How C-Stores Can Use Sales Data Analytics To Boost Sales


Sales at top-performing c-stores have changed dramatically over the past decade compared to the rest of the industry. And sales data is one big element driving this change. 

The NACS (The Association for Convenience & Fuel Retailing) mirrors this same idea. In a recent piece on their magazine, they shared how top-performing stores have embraced a transitional, forward-thinking business model — one that relies heavily on data analytics to uncover consumer trends and preferences. 

This has led to rising sales in categories like foodservice and packaged beverages, while sales in lower-performing stores remain stagnant. 

So if you’re hoping to join the ranks of the industry’s top performers, we’ve rounded up five ways you can use data analytics to boost sales right now. 

1. Look at products and categories that are commonly purchased together

Image source: Koupon Insights Report

As you know, c-store baskets are small and trips are fast. So, understanding the handful of items consumers are buying together can provide valuable insight. 

Once you’ve identified common product pairings (also known as products with high purchasing affinity), you can use this information to structure bundled promotions and guide in-store merchandising. 

As you can see in the image above, our data analytics program creates pairing scores for different products. The pairing score is a unified metric that measures the strength of category and brand combinations. Our model runs scenarios for over 10,000 products while considering more than 100 offer types. 

A good example of a successful product pairing promotion comes from Gold Peak Tea, owned by Coca Cola. They ran a two-month bundled promotion, combining a beverage purchase with a popular hotdog foodservice item. Sales from the bundle spiked more than 50 times during the campaign and created a 250% lift over the pre-campaign baseline. 

And if you’re looking for a sure thing, energy drinks have the highest purchasing affinity with breakfast sandwiches in the convenience channel — especially on Friday mornings. In fact, breakfast sandwiches are 50% more likely to be bought with energy drinks than products from any other department.

2. Analyze YoY growth to spot categories boosting sales

Analyzing categorical growth can help you understand macro sales trends that hold true even outside of c-store. Hard seltzer, for example, has had significant year-over-year growth due to the explosive popularity of the category — achieving a 146% lift on a sales-per-store basis. 

When you identify categories with high growth, like hard seltzer, it’s time to consider expanding your inventory and product assortment to take advantage of the trend. 

United Pacific, for example, which owns 509 stores throughout the western U.S., expanded its hard seltzer lineup at the beginning of the pandemic in response to categorical growth trends. They’ve added Corona Hard Seltzer and Truly Lemonade Seltzer, in addition to expanding their White Claw selection and adding 12-packs. 

“White Claw has been on fire,” said Kelsey Capellino, category manager of adult beverages for United Pacific. “We’ve encouraged stores, and we’ve been working with our distributors, to build ambient stacks of those items (12-packs) for holding capacity purposes.”

Once you’ve expanded your product assortment, you can run promotions to drive foot traffic, since products in high-growth categories are already popular with consumers. You can promote them on their own to increase trips or bundle them with pair-able items to boost basket size. 

3. Structure offers based on customer location

Image source: Koupon Insights Report

Using data analytics to identify regional differences is another good way to boost sales. After all, consumer preferences and behavior often vary largely by location.

Some brands have a unique presence in certain areas of the country, while others are more consistent nationwide. In the image above, we’ve highlighted how beer sales fluctuate by region.

While Bud Light is sold the most in three regions (demonstrating nationwide popularity), Miller Lite wins in the northeast. Coors Lite places second, third, and fourth in three regions, while Corona makes the board in the West and Michelob Ultra comes in at a surprising second in the South.

Of course, this is just beer. But every category and brand tells a different story in each region. 

Plus, brand preference isn’t the only thing that varies by location. 

Certain promotions work better in one area over another. Customers in some regions, for example, respond well to discounts in dollar amounts (Save $1 on Muscle Milk!) But customers in other regions respond better to offers of the same value listed as bonus points instead (Get 500 Bonus Points when you buy Muscle Milk!). 

Using data analytics to determine the type of product and offer that resonates most with customers on a regional level allows you to target promotions according to the way customers respond best to coupons. 

And we all know that coupons drive store trips and higher basket spends — ultimately boosting sales.

4. Run store-level breakdowns to identify low-performers

Image source: Koupon Insights Report

You can also use data analytics to look at sales on a store-by-store basis. Once you identify high and low-performing stores, you can dive deeper into the data to determine the differences. What are your top stores doing that the others are not? 

We recently conducted an analysis across our network of 45,000 c-stores and identified several factors correlated with high-performing stores. 

As you can see in the chart above, coupon use had the highest level of correlation with sales. In top-performing stores, consumers were 52% more likely to report coupon usage compared to low-performing stores. 

If you find this to be the case in your stores as well, you can run store-specific promotions designed to boost foot traffic and drive sales. 

A good way to deliver store-specific promotions is with personalized mobile offers. They can be sent directly to customers with a purchase history at the targeted store. 

As far as what products to promote, beverages are the top driver of c-store trips according to our data. Overall, packaged beverages make up 15% of c-store sales. And 53% of Gen Xers visit a c-store two to three times a week specifically to purchase a dispensed beverage. Plus, beverages often motivate the purchase of other products, like snacks, candy, and foodservice items.

5. Analyze sales based on time of day

Image source: Koupon Insights Report

Timing has a big impact on c-store traffic and sales, but it can vary widely by specific brand or category. Coffee, for example, is obviously a morning thing. It wouldn’t make sense to heavily promote coffee at 5 p.m. 

The timing of sales for other brands and categories, however, isn’t always as obvious. In the image above, for example, we explored how Belvita biscuit and Oreo cookie sales fluctuate throughout the day. 

While Oreo sales remain relatively consistent, a huge portion of Belvita’s sales occur between the hours of 6 a.m. and 8 a.m. Understanding when these spikes occur can help you run targeted promotions that encourage buying behavior during the periods when people are most likely to want the product. 

You can also combine this strategy with the product pairing method mentioned earlier — using categories with clearly defined peak hours to promote products with high purchasing affinity. For example, use coffee and morning traffic to promote Belvita breakfast bars: 

  • Morning special! Free coffee when you buy any Belvita breakfast bar! 
  • $1 off Belvita breakfast bars with any coffee purchase!
  • Earn 500 bonus points when you buy a coffee and Belvita breakfast bar this morning! 

Daypart insights can also be used to inform stocking and package size decisions, boosting sales by having the right product in front of the right customer at the right time. 

Anheuser-Busch, for example, discovered through data analysis that singles are sold consistently throughout the week whereas multipacks are bought in a very tight window (on Fridays) — leading to a high out-of-stock risk in many stores. 

So, they aligned deliveries to meet demand. According to Anheuser-Busch, beer baskets average two times more total units than baskets without beer in them. David Vartanian Sr., director of national category management for Anheuser-Busch explains that “Our goal from a category perspective is to help the retailer capitalize on these consumer trips to grow their overall baskets.” 


Top-performing c-stores are already using data analytics to their advantage. Will you join them? 

Here’s a quick recap of five ways to use data analytics to boost sales right now: 

  1. Look at products and categories that are commonly purchased together.
  2. Analyze YoY growth to spot categories boosting sales.
  3. Structure offers based on customer location.
  4. Run store-level breakdowns to identify underperforming stores.
  5. Analyze sales based on time of day. 

Interested in learning more on how Koupon can grow your c-store and drive shopper engagement?