Data Matters

After spending just over four years teaching “Applied Quantitative Methods” to undergraduate business students, I was burnt out trying to convince them that data analysis was an important aspect of business.  So I left my ivory tower and hung out my shingle as a consultant.

I started meeting with small business owners who were hoping I could help them with their business issues. It often went a little like this:

Client: My sales have been declining for the past year and I’m just not sure what’s going on. I don’t think my advertising is doing any good.

Me: Do you ask your clients where they hear about you?

Client: I don’t have the time or a budget for surveys.

Me: Here, let me suggest this method.  When people come into the store, have the salesclerk say “Can I ask if you’ve been to our store before?  Where did you hear about us?”  Then have them put a tick mark on this worksheet:

         Radio ad:  |||

         TV ad:  |

         Newspaper ad: ||||

         Repeat Customer:  |||| ||

         Recommended by a friend: |||| ||||

 Me:  Each day or shift, you can input that information into a spreadsheet to get a better handle on what’s working

(And yes, I recognize that I am dating myself with this particular list of marketing choices.)

Client:  Wow!  That was amazing and worth every penny you paid me! 

(Okay it might not have ended quite like that)

And here’s another common scenario I ran into – and still do:

Client: My sales volume has been going up lately, but there never seems to be much money left at the end of the month.  Maybe I need to change my prices?  What do you think?

Me: Which product/service that you sell is the most profitable?  And which is the least profitable?

Client: You can track profits by product?

Now these are relatively simplified examples, and not every business owner struggles with this sort of data collection (or lack thereof) issue.  

And, to be fair, small businesses just don’t have all that much data.  For example, small local retail stores in the United States, like that first client, average 13 transactions per day, and $961 in sales revenue per day.

Let’s compare that to mega-businesses like Amazon or McDonalds. 

Did you know, for instance, that Amazon brings in revenue of just over $17 million PER HOUR

Or that McDonalds sells more than 75 hamburgers every SECOND?

Those data volumes definitely require more than a tick-mark worksheet to drive their marketing plans!  How do they do it? 

Well, one solution to the massive data-driven decision-making dilemma for big business is the use of data scientists.  As a matter of fact, McDonalds is currently hiring a team of data scientists to “monitor and analyze performance of the AI Drive Thru Voice Agents.”  This team will “aggregate, curate and distill data from various hubs” to “feed actionable data” to various teams across “the greater McD ecosystem.”

The U.S. Bureau of Labor Statistics is predicting a growth rate of 28% for data scientist jobs through 2026.  These jobs have an average salary of $111,200, and require a knowledge of statistics, algorithms, data modeling and multiple programming languages.  

It seems a safe bet that most of those data scientists will be working for Fortune 500 companies rather than the family-owned machine shop or Mexican restaurant in your small town.

But that doesn’t mean that there isn’t value in collecting and analyzing data.  It just needs to be done “small business style”! 

Depending on the size of your business and your budget, here are some quick steps to head your business down the data-driven decision-making path towards success: 

  • Take advantage of existing software whenever possible

    Do you have a CRM to track your customer data? Use QuickBooks to track your financials?  Work with MailChimp to manage your email lists?  Set up Google Analytics to measure activity on your website?  Make sure that you are tracking as much data as is feasible and take the time to learn how to run regular reports that can help you visualize what’s going on in your business over time.  Any software you use will likely offer a whole host of report options and analytics to help you better understand what’s going on, along with online support to get them set up.

  • Lean on your sales or customer service team

Any employees that are in direct contact with your customers should already have a good sense of what your customers think of your business and where you could make changes. But try to be more intentional about that by having them all ask the same questions to every customer (when possible) and track the responses.  It doesn’t need to be quantitative in nature – just short and easy to track.  “Did we meet your needs with this interaction?” “Would you recommend us to a friend?” “Where did you hear about us?”  Start tracking data consistently and then decide when it’s worth digging deeper to learn more.

  • Experiment as needed but track the outcomes

Whenever you are considering a change (perhaps to pricing or your store hours), either ask customers in advance (social media is a great resource for this if you are active and have customers who follow you) – or keep track of what changes in your business when you make that change. Have sales gone down?  Are you getting more negative feedback?  Or has nothing changed?  If you track what’s happening before, during, and after a change, you’ll have the information you need to help you decide if the change was worthwhile.

  • Remember GIGO

Garbage In, Garbage Out. In other words, it’s important to make sure that whenever you are inputting data, that the data is true and valid.  Otherwise, a summary of that data is as meaningless as the data you just input.  And, it should go without saying that collecting NO data allows for NO analysis.  Even if you just track things in an Excel spreadsheet, try to start thinking of what information is valuable to you to guide your decision making, and start tracking it.

Here we are at the start of a brand-new year.  Before you get too far along in the year, spend a few minutes thinking about what information you could be collecting but you’re not.  Customer contact information?  Sales volume by day of the week?  Or by employee?  Website activity after an active marketing campaign? 

Find some tools to start collecting this information – anything from a simple paper with tick marks up to a more sophisticated CRM – and then look for trends and patterns in the data to help you better understand what’s going on in and around your business.

And don’t despair!  Even though the big businesses can hire a team of data scientists doesn’t mean they automatically have the advantage. Small businesses have all sorts of advantages themselves.  Tune in to the next blog post for more on that.

What tools are you currently using to collect data?  What data is the most useful to your small business?  Share your thoughts in the comments!




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