Let’s do the math. There are twenty-six letters in the alphabet, so the computer industry has a maximum of 17,576 three letter acronyms (TLAs) available. At a rate of one per day–and the folks who make up these things definitely work weekends–they would all be used up in 48 years. But all letters are not created equal; think of poor overworked “M”, which starts both “management” and “measurement” and is consequently present in about half of the TLAs that matter. So a certain amount of acronym duplication is inevitable. And although the intended meaning is usually clear from the context, the meanings of some TLAs are similar enough to cause genuine confusion.

The most prominent current example is BPM, which can stand for Business Process Management or Business Performance Measurement. Marketing systems vendors, and the analysts who love them, have analogously promoted MPM as Marketing Process Management and Marketing Performance Measurement, and sometimes Marketing Performance Management. What makes things even worse is that many Marketing Process Management systems have a Marketing Performance Measurement component. Or maybe it’s the other way around.

The result has been to take the inherently murky concept of measuring marketing performance and muddy it still further. Marketing performance is inherently ambiguous because it’s not clear what we’re measuring. Is it the efficiency of the marketing processes themselves, such as how many marketers does it take to change a media plan? Or is it the effectiveness of the process, such as how much value did the campaign generate? If we are measuring effectiveness, just how do we calculate the “value” of a marketing campaign anyway? And where do customers and customer value fit into all this?

There are no simple answers but we can at least clarify the questions. Here is a typology that may help in planning marketing performance measures.

• Efficiency metrics describe the cost to execute marketing projects. These projects are typically called something like a campaign or program. The two major efficiency metrics are staff hours per project and cycle time per project. These metrics are often but not always correlated, and in many cases reducing the cycle time (e.g., getting campaigns out the door quicker) improves results in ways that are much more important than any internal cost savings. This is why cycle time and staff hours must both be measureed separately.
• Program metrics measure program effectiveness by comparing their costs and results. Most marketing programs generate a set of marketing contacts, such as media impressions or direct mail pieces. But some contacts are worth more than others, depending on the number and quality of responses they generate. So simply calculating the cost per contact is rarely enough. Instead, program metrics must calculate the value of results.

Direct marketing programs can use immediate response metrics such as number of orders, revenue or profit per order. These can then be related to cost to calculate profit per program or return on investment. But direct marketing is an exception: most programs generate sales that either cannot be traced to a specific promotion or are made by a third party such as a retailer or dealer who does not report them to the advertiser at all. In these cases, marketers must calculate inferred sales by looking at reorders or product movement figures from vendors like Nielsen and IRI. Specialist vendors like Veridiem and Marketing Management Analytics can do sophisticated econometric modeling to estimate the incremental impact of such marketing programs, taking into account all other factors simultaneously affecting the market.

But marketing programs have results that extend beyond immediate sales. Savvy marketers recognize this and evaluate two additional classes of metrics:

• Brand metrics measure attitudes related to a product, on the assumption that these are indicators of future purchases. These include awareness and knowledge of the brand, preferences for the brand vs. its competitors, purchase intentions and product satisfaction. Most of this information is gathered through surveys. Sophisticated marketers correlate marketing programs with changes in brand metrics, and changes in brand metrics with future sales. This lets them assign financial value to marketing programs to calculate a long-term return on marketing investments.
• Customer value metrics estimate future purchases by individual customers and customer segments. Although they are concerned with the future, customer value metrics are derived from historical data. Two key measures are retention and purchase rates. If companies assume these will continue unchanged, they can be combined to estimate the future value of a new customer. This value can then be built into the return on investment assessment of a marketing program. Add acquisition rates and you can estimate the future cash flows of an entire business.

Estimates of future acquisition, retention and purchase rates are highly speculative. Most analysts recognize this and discount them heavily in their calculations. A more immediate use for these metrics is to track changes in acquisition, retention and purchase rates from period to period. This highlights positive or negative developments that bear closer examination. Companies typically do this analysis for customer segments in addition to looking at the over-all averages. Segment results are important because customers from different marketing campaigns, lines of business, demographic groups and other categories are known to behave differently. Breaking them out distinguishes the impact of changes in the customer mix from changes in behavior within individual segments.

Basic customer value metrics can be calculated without tracking results by individuals. But individual data allow more precise reporting of individual customers’ previous value, current status, and predicted behaviors. This has operational uses for targeting promotions and tailoring service treatments. From a metrics standpoint, it also allows companies to track customers as they move through the buying process and to estimate the long-term impact of marketing campaigns that may not generate an immediate response. Viewmark, DecisionPower and Satmetrix all offer tools that perform individual-level analysis, although the details vary greatly. Upper Quadrant provides response analysis without individual data.

These four types of metrics–efficiency, brand, program and customer–can each be elaborated almost indefinitely. Different companies will focus on different metrics depending on their situation. But it’s important to consider them all when building a system for marketing performance measurement.

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Copyright 2005 Raab Associates, Inc. Contact: info@raabassociates.com

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