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Why data will become key to c-stores profitability

When it comes to pricing and knowing what to stock, it will all come down to real-time data.
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Convenience Store Shelves with Food
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In today’s c-store market, questions about pricing and inventory management are becoming more critical. With consumers becoming more conscious of their spending and looking for more value for each dollar spent, c-stores need a deeper understanding of how to price their inventory and to know what it is they need to stock to stay competitive.

Many likely still remember the days when pricing and inventory management were done with paper and a pencil. You would carefully take stock of what was on the shelves and behind the counter, what was in boxes waiting to be opened and the items inside placed on the shelves and reconciled that with what was ordered; and one restocked accordingly. Pricing usually followed established business patterns and were stable, with accommodations made for promotional pricing, season pricing, etc.

While that worked before, in today’s market a c-store needs to know more about what is going onto and coming off their shelves, both to better understand what it is that their customers want and to get a better understanding of how to price them. That, in-and-of-itself is no easy task, no matter how skilful one is with paper and pencil.

“If you are a merchant and you have some 100 or 200 products, understanding how to price those products and how to price them differently at your different stores, stores that can exist in different markets and going up against different competitors, is extremely complex today,” says Matt Pavich, senior director of strategy and innovation at Revionics, an Aptos Company, a developer that provides lifecycle price optimization software for retailers giving them advanced retail price optimization tools and pricing analytics.

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Matt Pavich
Matt Pavich, senior director of strategy and innovation at Revionics, an Aptos Company

Because of that complexity, it is a challenge now for convenience stores to know what is happening on a granular level to make pricing and inventory decisions that reflect real-time market conditions and consumer trends.

Pavich gives an example of a franchised convenience store operation with multiple locations where each location carries over 200 different products across its shelves. Each of those locations may also be serving different markets and customer demographics. The challenge is how to get a proper read as to what is happening at each store with each of those products on the shelves, and to price them accordingly. 

READ:  Canadian retailers enhancing customer experience through generative AI

“The old way of doing things—my costs for those goods or a good went up X amount and I need to raise prices by Y amount — just does not work anymore,” Pavich says. “What may be the right pricing strategy or price for a good for a store in London, might not be the right one for a store located in Laval.”

Add to that the impact of different stores competing for the same consumer dollar as your store, all of which are trying to make sure shelves are filled with products to attract that consumer and to turn a profit, pricing and inventory control quickly becomes overwhelming.

“Take something as simple as potato chips,” Pavich adds. “You have different producers often producing that product in different formats that you have to price, and add to that that you have stores in different locations, some in urban areas, others next to highways, others in downtown cores, such as Toronto or Montreal, and add to that the competitors you have around you all competing for those customers who want to buy potato chips or other salty snacks. You need to take all those consumer and market inputs and use them to make decisions on what to buy and what to price your products at.

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Pavich says that is where Revionics can help. Its pricing platform and other solutions are made to take in the multiple real-time data points and customer information and buying behaviour to provide a retailer with insights into market and consumer purchasing behaviours that can then be used to make decisions about inventories and prices. 

To give a simple example, a convenience store operator with multiple locations can now take data from seasonal shopping trends, inflation, competitive pricing on the number of products sold at locations and within customer segments, to the impact of promotional items for sale. That information, along with any other sales and market information, can then be used to map out specific goals for the stores, from overall profits, revenue generation to the total number of items to be sold of specific goods. 

The convenience store operator can also look at how changes to its private brands will impact other similar product categories and their prices in the stores, or how to optimize those private brands’ pricing to increase sales and profits, without impacting other similar products and incurring a loss; or how to correctly place an item on sale or rollout a markdown on some products while still maintaining profitability; or how a competitor’s pricing of similar products is impacting the sales of the products in the operator’s stores.

READ:  Ask the Expert: How can c-stores tap into the power of retail media networks?

The idea is that by using advanced analytics and AI and having multiple data points to analyze, a retailer can ensure they have on hand what customers want when they enter the stores and at prices that are attractive to keep them coming back.

Another advantage of having this kind of information and analytics is the ability to identify consumer trends and what may be driving them, and then to take advantage of trends to entice customers into the stores and drive sales and profits.

Pavich gives an example of a store or of multiple stores in a specific area seeing a sudden increase in the sales of a certain snack or item, while the same snack or item is not seeing any similar increase in demand and sales elsewhere. Multiple factors could be happening with that sales spike: what is the competition doing, is there a social trend increasing the sales to even the weather in the area, or a price change. Knowing what is happening can then allow the retailer to adjust inventory and pricing to take advantage of that surge in consumer interest or to see if it can be replicated at other stores.

“What we are doing [at Revionics] is giving them predictive analytics to help them do such things as grow revenue and offer more value to customers,” he continues. 

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