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New Technology Boosts Store Sales

With margins squeezed at the pump in many areas of the nation, c-store owners/operators must get a lot smarter about making money inside if they want to win the marketing war. That means they need sales maximization, a fancy term for getting the most gross profit out of your square footage.

Maximizing profit used to take a lot of guesswork. Most marketers depended on their suppliers to help them select products and merchandising strategies. Many still do. The unfortunate part of relying on suppliers is that they have their own agendas. The supplier rep is likely to push his highest margin products or those that have a special volume bonus that quarter to pad his personal paycheck.

Until recently, there wasn’t much an independent storeowner could do other than put his trust in his supplier’s advice. Not any more. Thanks to data warehousing, a storeowner now has reasonably priced access to detailed information about the likely buying habits of current and potential customers. Through zip code stratified credit card data that tracks actual item sales, and sophisticated sensitivity modeling used in conjunction with demographic data, a savvy storeowner can now know, with certainty, exactly the right products to stock.

The first step in the process is determining a store’s actual market area. This sounds simple, but can get a bit complicated in a metro market or high traffic street frontage store.   For instance, a store may be located in a certain neighborhood, but draw much of its traffic from outside that neighborhood. The easiest way to verify market area is to conduct a quick customer survey. As customers pay for their purchases, a clerk asks them for their home zip code.   A tally box with common zip codes simplifies the recording process. With just a week of survey data, you’ll have your true market area defined.

With the market area defined, the data firm can now give you a myriad of information about your customers. Most firms use demographic “mosaics,” a standard used to breakdown consumers into sixty-two different buying types. More sophisticated firms can give you actual purchase data by zip code. You can see exactly what they buy, which means you can put exactly the right “stuff” in your stores.

But it gets even better than that. Through predictive consumer behavior modeling, these data firms can even tell you what margin (mark-up) certain consumer groups will tolerate within product categories. This is where the data abilities get very sophisticated and the more sophisticated your pricing system, the more you can take advantage of the information to maximize margins. For instance, you may discover that your customers are willing to pay twice as much mark-up on a can of coffee as on a can of soup (or vice versa). If you use a standard mark-up on all your canned goods, which includes both soup and coffee, you may be missing profit or driving away sales, depending upon how far your standard mark-up is from the profit maximizing suggested mark-up.

So the keys to maximizing your store sales are first, have the stuff your customers will buy, and then set the price on each product that will maximize gross profit. If this sounds too time-consuming, just bear in mind that all the big chains are already using this technology. That’s why some small, unsophisticated storeowners are eating their dust!

Like any other new technology, it’s not error-free, so you’ll still want triggers in place for slow-moving products. Always be tweaking your offerings based on actual sales data and be alert for non-movers. If you bring in a product that doesn’t sell, get rid of it somehow, so that valuable shelf space can go to a product that moves and generates margins. That may mean returning it to your supplier for a refund, or moving it through a discount sale – just don’t sit on it. Remember that every $100,000 in excess inventory you keep on hand costs your company about $10,000 a year in direct expense.

As you fine-tune your product selection, you should also fine-tune your “build to” stocking quantities. A good general rule of thumb is to keep 1.5 times your supplier frequency on hand for every product. In other words, if your supplier delivers a certain product every 7 days (once a week), then you should have 7 x 1.5 or about 11 days of stock on hand.

Frequently when store chains begin managing their inventory aggressively, they end up with empty shelf space. Because it’s important for a store to look fully stocked, either go get some new product offerings (based on your customer metrics) or redesign your store layout to look full. Chains that have become sophisticated at sales and profit maximization often find they reduce their product offerings which allows them to make their stores roomier and more customer friendly while making higher profits than stores that are chock-a-block full from top to bottom and side to side!

So, physical layout is the last important step in profit maximization. The same data firm that helped you get the right products in your store can now help you merchandise correctly by providing lists of highly correlated products for your consumer group. For instance, a cold tablet purchase may be accompanied by the purchase of a box of tissues and orange juice. Once your products are listed in a database, the metrics firm can give you groups of high correlation products for merchandising purposes.

Some marketers may think all this sounds too high tech or too much like work. If you are one of those marketers, remember that some very formidable competitors are already using these tactics. If you’re going to stay in the war, you better be armed.

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