How Can Retailers Get Started With In-Store Analytics?
Soon your ability to compete will be largely tied to creating value from data. Not just online, but especially in-store.
But, how do you move from talk to action? Here I’ll go through key 5 steps to help you get started on testing out an in-store analytics program.
At this point, I’m assuming you’ve already selected an in-store analytics solution. If not, I recommend starting with my article from last week that offers tips and advice on selecting an in-store analytics solution and provider. Otherwise, keep reading…
1) What Answers Am I Looking For?
Defining a results-driven analytics strategy starts with knowing your endgame. In order to select your solution, you’ve already figured out at a high-level some of the things you’d like to know. You’ve also had to determine whether you’re looking for more operational-specific insights to find cost-savings and improve workflow and workforce efficiency, more marketing- and sales-specific insights to improve merchandising and store layout performance and ROI or both. But, now it’s time to really start getting granular. The easiest way to do this is to start by defining the decisions that need to be made then mapping out what data would be needed to inform those decisions.
For example, perhaps you’ve decided to focus on more marketing- and sales-specific analytics, you’ve noticed that you’ve got a few stores that have a pretty high traffic rate, but lower sales numbers than some of your lower-traffic stores.
At this point, perhaps you’d like to know, more about why your shoppers aren’t converting. Maybe you’d like to know what are the demographic profiles (ages/genders) of shoppers visiting these stores? Are they noticing your merchandising? Are they stopping for your merchandising and then engaging? What areas of the store are they going to? Which departments/categories/areas are they spending the most time in?
This is just a general scenario, but hopefully you’ve started to see how to define the decisions you need to make and map out what types of information you’d need from your analytics.
2) What Defines A Good ROI?
What’s the payback? No sense deploying something that will cost you more rather than earn you more. If you want to do category/department-level analytics to understand how shoppers engage in particular areas, how could this understanding and change impact your sales? How many additional units would you need to sell to get a return? Make sure to clearly outline what KPIs you are looking for from the start, just like you would do with any campaign.
3) How/Where Will I Integrate My Analytics Solution?
Are you planning to just rollout some new store merchandising with the analytics embedded? Or are you planning to mount your analytics in shelves, ceilings or other structures already in the store? All these scenarios require different planning and costs, so be sure to think through what the best solution is for you ahead of time.
Also keep in mind for this test, you’ll need to pick a statistically relevant sample of stores, mixing shopper demographics, regions, levels of urbanization, etc.
4) Are There Different Store Layouts to Consider?
Your store locations likely won’t all have exactly the same layout. You’ll need to figure out what that means in terms of integration. Create a few different integration scenarios based on your store layouts.
5) What Other Data Do I Need to Get Answers?
Will you need to correlate any of your in-store analytics data with other data sources, maybe POS data or ecommerce & mcommerce data? Make sure to have this structure setup so that all your data can be easily exported to make this process as straightforward and easy as possible.
If you’d like to learn more about in-store analytics, I highly recommend checking out our whitepaper:
Retail Analytics: Understanding the Options
Learn everything you need to know about in-store analytics to make the right choice for your store.
Image Copyright: iStock /peterhowell