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Become a Big Fan of Data & Analysis

6/14/2016

My last article gave perspective on the importance for you as a convenience store owner to make strategic and fact-based decisions that focus on your unique shopper. It starts by creating some overall strategies and implementing category management in your store(s). This doesn’t have to be very time consuming or complex, but it sets the foundation for a more strategic approach for the future. Once you’ve defined your strategies, you can start to analyze your data.

Before you learn how to analyze and interpret data, you need to understand the key data sources that you may have access to as a c-store owner. Some of the data is available in your store, but much of it needs to be provided by your suppliers.

I’m hoping that if you are not already a big fan of data and analysis, I’ll make you a fan. Once you develop a basic understanding of how your data can help you make better decisions for your store, you will embrace it wholeheartedly! By moving to a more data-based approach to decision-making, you should see improvements in both your sales and profit.

Your Key Category Management Data Sources

Before you can start to analyze your data, you need to consider the key data sources available to you and understand the following:

  • How is each type of data derived?
  • When should I use this data to make strategic decisions for my store?
  • How can I access this data?

The three most common category management data sources available to you as a c-store owner are: retail point-of-sale data, retail measurement data and consumer panel data.

Retail point-of-sale data is your own internal data and it contains a wealth of information. In fact, it is the most powerful data source to use in your category management analysis. The level of depth and types of reports are driven by your frontend and backroom systems. Scanned sales data allows for powerful, flexible analysis, including in-depth profit, promotion and pricing analysis.

Retail measurement data gives you a total market perspective. It is derived from scanned sales data across many retailers, which comes from a third-party resource like Nielsen, IRI or market shipment information from your suppliers. This data helps you understand how your store’s results compare to the rest of the market.

Consumer panel data gives you a consumer/shopper perspective. Remember, they “own the wallet” that drives sales in your store. Panel data is derived from a panel of consumers who scan their purchases, which get fed into a massive panel database. This consumer data provides great insights into the shopper and their purchase behaviors.

As a c-store retailer, you should try to access these data sources to better understand what’s going on in your store, in your market (to compare your results to) and with your important shopper.  Challenge your suppliers and find out what data sources they are using, ask for more information about the shopper, and find out what’s going on in the market vs. what’s going on in your store. 

Time to Analyze Your Category Data

Once you have an understanding of the data sources and what you have access to, you can complete a category assessment. Analyzing your data will allow you to better understand your business in a category, including comparing results vs. the market, interpreting the data and identifying category opportunities and weaknesses for your store(s).

When assessing a category, have your scanned sales data available at a category and subcategory level so that you can get deeper insights for your business (refer to the above example of a confectionery category assessment).

By looking at your business this way, you can draw great insights about what’s going on in your various categories. For example, here are some insights I can draw about the confectionery category based on the simple assessment provided:

  • Percent Change (Calculation: Dollar sales this year divided by dollar sales last year): My category is up 8.6 percent in dollar sales, driven by peg candy, non-chocolate bars, and candy rolls and mints. Sales are declining in gum and change makers vs. last year.
  • Absolute Sales Dollars (Calculation: Dollar sales this year minus dollar sales last year): Confection sales are up $2,117, driven primarily by growth in peg candy, non-chocolate bars, and chocolate bars.
  • Category Dollar Share (Calculation: Dollar sales by subcategory divided by category dollar sales): Chocolate bars and peg candy represent almost 70 percent of total sales in confection.

By identifying the biggest areas of growth in the category, plus understanding more about the subcategories, I can now determine my goals and objectives for each of the subcategories to help me achieve my category target. Usually, the categories that are growing the most and/or that are the most important subcategories in confection are given the most support.

Your Next Steps

Now, pick a category you would like to better understand. Determine the data sources that you can access for this category. Pull your point-of-sale data for your store for the chosen category and try to use similar measures to my confectionery category example. See what data is available from your suppliers for this category. 

Then, assess this category business. What are the areas of growth? What are the areas of decline? Which are the largest subcategories that should be given more attention? By understanding your category from this data-based perspective, you’ll be able to create some goals and objectives by subcategory and then start to analyze the tactics using a similar approach.

Look for my next article on how to make strategic, fact-based decisions on what items to carry in your store(s). These choices directly affect how much money you take to the bank each day.

Editor’s note: The opinions expressed in this column are the author’s and do not necessarily reflect the views of Convenience Store News for the Single Store Owner. 

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