Why Starting a Tech Company to Serve Brick and Mortar Merchants is a Bad Idea

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Technology companies are sexy because they can create enormous upside in short order with relatively little capital. Think about it this way: if you want to build a car company, calculate all the risk in the business. You have to build or buy factories. You need to procure raw materials and handle logistics. You must train and employ people to build the machinery. You have risks of employee injury. Making product changes is expensive and slow. Customer discovery is pricey and lengthy.

Now compare that to software. You can build it on the nights or weekends while keeping a day job. Mostly anyone can do it without specialized training, and there are plenty of forums to help you do it better. It only takes 3-4 months to build an application like Facebook. And you can get product feedback relatively fast, depending on the use case.

Sometimes.

Software is great on the macro, but specific applications can fall far short of theorized benefits. This can be demoralizing for a host of participants: investors who are expecting fast returns; employees who are expecting valuable options; and founders who are expecting noticeable progress to stay motivated.

Brick and mortar software applications are almost guaranteed to be losers, by no fault of their own. The problem lies with the market.

Let’s first turn toward a wonderful diagram published by Steve Blank, a guru for startups. Steve argues there’s a pyramid of customer needs in any sales process. It might look stupidly simple – as in, I have a pulse so I understand this – but it’s the most important diagram brick and mortar technology startups should examine.

The choke point is never number one. Brick and mortar businesses have TONS of problems. They are so far behind everyone else that it’s improbable they’re problem-free. Even the most well-run company has problems.

 

Where everyone gets stuck is number 2: the customer is aware of his problems

 

Between 2000 and 2014, an estimated 17 million people were saved from the measles virus. But before global vaccinations were made available in the 1980’s, a cough and rash could spell death. It sucked, but what else were ya going to do; it was just an accepted part of life.

This is the exact thinking that permeates the majority of brick and mortar merchants. Any reasonable outsider looking at a merchant’s business could say, “Wow, that’s a serious problem,” but the merchant would dismissively reply, “What problem?”

Thus software companies attempting to sell into brick and mortar industries have hit a road block on only the second phase of the sales process. Now they must spend an inordinate amount of time educating and convincing the merchant that yes, measles is a problem, and yes, it can be cured with a vaccine that’s been around for 40 years.

Because so many merchants lack external industry experience, it’s very, very difficult for a technology startup to perform objective customer research. Many brick and mortar merchants will not know what problems they possess, or have any idea how to ameliorate them. There is sadly very little self-awareness in the entire sector.

Here’s a very simple example to hammer on this point.

You have a 10-year old daughter. Your daughter wants to sell lemonade one summer. How does she decide what to charge?

If you’re like us, you imagine a 10-year old girl sitting down and adding up the costs of her ingredients (lemonade, water, ice, cups, etc.) and time and determining a price. Then you envision her wanting a profit and adding an extra surcharge. But not too much, or nobody will buy it. Now maybe she’s charging $0.25 a cup or something.

Simple, right?

Yet 80% of restaurant have no idea what their finished menu items cost. A 10-year old girl worked through this importance for her casual, popup business while 80% of restauranteurs don’t think this is a problem. There are companies like Orderly, BlueCart, and handfuls of back office providers that provide such solutions but they’re not pervasive.

That is exactly what brick and mortar technologies companies are dealing with.

Contrast this with software in non-brick and mortar industries that follow a pretty established trend.

Some target business had problems. They would log and organize these problems. Then they would build or buy solutions. In most cases, Microsoft Excel was the way problems were recorded and analyzed. Have a lot of customer complaints? Let’s keep a log in Excel, and hire an analyst to find trends and help solve the problem.

So what SaaS startups did was pretty simple: take what was done in Excel and build a software solution that does it better, faster and cheaper.

Let’s look at where they fit according to Steve Blank’s pyramid of customer awareness.

  1. Customer has a problem? Check.
  2. Customer knows they have the problem? They’re using Excel to fix it. Check.
  3. Customer is actively looking for a solution? Well they thought Excel was the answer, but they know it could be better. Check.
  4. Customer has put together a solution? Yea, they’re using Excel. Check.
  5. Customer has or can acquire a budget? Well yea: they’ve paid for an Excel license and have employed a dedicated team of analysts to examine it. Check.

Easy.

To compound all the problems for technology companies are the sales cycles for brick and mortar merchants. Jason Lemkin, an investor who runs the site SaaStr, talks about expected sales cycles and commensurate revenue. Here’s his observations. Note: ACV = annual contract value, or twelve months of revenue.

1. Deals < $2,000 in ACV should close on average within 14 days.

2. Deals < $5,000 in ACV should close on average within 30 days.

3. Deals < $25,000 in ACV should close on average within 90 days.

4. Deals < $100,000 in ACV should close on average within 90-180 days depending on # of stakeholders and gates.

5. Deals > $100,000 in ACV will take on average 3-6 months to close. Of course, some faster, some shorter. But on average.

We noted earlier that brick and mortar merchants have a near-impossible time paying more than $100/month per location for any solution. That yields an ACV ~ $1200 per location. If we follow a linear interpolation from these numbers, the sales cycle should be about a week.

I’ll tell you from personal experience that it takes at least a month to close a sale for even the smallest of merchants. Finding the owner’s email is impossible, so you must repeatedly call until you can get someone to pass you to the owner. Then you need to set a demo meeting, which is almost never adhered to. If you’re lucky, you’ll get this done within 30 days.

The inability to reach potential customers also makes the feedback loop frustratingly long. When you’re trying to assess if a product will work, or what enhancements need to get done, you cannot rely on existing or prospective customers to provide much input. At the risk of beating a dead horse, the brick and mortar customer has little concept for what’s possible, and what problems a good solution will solve.

Forrester Research’s 2015 survey shows that only 15% of retailers have deployed in-store analytics. 15%!

I have no idea how you can even begin making business decisions without the data gathered from in-store analytics. How do you know what merchandise to stock? How to price things? How do you know what to pair together? If your marketing’s working? How to staff? What staff are actually delivering accretive revenue?

Some things will confuse me to the day I die, no doubt. But I will not die from measles. Software companies would be wise to look at merchant immunization records before getting started in brick and mortar.

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  • John Singleton

    “I have no idea how you can even begin making business decisions without
    the data gathered from in-store analytics. How do you know what
    merchandise to stock? How to price things? How do you know what to pair
    together? If your marketing’s working? How to staff? What staff are
    actually delivering accretive revenue?”

    These are all issues that are possible to be solved by an individual/organization with the education, exposure, and resources to solve them. The “average” small business owner simply doesn’t care and/or doesn’t have the intellectual/emotional capacity to solve them in an effective manner. Without a higher floor of education – I don’t think it is reasonable to assume action or (as your posted data suggests) awareness. This is amplified by the issue that you have run into – it is a hell of a task to do B&M sales at scale…so market leaders in digital store tech suffer from the same inability to educate and inform their customer that “they have a problem.”

    The data driven approach you describe will largely exist in chains/mature organizations in which thought leadership is top-down and there is intellectual/human capital to employ strategies and measure their performance.

    • JT

      It may surprise you to learn that ZERO public restaurant companies use machine learning for inventory and labor forecasting. They are decades behind in every possible measure. I have a very objective post coming out that should make the IRR at any PE group shoot through the roof.