Footfall Data & Analytics

Same-store sales or comp sales is misleading

Operational maangement
Tony Loxton

Written by Tony Loxton
Apr 15

“I focus on same-store sales because if my comps is up, we are growing and business is good”.

The Head of Retail at a large fashion retailer said this to me during a recent meeting. Now, I definitely agree that same-store-sales is important, but I felt it was my duty to explain to this retail executive that it can also be a hugely misleading metric.

‘Same-store-sales’ is a measure of retail performance. It can also be referred to as ‘comparable store sales’ or ‘comp sales’. It simply measures the sales of a retail store, year-on-year, for the same period. For example, how did January sales this year, compare with January sales last year, for the same store. If sales were up by 10%, this is seen as a good result.

When looking at the overall performance of a retail business, same-store-sales does two very important things: it eliminates seasonality and accounts for any incremental new sales generated by opening new stores. It allows retailers to assess how well their existing locations are performing, individually and in comparison to new locations (those opened in the last 12 months). A retail business can easily grow by adding more stores, yet it is important to ensure that growth also happens in existing stores.

What same-store-sales doesn’t tell you

As retail store performance is impacted by many variables, simply eliminating seasonality and new stores to garner performance isn’t enough. Almost nothing is the same year-on-year, making same-stores-sales a deceptive metric. Operating a retail business is just not that simple.

Last year, was your competitive landscape the same? Were your staff the same? Did you offer the same product mix, at the same prices? Were your advertising campaigns the same? Were the weather and economic conditions the same?

Same-store-sales is a good performance metric, but it tells us nothing about true opportunity or what has driven performance. This is where traffic and in-store sales conversion data comes in. By combining same-store-sales analysis with traffic and sales conversion metrics, you dramatically change the way you interpret the data.

June comp sales up by 15% = a great result?

Let’s take a look at the numbers for June:

June Last Year This Year % Change
Sales $823,188 $946,742 +15%
Transactions 2,172 2,498 +15%
Avg. Transaction Value $379 $379 0%

Your top performing store was up 15% on a comp sales basis. Average transaction value and gross margins remained unchanged from a year ago.

Comp sales up is 15%, presumably this is a great result?

How did the conversation go around the boardroom table?

June was a great month! Comp sales is up by 15%!

Transactions were up by 15%. Obviously, store traffic must have been up 15%. That’s what drove the 15% comp sales increase.

Well done to the marketing team, your efforts resulted in a 15% increase in store traffic!

Now, let’s add traffic and sales conversion data to the conversation.

June Last Year This Year % Change
Store Traffic 8,688 10,860 +25%
Conversion Rate 25% 23% -12.5%
Sales $823,188 $946,742 +15%
Transactions 2,172 2,498 +15%
Avg. Transaction Value $379 $379 0%

This is where things get much more interesting. Store traffic in June was actually up 25% from the same month last year, not the 15% that was suggested around the boardroom table. Customer traffic can realistically be thought of as ‘opportunity size’. This means that the sales opportunity increased by 25%. This is significant! Now you have to ask: if sales opportunity was up 25%, why were sales only up by 15%?The answer is conversion rate. The above table shows that conversion rate for the period was actually down by 12.5%, from 25% to 23%. As is often the case when traffic increases, conversion rate has decreased. Driving more visitors into your store is a great thing, but only if you manage to convert them into paying customers.

So, June’s result isn’t as great as we thought.

On the surface, a 15% increase in same-store-sales seems like a great result. When you add the context of traffic and conversion data, you can see the store performed poorly in June. Had the store performed well, then comp sales should have also increased by 25%.

So, instead of congratulating marketing for driving a 15% lift in traffic, they should be congratulated for a 25% increase. Knowing that the conversion rate decreased in June, the focus should be to review store operations and ensure every ounce of sales opportunity is extracted in the future. It is impossible to know the true performance of the store, without the context of traffic and conversion data.

July comp sales down by 10% = a bad result?

Now, let’s look at July for the same store.

July Last Year This Year % Change
Sales $899,367 $809,430 -10%
Transactions 2,373 2,136 -10%
Avg. Transaction Value $379 $379 0%

Comp sales is down 10%, while the average transaction value and gross margins remain unchanged from a year ago. Comp sales is down 10%, presumably this is a bad result?

How did the conversation go around the boardroom table?

July was a poor month!

Comp sales is down by 10%! This needs investigating. Obviously store traffic was down by 10% and this is what drove store comp sales down.

The marketing team needs to review their activity as this was an extremely unsatisfactory month.

These are common conversations for most retailers. With the available data above, the assumption is that traffic is driving the transaction volume and sales results. Consequently, the marketing team is often in the hot seat when it comes to poor performance, as there is the assumption their marketing efforts have not yielded enough customer traffic.

Now, let’s add traffic and conversion data to the conversation.

July Last Year This Year % Change
Store Traffic 10,786 8,628 -20%
Conversion Rate 22% 24.7% +12.3%
Sales $899,367 $809,430 -10%
Transactions 2,373 2,136 -10%
Avg. Transaction Value $379 $379 0%

Again, this is where the conversation gets much more interesting. The table demonstrates that store traffic was down by 20%, however conversion rate increased by 12.3%, from 22% to 24.7%. While a 10% decrease in same-store-sales is bad, the situation could have been much worse had the conversion rate not increased for the period, as same-store-sales would have fallen by a huge 20%.

So, July wasn’t as bad as we thought.

On one hand, July was much worse than originally thought, as customer traffic and sales opportunity dropped by a significant 20%. On the other hand, the store actually performed better against a shrinking opportunity. Marketing strategy needs to be urgently investigated, as store traffic was down by 20% for the month, not the 10% that was first thought.

Traffic and conversion data provides critical context

The examples given above are real. This retail customer commenced working with Blix in May and quickly discovered the value of having traffic and conversion data when reviewing overall performance. The business had been using same-store-sales data for years and were clearly making some incorrect decisions as a result.

Without the context of store traffic counts and sales conversion data, analysing store performance using same-store-sales is incomplete, and potentially misleading. Traffic and conversion data enables you to understand the true performance of your stores.

Want to see the power of this data in action?

The Blix team will happily show you the power of this data in live demo. Get in touch today.

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