ATLANTA -- The enormous volume of syndicated scanner data available for measuring trade promotion can rapidly swamp brand marketers in complexity. What is needed is a strategy and a set of tools for simplifying evaluation and decision-making, said one expert at a conference here.
"In one of our categories we have 28 billion numbers. That's completely overwhelming," said Beth Jarocki, director of syndicated services for Ralston Foods, St. Louis.
"You have 2,700 items and 200 measures or facts, depending on what service you buy. There are over 200 geographies. And then you have three-and-a-half years of data. It is a completely overwhelming task to analyze that when you are talking about account-level data."
In a presentation at the conference, Jarocki outlined a strategy she advocates brand managers in her own company use for paring down the complexity of promotion analyses. "You need a practical insight into the numbers," she said. Her presentation was made at conference titled "Efficient Promotion: A Fundamental Premise of [Efficient Consumer Response]," sponsored by the Strategic Research Institute, New York.
Brand marketers today normally have access to scanner data from Information Resources Inc. or Nielsen, she observed. Most also buy some level of key account data. But few have the depth of resources to needed to analyze promotion performance.
As Ralston Foods' expert on syndicated data, she said, colleagues came to her for practical help in quickly sorting through the data and finding key insights. "How do I measure my trade promotion? That is the basic goal here," she said.
Jarocki recommended four main "tools" for simplifying the data and honing in on key results that can drive correct decisions:
Promotion response data. Also known as lift, in chart form this allows analysis of the percent increase received from merchandising activities. Typically, results show that a combination of feature and display activity yields the greatest lift.
Lift information can be used to help benchmark one brand's promotion performance against a prior year, against a competing brand, or against total category performance, she said.
Account ranking. This allows brand marketers to sort through the mass of information and make distinctions between accounts that are overperforming and underperforming. A national ranking will show that certain brands will consistently do well in certain accounts, she observed. But even within a market, response numbers can be very different between accounts.
Decision tree. This allows deeper-level analysis, by further sorting information into actionable bits, measures or facts. "If my volume is changing, is it due to base volume or incremental volume? That is the first cut at the data," she said.
Within incremental volume, for example, there would be four areas to drill into for deeper analysis: promoted pricing; promotional response-lift factor; level of merchandising support (as a percent of all-commodity volume), and the mix of high-quality vs. low-quality support.
"Bump" chart. Visually portraying what is going on at the account level makes it easier to compare one brand's promotion against a past year, a competitor, or an entire category.
Jarocki cautioned users of syndicated scanner data to be aware of several limitations.
"Anytime you are dealing with the IRI or Nielsen numbers, you want to make sure you are using them directionally. In most cases you are using sample data that has been projected," she said.
In addition, Jarocki said, brand marketers should validate their analyses with field sales experience. She described this as "combining common sense with what the numbers tell you."