## August 20, 2013

### The Impact Of Comp Store Sales Calculations

Many retailers now post comp store sales numbers with the inclusion of e-commerce.

Omnichannel experts celebrate this as a step in the full digitization of a retail brand, silos being torn down in the hopes of serving a modern customer.

Conversely, a lot of bad data is hidden in this style of sales reporting.  For example:
• 2012 Retail Comp Stores = \$1,000,000.
• 2012 Online Total = \$200,000.
• 2012 Blended Comp = \$1,200,000.
• 2013 Retail Comp Stores = \$950,000.
• 2013 Online Total = \$280,000.
• 2013 Blended Comp = \$1,230,000.
• Reported Comp Store Sales Metric = (\$1,230,000 / \$1,200,000) - 1 = +2.5%.
Do you see what was hidden?

Retail comps are actually -5%.  Online demand is actually +40%.  The blended average is a +2.5% comp, reported to the financial community.

Here's the thing, folks.  Let's look out ten years.  Say that retail comps erode at a -2% rate each year, for the next ten years ... and say that retail fixed costs increase at a 3% rate, each year, for the next ten years.

At that point, you have a rift in the retail profit and loss statement.

This is what the CFO is going to see. Regardless of all the attribution wizardry that folks will dream up, the CFO is going to look at a black-and-white report, and come to the conclusion that stores are in the process of dying.

And it won't be hard to disagree with the CFO - the stores will be somewhat empty, right? In the example above, there's going to be 20% fewer people in the store.

This will create two problems.
1. A desire to close under-performing stores, because of the profit illustrated in the table above.
2. The closed store will cause the website and mobile presence to under perform due to a lack of traffic ... former retail customers stop window shopping on the website (many of us observe this when a store closes). This will cause the website/mobile presence to perform differently, causing online analytics experts to conclude that things like large orange buttons are no longer drawing traffic (when in reality, traffic disappeared because the store closed), causing creative changes to the website that further impact traffic and, worse, conversion. Maybe worse, traffic via mobile will drop, because the store is closed, so the experts will say that the brand is doing "omnichannel" wrong, causing a cascading set of problems.
I want for you to take a few moments, right now, and think about the consequences of the omnichannel magic you're being sold. Increasingly, the website experience is subsidizing declining store sales. At some point, website growth will slow/stop (after it finishes cannibalizes other demand sources and mobile starts cannibalizing e-commerce).

If you were CEO/CFO, would you keep a store open that is probably generating sales across all channels, but has 60% of the foot traffic that it had back in 2003?

The CMO is going to, as folks say, have some 'splainin' to do. It will be necessary to teach that somehow, all of this stuff fits together and yields the same amount of sales that have always been generated. And then the CFO will ask why she has to pay more for all of these channels that ultimately yield the same amount of sales!

CMOs and CFOs are always working together to kill old-school marketing channels, then noticing that sales don't decrease. Regardless of attribution methodology, stores are going to be under severe pressure, due to increasing fixed costs. Retailers with high debt loads will be caught in a trap.

This omnichannel thing is going to get interesting, don't you think? More screens, more problems!

1. I agree. So... any good examples of how online efforts drive brick 'n mortar foot traffic (and hopefully, sales)?

2. A couple of things - I can't use specific client examples, but I can refer you to what we learned at Nordstrom in 2007 ... for our good customers, we knew they visited on-site three times a month, in-store two times a month, and purchased one time a month, with 85% happening in-store.

I will say this, most of my retail clients know that "x%" of all searches result in an in-store purchase, they know that "y%" of all email responses happen in-store, and they know that "z%" of all catalog responses happen in-store. Many of my retail clients have a report that tells them how much of their retail business is driven by various marketing activities.

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