C-Stores Look to Turn Data Into Results
By Tom Ryan
With the introduction of services, such as Information Resources’ (IRI) new AllScan Convenience Store Tracking service, c-stores appear to be catching up to other retail sectors when it comes to capturing sales data.
The service, which officially launched last week, leverages POS data from more than 11,000 sample convenience stores, including major nationals, such as 7-Eleven and Circle K, as well as independents, across 54 syndicated markets. It promises to offer visibility into all product categories with weekly granularity for deeper business insights, improved information quality and greater accuracy at the national, regional and local market levels.
C-stores, according to IRI, have been unable to effectively analyze and understand sales and brand performance across markets due to limited information.
“Since the convenience channel represents a significant portion of business to many CPG manufacturers, you need to be able to perform the typical brand and category management analytics like you do in grocery, drug and mass outlets,” said IRI president and CEO Scott Klein, in a statement.
John Lofstock, editor at Convenience Store Decisions, told RetailWire that Nielsen and NACS (National Association of Convenience Stores) also offer a data scanning service for convenience stores, but he said the c-store industry certainly welcomes another tool for rich, real-time data collection.
“The need for this data is exceeding the availability,” said Mr. Lofstock. “This kind of data is available from only a few sources.”
Mr. Lofstock estimates that c-stores are about 10 to 12 years behind supermarkets in capitalizing on access to POS data, and have been a step behind competitively because of it. However, he estimates that c-stores will be able to ramp up to speed rather quickly.
“The supermarket learned by trial and error,” said Mr. Lofstock, “They were scanning for years and doing nothing with the scan data. But once they started using it, they found a wealth of information.”
“It’s different for c-stores,” adds Mr. Lofstock. “They can learn from the obstacles and the barriers that supermarkets faced and quickly use that data to create loyalty programs and better promotions, market the stores more efficiently and capitalize more quickly on trends. These are all things the industry is trying to do but they just need more tools.”
Discussion Questions: How do you think better tracking of POS data at c-stores will affect merchants in this channel? What will it mean for suppliers? Are c-stores now in a position to do something with the data captured and, if so, what will it mean to the competitiveness of convenience operators?
C-stores have been way behind other retail formats in developing the right merchandising mix. Yes, some have been innovating, but for the most part the wholesalers have run the show. Scanning was slow getting into C-stores, but is fairly widespread today. By studying the scan data, what will be learned first is what is not selling. The majority of C-store merchandise turns like jewelry. Replacing what is not selling with new product should make a big difference. With Tesco’s new modified C-store concept, consumers will see more traditional food products in C-Stores.
Hopefully “analysis paralysis” will not be a side effect of providing copious new information to decision-makers unused to it. Additionally, if they begin relying solely on the new data source rather than their intuition and experience, there will be less opportunity for innovative new products and services. Research is a tool best used with a light grip.
My opinion is that the C-Stores we have been exposed to, with the marketing of our CashValue card loyalty program, are currently in no position to use their data. We have partners that we have shown a 145% increase in transaction price card holder vs. non-card holder. We have shown close to a $.50 lift in overall transaction average inclusive of non-cardholders since program inception. Yet, we have struggled to get these small to medium sized c-stores to even look at their data let alone integrate our technology direct into their POS. The C-Store market reminds me of the famous Stan Laurel quote: “You can lead a horse to water but a pencil must be lead.”
Having reliable POS data should enable C-Stores to improve their assortment by not only eliminating unproductive SKUs but also leveraging successful ones (stockouts, promotions, etc…). It should also help them optimize the inventory they carry–both in terms of units as well as dollars. If utilized properly, this data can also lead to better forecasting which in turn will help vendors improve their service and may even result in fewer days in the supply chain.
More data is good. Understanding what the data means is always a challenge. However, with the introduction of Tesco and Family Mart into the convenience store mix, understanding consumer purchase behavior will be increasingly important.
A rich source of data for C-stores will be a welcome addition to the marketplace for both retailers and vendors. From the retailer side, they will need to invest in analysts and training in order to make the best use of the data. Areas that should be evaluated besides base sales data are an analysis of the valuable floor space for merchandising and the coolers that line the walls for sales and profitability
Vendors will be able to review their product mix, their merchandising results and make future decisions based on better information than they get today. As with any data source the biggest questions will be who will invest and will they utilize the data?
David Biernbaum says that “Fact-based data that results from scanning simply tells us what already happened…” As long as thinking about retail continues to be an obsession about people and products, we’ll continue to drive retail through the rear-view mirror. Having said that, measuring results is clearly a prerequisite for management accountability. Measurement of the process that leads to the purchase is the rich ore that leads to performance.
It took Deming and Juran a few years to teach the Japanese how to focus on process instead of simply counting successes and failures (outcomes in quality management.) The revolution in active retailing, which is following a similar course, will probably not be nationally focused.
There are lies, damn lies and statistics said Mark Twain. Capturing better POS data will help C-stores to improve their product mix, but it fails to capture the condition of the stores, the placement of the products and their condition. All 3 of these factors is critical to determining how successful a product mix, store layout and pricing really are in the conditions of the c-store. Most importantly, the POS only records the sale, not the conditions leading up to it, nor the failures that often prompted the sale (i.e. did an out of stock item force the sale, was it very hot outside, or a blizzard, etc.). Interpreting the data at store level is the most difficult thing for any retailer to do, and it still remains more art than science.
The availability of POS data for C-store operators will give the suppliers to this channel the ability to make informed recommendations and enable them to assist the c-store operators to improve their product assortment to take better advantage of regional consumer preferences.
I also think that the c-store operators will now be in a position to narrow their “fill-in” grocery selection and better apply their space and inventory investments into categories that will enhance their revenues and profits.
The challenge for independent and small supermarket and convenience store chains is not only obtaining the data, but converting it into meaningful action for the store operator. The IRI material seems to focus on the manufacturers competing for store presence. The operator needs someone on their side to help them maximize return on the total store space.
The convenience store space is truly a “zero sum game.” There is only so much space and inventory investment available. A manufacturer who misses an opportunity loses. But the goals of the manufacturer are self centered and may not maximize the return for the store operator. The big guys have their central merchandising department fighting for their success. The individual operators need someone on their side who can help them interpret the data from someone like IRI and turn it into actionable items for their benefit. The problem is that the incremental return for one store may not justify the cost of critical data analysis. This is where syndication and the use of internet based service can help the independent and small operator.
IRI has a huge opportunity here if they can focus their service offering on the total store return rather than individual brands and manufacturers. The potential in this channel is huge once you recognize that its return comes from leveraging the reach of the network to collect small fees from thousands of users. By using analytics based on individual store space and transactions to make total store allocations, IRI can help individual owners compete against their larger cousins.
The most immediate impact should be the elimination of about 50% of the skus stocked. Top performing c-stores have already disabused themselves of the notion that they need to stock laundry detergent and canned tuna. Now there is no reason for the rest not to know.
The use of better scan tracking in C-stores will result in the C-store channel becoming as dull, boring and sadly predictable, as the traditional retail chains have become. Fact-based data that results from scanning simply tells us what already happened as the result of the product assortments and choices we already provided the consumer when he or she was last in the store. We learn nothing about what possibilities exist to provide something new, more exciting, and alluring to the consumer.
So, when it comes to using scan data, I caution the C-store channel to catch up to speed with the others with a great deal of consideration for what makes the c-store channel a little bit unique, and not to sacrifice those points of differences, or else C-stores will simply become lesser versions of “regular” stores.
Being able to capture the POS data has the potential to make a dramatic change to the convenience store operator–dramatic being defined by increased sales and traffic. Traditionally, convenience stores have done little target marketing and have banked on “presence” marketing concepts. If located on a busy corner, traffic will come. With intelligent data, convenience stores will be able to take a new holistic view of the consumers they are attracting and why-and possibly more importantly–the ones that they are not attracting. The new data will allow more pointed target marketing and the ability to create fun and profitable promotions. Very exciting for the convenience store industry.
The suppliers will have more data readily available to assure they have enough product at the right time. For instance, here’s a fictitious example: milk and bread have a 60% sale rate on Mondays and Thursdays. Therefore, they may change there inventory numbers, delivery times, etc. to make the most of this valuable information.
How will this affect non-informed competitors? It could be detrimental to their business. As a convenience store gets smarter–more marketing inclined and customer service inclined–watch out!
IRI AllScan will help convenience store managements see what their merchandise mix is missing, compared to other convenience stores. People also need to compare other stores, especially fast food restaurants and supermarkets. Convenience stores are not just little groceries with gas pumps. They’re also delis, newsstands, mini HBA stores, and sometimes, tourist info kiosks. Any data is valuable that helps them compare their performance to the big picture elsewhere, with specific recommended actions.
Yes, in theory, C-store operators will be able to make better-informed decisions about product mix and stock levels. But this assumes that they have the time and training to analyze the reports provided and deduce appropriate action, taking into account their own data on out-of-stocks and their knowledge of their own retail space. Major convenience store chains probably do indeed have the resources available to take advantage of this sort of analysis, and some of them are starting to do so. But in a trade where, by-and-large, even analysis of own-POS tends to be rudimentary at best, will the improvement in quality and spread of channel data encourage more operators–the smaller operators; the independents–to invest both the money and the time required to fine-tune their operations? Probably not.