailers sub-optimize their competitive insights by choosing a legacy list of competitors based on historical gut feel, focusing on only a handful of large national players, or not being strategic about the specific competitive locations to include.  Using store level competitive leakage data and reverse engineering of competitor price zones, there is a better way to build a Competitive Intelligence shop list that maximizes visibility into competitive strategies and ensures that your shoppers have locally relevant prices.

Choosing your Competitive Set

The average shopper visits over 2.5 different retailers per week, according to recent Nielsen research.  Insights from sources such as Nielsen Spectra data or Credit Card purchase data, which track shopper leakage, can be invaluable in helping retailers understand which competitors your shoppers are going to and identifying the top competitors for each of your stores.  However, most legacy programs we’ve seen do not use this data  to identify the right competitors to track.

For example, one major retailer didn’t have competitive data from 58% of each of their stores’ #1 competitors and 34% of their stores didn’t have data from each of their stores’ top 3 competitors.  This means that prices they are collecting are not locally relevant and are based off of competitive data for stores that shoppers are not cross-shopping.

Using the Engage3 Comp Shop Optimization engine powered by Nielsen Spectra data, we identified where their shoppers are cross-shopping and which top competitors they need to watch for each of their stores.  This information was then crunched to identify a competitor shop list that maximized their visibility into their shoppers’ rest of market spend.  By reallocating resources from shopping low value competitors, we were able to help our case-study retailer get competitive data for 79% of their stores’ #1 competitor and provide data to 94% of their stores from at least one of their top 3 competitors — all for the same budget as their legacy program.  This allowed the retailer to set prices based on relevant competitive prices from the retailers their shoppers were cross-shopping with.

One major retailer didn’t have competitive data from 58% of each of their stores’ #1 competitors and 34% of their stores didn’t have data from each of their stores’ top 3 competitors.

Selecting the Right Stores to Shop 

According to Nielsen Homescan Panel research, 92% of shopping trips are made to a retailer within 5 miles of a shopper’s home, making it critical that retailers have localized competitive data to ensure relevant pricing.  Gathering local pricing insights is complicated because of competitors’ price zoning strategies and local item pricing.

Using Engage3’s store level price tracking data, we were able to reverse engineer that one of the largest national retailers in the U.S. was using less than 50 price zones to price the majority of their products, while pricing about 600 items at the store level.  Further, we were able to assign each store to a price zone and identify their investment price zones for key products such as Private Label items.  With this information, we then reviewed the legacy program of one of their main competitors and found that over half of their stores were using competitive data from an investment store, when in reality their shoppers were most frequently shopping at a non-investment store.  By unnecessarily chasing their competitor’s investments that their shoppers were never seeing, this retailer was costing themselves 21 basis points of gross profit dollars every year.

Building the Perfect Program

By combining shopper leakage information with advanced competitor price zone and localization, reverse engineering a retailer can build the perfect Competitive Intelligence program grounded in shopper behavior:

  • Competitive data from the right competitors that your shoppers are cross-shopping
  • Locally-relevant competitive insights for each of your stores
  • Pricing strategies to outsmart your competitors’ localization and investment efforts

For a FREE Engage3 optimization of your Competitive Intelligence program that will maximize visibility while saving you money, click on the button below.

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