When A Store Closes

If you really want to see the (complete lack of) power in the omnichannel business model, take a look at what happens in a market where you decide to close a store.

The secrets to your business happen in those markets.

Here's what you typically observe within the market:

• 2012 Retail At Store = $1.00 Million.
• 2012 Retail Via Other Stores = $0.40 Million.
• 2012 E-Commerce = $0.20 Million.

• 2013 Retail At Store Closed = $0.50 Million (closed mid-year).
• 2013 Retail Via Other Stores = $0.50 Million.
• 2013 E-Commerce = $0.20 Million.

• 2014 Retail At Store Closed = $0.00 Million.
• 2014 Retail Via Other Stores = $0.60 Million.
• 2014 E-Commerce = $0.25 Million.

Let's compare 2012 to 2014.

• 2012 Market Demand = $1.60 Million.
• 2014 Market Demand = $0.85 Million.

We lose $0.75 million. The closed store generated $1.00 million.

In the omnichannel future presented to us by the experts, customers are shopping everywhere, using all devices and spending a fortune.

Then you close a store, and 75% of the demand from that store simply disappears. Gone.

If omnichannel had any power whatsoever, then the demand would still be captured, right? The customer wouldn't quit shopping, the customer would move to another store, or would transition purchases online.

But that's not what happens.

That's almost never what happens.

When a store closes, one of two things usually happen.

1. 75%ish of the sales disappear, with the remaining demand recaptured among existing stores or e-commerce.
2. In a multi-store market, 50%ish of the sales disappear, with the vast majority being recaptured by existing stores, and a minority of demand flowing back into e-commerce.

Why pay attention to this trend?

As retail demand leaks out into e-commerce (because retailers will work hard to become "more digital", and will continue to siphon demand out of the in-store experience into e-commerce), individual stores will look unprofitable. This will cause CFOs to demand that unprofitable stores be closed. Then, after unprofitable stores are closed, demand will not flow back out into other channels, growth will stall, and all sorts of chaos ensues.

Run the query for yourself - look at what happens to e-commerce demand in markets where you close stores. This is the future that omnichannel is going to give us, if it continues down the current path.

You Get What You Pay For

This is a frequent outcome in e-commerce. I run a principal components analysis to segment twelve-month buyers into nine groups.

The most valuable customers are on the far right. What do you observe, when you look at the three segments with the best buying behavior in the past year?

Ok, I'll walk you through the three segments.

Bottom Right: Loyal customers, with prior purchasing behavior. They tend to use the company blog, email marketing, and tend to visit the site via SEO.

Middle Right: Loyal customers, with prior purchasing behavior. They are similar to customers in the bottom right segment, but they are much more active online - influenced by retargeting, affiliates (they want their discounts), paid/branded search (they know the company well), and they are socially active via text-based social channels (i.e. Twitter / Facebook).

Upper Right: Highly productive customers, mostly first-time buyers (newly acquired). These customers "do everything". They are literally scavenging the internet before purchasing ... they digest corporate content (blog, email), they are online carnivores as illustrated by retargeting, search, and display attributes. They thoroughly consume social channels, including Pinterest / Tumblr / Instagram (image social channels).

Marketers adore customers in the Upper Right segment. This segment is "proof that online marketing works". Well, of course online marketing works!

CFOs adore customers in the Lower Right segment. How much do you have to pay to get these customers to purchase? Nothing. NOTHING!! Your blog, email, and SEO. I know, I know, there are fixed costs associated with the disciplines, but those fixed costs are close to zero as a percentage of net sales. Marketing expenses are often 10% to 40% of total net sales ... think about that one.

Vendors demand that you go after the Upper Right segment - and for good reason - vendors generate profit when you attract that type of customer.

Every company needs to have a huge chunk of customers in the Lower Right segment - you generate profit when you attract that type of customer.

I know, vendors are going to demand that you "do both". So go ahead and do both.

But every dollar you save in marketing expense is a dollar that can be reinvested elsewhere. By cultivating customers who do not purchase because of online marketing, you have more money to spend growing in other ways - or to pay staff or owners or shareholders.

You get what you pay for.

P.S.: If you'd like me to run this analysis for you, send me an email message (kevinh@minethatdata.com).

Attribution Credit

This quote comes up in various forms, all the time.

• "63% of our orders happen after a customer sees a banner ad or retargeting effort. It's clear that this stuff works."

Alright.

You go in and analyze data, and you see the following trends:

• Prior to retargeting/banners = $3,000,000 a month average.
• After retargeting/banner program is initiated = $3,080,000.

Now, you can use control groups to measure your retargeting/banner efforts, but that's no fun when you demonstrate that you didn't generate much volume ... it's better to hand the problem off to an attribution vendor who gives retargeting/banners credit for $400,000 in monthly volume.

In theory, we're trying to prove that our investments work.

Sometimes, I wonder if we're trying to prove that we're valuable?

We are valuable.

I know, it's difficult, because you have a merchant who is under tremendous pressure, and is afraid s/he will be fired.

It's difficult, because the creative team never has quantifiable metrics to prove that their work matters, so they want to make sure that marketing brings them the right traffic - they didn't screw up, marketing screwed up.

It's difficult, because IT strongly believes that a trained monkey could run marketing. I've been in the meetings.

It's difficult, because operations browsed an article in a trade journal about best practices, and wants to know why your department won't employ best practices? I mean, they're "best", right? Don't you want to be the best? Are you stupid? And operations paid for a Woodside Research report, and the report suggests marketing is stupid, so marketers are stupid.

It's difficult, because half the Executive Team is going to get fired if sales don't improve, and they cannot change the merchandise assortment for at least another half-year ... they need marketing to act, NOW!

All that pressure trickles down to marketing.

Is it any wonder marketing wants to prove that they touched every single order?

And the vendors need to prove that everything marketing did touched every single order, because that's how vendors get paid. It's hard to blame anybody.

Too often, attribution credit is a function of pressure, and is not focused on genuine measurement of return on investment. How could it be?

Try to remain unbiased. I know, it's hard to do, but it is necessary.

Retail Inflection Point

If you want to know how important your store is to your "omnichannel mix", perform this very simple analysis:

• Segment Annual Demand (Retail, Website+Phone+Mobile) by Store Distance.
• Calculate the Percentage of Demand Within Store Distance Band Attributed to Stores.

Here's an example:

• 0 to 5 Miles = 77% Retail.
• 6 to 10 Miles = 62% Retail.
• 11 to 15 Miles = 51% Retail.
• 16 to 25 Miles = 46% Retail.
• 26 to 50 Miles = 40% Retail.
• 51 to 75 Miles = 30% Retail.
• 76 to 100 Miles = 25% Retail.
• 101 to 150 Miles = 22% Retail.
• 151+ Miles = 20% Retail.

Here, the inflection point is at 16-25 miles from a store. That's where the customer switches from retail purchase preference to e-commerce purchase preference. 

There are three important pieces to this analysis.

1. The retail businesses with the best long-term potential generate 50% or more demand in retail as far out as 100 miles from a store.
2. The best retail businesses maintain a constant ratio over time ... meaning that if 40% of sales come from retail at 26-50 miles from a store, the ratio generally stays near 40% over a 2-3 year period of time. If the ratio skews wildly toward retail, or toward e-commerce, then one of the channels is having a problem.
3. The best retail businesses generate 90% or more of sales in-store for customers within five miles of a store. If a customer lives 2 miles from a store and chooses not to visit the store, how compelling can the in-store experience be?

What is your retail inflection point?

Macy's Allegedly Drives $6 In-Store Demand Per $1 Of Search Spend

Yup, click here folks.

We learned this at Nordstrom, way back in 2004-2005 (hint - that's what happens when you have a good database and staff dedicated to measuring store/web dynamics) ... technically, we learned that we drove at least as much volume in-store with search as we drove online. Once you learn that, you invest your money differently. In fact, you can kill a catalog division and not lose sales once you know a fact like that.

Now, this is assuming that the article reflects reality. There are MANY reason to think that the article is biased.

• The theme of the article shifts from Macy's to a survey to quotes about Google, an organization who significantly benefits from increased search spend.
• The basis for the findings in the article is a survey of 6,000 individuals. That's nonsense. Both Google and Macy's have millions/billions of individuals to measure reality from. Why ruin that to talk about how 6,000 individuals behave?
• There are numerous research organizations that are part of the research - stuck in between Macy's and Google.
• Trade journalists need to make money too - think talking about Macy's and Google attracts eyeballs?

In other words, the analysis is likely to be directionally accurate, and thoroughly biased all at the same time.

The article reflects everything that is right about analyzing data and making good decisions, and everything that is wrong about power, eyeballs, attention, and monetizing outcomes.

How Do I Know I Have A Lapsed Buyer / Reactivation Problem?

Here's one of two queries I like to run to identify customer reactivation / lapsed buyer problems.

Step 1 = Identify all customers who purchased in September 2014.

Step 2 = For all customers who purchased in September 2014, count the number who are not first-time buyers, and who had not purchased in the twelve months from September 2013 - August 2014. This is the number of customers who are "reactivated".

Step 3 = Re-run this query, shifting all dates back exactly one month. Count the number of reactivated buyers.

Step 4 = After running this query, going back in time several years, calculate the difference in the number of reactivated customers, year-over-year. For instance, if there were 900 reactivated customers in September 2014, and there were 1,000 reactivated customers in September 2013, then you have (900 / 1,000) - 1 = -10% change in reactivated buyers.

The image above is what I see, repeated over and over again for catalogers, and for retailers. In the past two years, the sky is falling. In retail, the more we encourage customers to sit at home and use devices, the more we're going to see this outcome. In cataloging, the more we ignore customers under the age of 50 by offering merchandise that appeals to customers over the age of 50, the more we're going to see this problem.

First, run the queries and quantify if you have a problem. Or contact me (kevinh@minethatdata.com ... pricing details are found by clicking here) and I'll run this for you. This query yields results, folks, helping explain why lapsed buyers and new buyers are the Story of Fall 2014.

Grumbling About Amazon

In Madison, about 80,000 fans pack the stadium (students pack it a bit after the 11:00am starting time, but whatever), paying a lot of money to attend a game that is being freely televised across the country.

Oh, I know, you're going to nitpick this, telling me it is only available on certain cable systems or satellite providers. Fine, point taken.

Have you ever looked at what it costs to purchase football tickets? Click here, it's an expensive proposition. You have to pay a "contribution fee" that is several hundred dollars, just to earn the right to purchase season tickets. That's like paying Gap $49 for the right to purchase chinos.

Then you're looking at $420 per seat, for seven home games.

What if you want to buy season tickets for you, the spouse, and for little Timmy and Gemma?

• $420 x 4 = $1,680.
• A $200 contribution fee, which allows you to spend the $1,680 in the first place.
• Total = $1,880.

Or you can watch the games, at home, for free.

For free.

So why are at least 70,000 people (80,000 for conference games) filling the stadium seven times each fall? Fans could put this money to better use elsewhere, right?

Sports teams are able to get you to come to their retail channel (the stadium) to pay a lot of money for something you can do at home, for free. Obviously, the entertainment experience provides an emotional benefit greater than the cost required to obtain the emotional benefit.

Back to Amazon.

Amazon is like watching a football game on TV. It's easy. Given the choice between the customer having an easy experience on your website (or in your store), or an easy experience on Amazon, the customer will choose Amazon. Think especially about your retail store. Is the customer amazed, dazzled, sort of like when the customer walks into Cabelas or an Apple store? Or does the customer have eleven different, boring choices to buy chinos?

Be honest ... when is the last time you got an energy rush buying a t-shirt in a retail store? Or online?

So grumble about Amazon all you want. Have at it. But think carefully about the source of your grumbling. Amazon does "boring" better than almost anybody else. They've cornered the market on boring. You're not going to compete with them, they do boring better than you. 

Either you sell something Amazon doesn't sell, or you give the customer an adrenaline rush, much in the same way sports teams do. The latter is terribly hard work, it's expensive, and it has a much lower probability of success. But ask yourself what the probability of success is competing on boring?