The eSite Analytics Blog

Market Cannibalization: Why Your Calculations Are Off

(Be sure to scroll to the bottom of this post, where you’ll find a link to request a personalized demo so you can see how your own cannibalization calculations could be off.)

What method do you use when you need to determine how a new site will impact your existing store network? Standard gravity modeling is probably the answer.

The Limitations Of Standard Gravity Models

Long used as the standard for calculating retail cannibalization, gravity models attempt to reflect the habits and preferences of customers using subjective standards, retail counts, co-tenancy and historical data. They also treat distance uniformly (drive times, straight miles or drive miles).

All this leads to results that are “directional” at best and virtually impossible to test.

In the real world, people rarely drive straight from home to your store and back. So while generic drive times and mile counts do have value, the insights they offer are more guesswork than real intelligence.

Your cannibalization estimates could be off by 38+%

Trip2Trade retail cannibalization case study


eSite’s Trip2Trade tool completely changes how retail cannibalization is calculated, using real trip data from TomTom.

Let’s say your company is considering a new location — a great opportunity in a thriving shopping center with excellent cotenants and very high sales potential.

It’s also seven miles from an existing store.

Based on traditional gravity models for measuring transfer, you’d assume each customer will shift to the store closest to his or her home, weighted by some subjective criteria. That method would show damaging levels of cannibalization because so many current shoppers live west of your existing store.

That calculation may not be correct, and can’t be tested.

Usually, customers choose locations that are convenient to where they are when they need or want to shop. Not necessarily where they sleep at night.

By examining actual (anonymized) trip data, the decision-makers at your company would be able to see that current customers don’t typically cross the river, which insulates the two markets.

Instead of a whopping 40% cannibalization estimate, it would come down to just 2%. The two stores can easily co-exist, opening the doors for millions in potential revenue your team might otherwise miss out on.

Get this trip data from eSite now.

Six months ago you couldn’t get this kind of data. There wasn’t a single tool powered with real-world driving data.

Then eSite found a way to more accurately calculate cannibalization with data collected from GPS devices. The result is Trip2Trade, the only site selection tool powered with data from navigation leader TomTom.

Trip2Trade puts recent data on actual trips at your fingertips to get more accurate estimates…before your real estate team invests a single dollar or hour in researching a site.

How Trip2Trade Works

With Trip2Trade, you can identify specific areas where a new store would pose a definite threat to an existing store—and the degree to which it would impact that store.

The tool can also be used to run cannibalization studies and create buffers around existing stores. You can even look at a 40-mile radius and drill down to see the impact a new store would have at every mile marker within that scope.

See Trip2Trade in action

If you’d like to test drive eSite’s newest tool, you should schedule a Trip2Trade trial here. (Or, if you’re going to RECon 2014, an in-person demo.)

An eSite analyst will show you how TomTom data impacts cannibalization estimates, trade areas and more.

eSite AnalyticsMarket Cannibalization: Why Your Calculations Are Off

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