How Can Brands 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 two things: 1) check out my article from last week that offers tips and advice on selecting an in-store analytics solution and provider. 2) Check out InReality’s in-store analytics solution, of course! Otherwise, keep reading…
1) What Answers Am I Looking For?
Defining a results-driven analytics strategy starts with knowing your endgame. To select your solution, you’ve already figured out at a high-level some of the things you’d like to know. 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.
Perhaps you’ve noticed that you’ve got two stores carrying your products in one city, and one is doing really well, but the other is not, despite both stores meeting compliancy.
At this point, perhaps you’d like to know, what are the demographic profiles (ages/genders) of shoppers visiting these two stores? And, how many are looking at your displays or products, stopping and then engaging versus just passing-by from one store to the next?
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 display-level analytics to understand how shoppers engage with your brand, 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?
Brand-level analytics are most likely going to be in the display, shelf or other marketing structures. Some brands with store-in-store areas will be able to use ceilings. For the display-specific opportunities, you have to decide how you are going to integrate the actual hardware in your display. Will you plan for new displays to have them embedded and or will you retrofit displays already in stores to start a pilot? Both 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 carrying your products, mixing shopper demographics, regions, levels of urbanization, etc.
4) 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.
5) Are There Any Restrictions?
This is where you’ll need to work with your retailer. What will and won’t they allow? Perhaps you’ve opted for a WiFi-based analytics solution—will the retailer allow you to use their WiFi? Each retailer will have different standards, but we’ve found that most are very receptive to working with brands who want to learn more about their shoppers and create targeted customer experiences around their needs and preferences. Definitely consider offering to share insights with your retailers as well.
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 brand.