How to Use Product Velocity to Expand Retailers and Improve Store Footprint

Getting your products in stores is half the battle of reaching your audience but your work is far from done. Once distribution gets you in the door, pay attention to product velocity to understand how you’re performing with a retail partner so you can fine-tune your strategy and maximize your performance. That’s where Store Level Data comes in.

Velocity tells you how many units you’re selling per point of distribution. For example, if you’re a beverage brand, you want to know how many cases you’re moving with a retailer each week. 

The average rate of velocity lets you know your overall performance so you have a sense of how many cases you should expect to move on a weekly basis. As one expert puts it, you look at product velocity as part of a calculation: Sales = Distribution X Velocity. In other words, velocity is a true measure of consumer demand for your product.

While average velocity is great for a high-level view, the velocity by store is where you get a more insightful look at performance. Your average velocity is most likely not evenly distributed across all stores; you’re going to have some top performers and some underperformers.  

For brand teams, the value of studying velocity on units per store per week basis helps you understand which locations are driving your velocity. For example, SLD shows that if your average velocity is 50 cases per week, your best store could be moving 60 cases and your lowest performer is at 20. The store with the strongest demand is either doing something right or their shoppers are your ideal customers. Similarly, your lowest performing store might need to correct some missteps, or their audience might be different than the others. Whatever the case is, you want to understand what’s happening each store and adapt accordingly. 

You can also study the momentum of your velocity. In the course of a month, you might average 50 cases per week, but it doesn’t mean each week is identical. You could be selling more with each passing week. The monthly average remains the same, but the story suggests you are gaining traction with shoppers and, once again, you want to understand why. If you see the inverse—that is, decelerating velocity—you need to understand the cause so you can course correct. 

Now that you know your overall velocity, velocity by store, best and worst performers, and velocity trajectory, you’re ready to work with your retailer to make some adjustments. 

For your high performing stores, or stores where you see the velocity accelerating, you want to invest more. That might mean asking for an in-store display or making the case for additional shelf space. You clearly have a connection with those shoppers, and it behooves both you and the retailer to maximize the sales potential based on the SLD you’re sharing with them.  

For the underperforming stores, talk to the retailer to find out what the cause might be. Is it a shopper disconnect, a lack of in-store visibility, inventory issues, or something else you haven’t thought of? Retailers don’t want to miss out on sales any more than you do, and SLD brings together all the necessary data you both need to start improving performance.  

You can also take the lessons from this retailer’s SLD to conversations with new retailers. Include insights from your top performing locations in your brand story when you are looking to expand your retail distribution. Top performing stores prove that you already have an existing audience with a strong demand for your product. Data that points to accelerating product velocity can show a potential retail partner that you’re not only bringing a loyal customer base with you, you’re also expanding your reach and attracting new consumers. With SLD, these potential retail partners don’t have to take your word for it: you can point to the data. 

Jim has 30+ years of CPG industry experience beginning on the client-side (Kraft Foods, Marketing/Sales/Category Management) before crossing over to the “dark side” of information services (Spectra, IBM, IRI, Acxiom).  His specific expertise in store-level data spans Spectra (store trade areas, profiling & targeting) to most recent sales and offering development at store-product-day provider RSi (now part of IRI).

Working with the SPINS retailer relationships team, Jim is building the next generation of applications across an expanded channels/network capability and working with existing clients to further harness the power of SLD for the benefit of manufacturers and retailers alike.