From the desk of Steve Brester, director of information technology
When people use the word “data,” they typically think of information found in a file on their computer, such as data found in a Microsoft Excel® file. Although that is one type of data, there are many other types of data available to you to help tell a story or help in decision making.
Use your imagination when thinking about where you might pull data from to tell a story. Let’s say you are a store owner and someone asked you to tell them what the shopping patterns are at your store. Someone with a very analytical mind might right away think of the reports available from the store’s POS system as a way to analyze data to find the best sellers and determine store shopping patterns.
Someone else might watch shoppers walk around the store, note what products they pick up and look at, and document the questions being asked. They might then combine that information with the POS data to see actual purchases and use all of that data to build a story about shopping patterns.
The tricky part is how to link all this data together to create a basis for your story. Look for commonalities between the disparate data you have collected. For instance, think about the older shoppers that come into your store and the data you’ve collected on that group. What time of the day do they come in? What department do they usually go to first? How much time do they spend reviewing a product before they either put it in their cart or put it back on the shelf? Do they tend to ask for help when shopping? Do they usually purchase a name brand or a private label? Compare this information to the data you’ve collected on your Millennial shoppers. Did you find similar patterns between the groups or differences? Either way, you can build a story on shopping patterns as well as use the information to improve the shopping experience for both groups of people. Keep yourself informed about current technology – every day there seems to be a new technology introduced that can capture data in an innovative or unique way.
Remember that social media today provides a wealth of data for you to use. Review your Facebook engagements, Twitter analytics, etc. for insights and actionable data that you can combine with all the other data you have collected.
We use data from multiple sources when we create planograms. You could think of a planogram as the last chapter of a story – one about what products should be on the shelf and where they should be placed. To create this story we use data from wholesalers, manufacturers, online resources, in-store visits, syndication services, and print ads in industry publications. All this combined data allows us to build the “story” about why products deserve a spot on store shelves, i.e. a planogram.
Another example of how we normalize and combine disparate data to create a story is our pricing strategies that we develop and maintain for retail stores. For this, we use data we collect from meetings with manufacturers, syndication services, item research, shopping local stores in our region, trade publications, and analytical tools to create a “story” or base strategy as to why products should be priced a certain amount. Then we create localized strategies for retailers within specific regions of the country by analyzing data received from wholesaler clients and collected during store visits in that area. For each region, we combine our base data with the region-specific data to develop a localized pricing strategy.
We can look at our data from a variety of angles for opportunities to tell a story. We’ve used our data and market research to build a story for a manufacturer about why their product belongs on shelf – otherwise known as a buyer presentation. We can delve into our data to tell a story about product successes two, three, or more years after launch; ingredients that are popular across categories; the white space in a category or subcategory, and so much more.
So the next time someone asks you to tell a story, use your imagination to think of all the different places you could draw data from to develop it, don’t just focus on data found in computer files.
