Wednesday, December 21, 2005
Let’s say you have a tracking study out in the market in which you’ve identified 15 key brand attributes and have a sampling of customers and prospects rating your brand vs. competitors on each attribute. You also ask about self-reported purchase activity in your category. You survey 200 people each month and read the results on a rolling three-month basis.
Now, using statistical regression techniques, you can correlate brand attribute ratings to purchase activity or purchase intentions to identify the attributes that are most strongly associated with increased category or brand purchase behavior.
Simple, right? Hardly.
There are a great many places where this approach can get derailed or become seriously misleading.
First off, self-reported purchase behavior can be significantly different from actual purchase behavior. Sometimes, people forget how much they bought and which brands. Other times they tell little white lies to protect themselves from the judgment of others (even the interviewer). If you can connect a specific individual’s survey responses back to that person’s actual purchase behavior as reflected in your transactional files, you can close the gap somewhat. If not, you might check to see if there's a syndicated "panel" study done in your category where consumers respond to survey questions and share their actual receipts or credit card statements. Failing that, you can conduct a separate study specifically among a group of category consumers and check to see how self-reported behavior varies from actual purchases, then use that as an error factor to adjust what you get from your tracking studies.
Second, attributes are commonly “lumped” together by consumers into positive and negative buckets, making it difficult to see any one attribute as a real driver to a greater degree than others. This is the covariance effect — a statistical term indicating the extent to which two or more elements move in the same direction. Sometimes it’s helpful to group attributes with high covariance into “factors,” or higher-level descriptions. For example, the attributes “offers good value for the money” and “is priced competitively” might be grouped into a factor called “price appeal.” As long as you aren’t grouping so many attributes together into a few still undistinguishable factors, you can still get a strong feeling for which elements of the brand scorecard might be most important.
There are many more ways that this process can become subtly misleading. If you’re not a research professional or statistician, you might consider consulting one of each in your methodology design. But, time and again, interviews with researchers suggest that the best approaches start with sound qualitative research among customers and prospects to identify the possible list of driver attributes and articulate them in ways that are clear and distinct to survey respondents.
Done correctly, this effort can help directly link changes in attitudes or perceptions caused by brand advertising back to incremental economic value creation. But obviously it takes time and money to lay this foundation. If you're spending a few million (or more) annually on brand advertising though, it might just be worth it.
Have you been able to identify specific aspects of your brand that drive customer relationships? We'd like to hear your story.
Sunday, December 11, 2005
Today, marketing reporting, and to some degree financial reporting, is primarily a function of gathering sales data at the end of a reporting period, massaging it into charts and graphs, and then circulating it for discussion or comment. And for most, even this is no small accomplishment.
This diagnostic approach is rooted in the instinctive human learning method of interpreting past experiences to frame future expectations. At best, that process is effective at helping the organization see where it’s recently been. Only through very intuitive methods do companies attempt to project the trajectory of performance into the future so they can manage to the desired outcome. And only a very few possess the innate (or artistic) ability to properly view diagnostic information and project it with reasonable accuracy, overcoming their own perceptual biases and assimilating the collective wisdom of their entire team. This is the fundamental human frailty marketing dashboards can help overcome.
Without a doubt, there is benefit to having diagnostic measurements on your dashboard. But without components that help you predict the future, the dashboard is only expanding the limitations of memory, not improving decision making. Think again about the dashboard on your car and how it works with your vision and stored experiences. You keep your eyes fixed on the road ahead with only quick glances at the dashboard to see how speed, fuel level, and engine stress will affect the desired outcome of arriving at your destination. Your brain makes millions of calculations per second to adjust the turn of the wheel, the pressure on the gas pedal, and the search for rest areas along the way. You might even have reviewed a map before starting out to form a mental picture in your mind of where you were going.
Today’s vehicles are increasingly equipped with some “forward-looking” dashboard capabilities. Compasses are being replaced by GPS systems that provide real-time mapping to guide you to your destination, alerting you in advance to upcoming turns. Fuel gauges are evolving to become distance-to-empty meters that display not just the current level of the tank, but how far you can go before stopping based on constantly updated fuel economy readings. By focusing your thinking on the journey ahead, these advances make driving easier and more efficient.
However, most marketing dashboard metrics are still being presented in the form of current vs. prior period. That’s helpful in terms of seeing the trend to the current point in time. But, to use the vehicular metaphor, it would be like driving forward while looking in the rear-view mirror — more than a little dangerous.
The metrics on a marketing dashboard highlighting current performance should be compared to a forecast for where they’re supposed to be at that point in time relative to the longer-term goals. That way, the dashboard answers the question, “Where is my projected outcome vs. my target outcome?” Proper marketing dashboard readings give you an indication of whether you’re on the right course, at the right speed, and have enough gas in your tank to get to your desired destination, not just any destination. If the dashboard says you’re off course, you can look at past-performance data for diagnostic insights and ideas on how to course-correct, but no longer will looking back be your central focus (or the focus of countless hours of discussions and justification exercises).
Thursday, December 08, 2005
The potential to be misleading is relevant in that marketing costs must be allocated to the sales they generate before we determine the net incremental profits derived from the marketing investment. If we spend $5 million in marketing to generate $10 million in sales, fine. If the cost of goods sold (COGS, fully loaded with fixed cost allocations) is less than $4 million, we probably made money. But if the COGS is more than $4 million, we’ve delivered slightly better than breakeven on the investment and more likely lost money when taking into account the real or opportunity cost of capital.
Presenting marketing effectiveness metrics in revenue terms is seen as naive by the CFO and other members of the executive committee for very much the same reason as outlined above. Continuing to do so undermines the credibility of the marketing department, particularly when profits, contribution margins, or even gross margins can be approximated.
In my experience, there are several common rationalizations for using revenue metrics, including:
- limited data availability;
- an inability to accurately allocate costs to get from revenue to profit; and/or
- a belief that since others in the organization ultimately determine pricing and fixed and variable costs, marketing is primarily a topline-driving function that does not influence the bottom line.
To the first of these, I empathize. Many companies suffer from legacy sales reporting infrastructures where only the topline numbers are available or updated with a minimum of monthly frequency. If you’re in one of those, we encourage you to use either the last month’s or a 12-month rolling average net or gross margin percentage to apply to revenue. Finance can help you develop reasonable approximations to translate revenues to profits in your predictive metrics. You can always calibrate your approximations later when the actual numbers become available.
If you suffer from the second of these, an inability to allocate costs precisely, consider using “gross margins after marketing” (revenue less COGS less marketing expenses). Most companies know what their gross margins are by product line, and most CFOs are willing to acknowledge that incremental gross margins after marketing that exceed the overhead cost rate of the company are likely generating incremental profits. This is particularly true in companies in which the incremental sales derived from marketing activities are not necessitating capital investments in expanding production or distribution capacity. In short, engage finance in the conversation and collectively work to arrive at a best guess.
If you find yourself in the third group, you need to get your head out of the sand. The reality is that the mission of marketing is to generate incremental profits, not just revenue. If that means working with sales to find out how you need to change customer attitudes, needs, or perceptions to reduce the price elasticity for your products and services, do it. Without effective marketing to create value-added propositions for customers, sales may feel forced to continue to discount to make their goals, leading the entire organization into a slow death spiral — which, ironically, will start with cuts in the marketing budget.
If you identified with this third group, this should be a wake-up call that your real intentions for considering a dashboard are to justify your marketing expenditures, not really measure them for the purpose of improving. If that’s the case, you’re wasting your time. Your CEO and CFO will soon see your true motivation and won’t buy into your thinking anyway.
Having said all that, there are some times when using revenue metrics is highly appropriate. Usually those relate to measurements of share-of-customer spending or share-of-market metrics that relate to the total pie being pursued, not those attempting to measure the financial efficiency or effectiveness of the marketing investment.
In addition, be especially careful with metrics featuring ROI. If ROI is a function of the net change in profit divided by the investment required to achieve it, it can be manipulated by either reducing the investment or overstating the net profit change beyond that directly attributable to the marketing stimulus. Remember that the goal is to increase the net profit by as much as we can, as fast as we can, not just to improve the ROI. That’s just a relative measure of efficiency in our approach, not overall effectiveness.
Wednesday, December 07, 2005
For marketing executives, risk management is a trial-and-error evolution. Has this agency produced good work previously? Will this vendor deliver on time? Experience has fine-tuned our instincts to a point where we intuitively assess risks based upon a combination of hundreds of deliberately and subconsciously collected data points.
Many executive committee members still view marketing as the last bastion of significant risk exposure. Everyone else from finance to operations, HR to IT employs robust risk-assessment tools and processes and highly effective ways to demonstrate the risk-adjusted outcomes of their key projects. They talk in terms of "net present value" of "future returns" associated with an investment made today. They link their recommendations to the bottom line and present their cases in such a way as to reassure not just the CEO, but also their peers, that they have carefully analyzed the financial, operational, organizational, and environmental risks and are proposing the optimal solution with the best likely outcome.
This process needs to be carried into the marketing measurement platform. Each proposed initiative or program should be evaluated not just on its total potential return, but on its risk-adjusted potential.
Here’s an example: Let’s say we’re a retailer planning a holiday sale. We plan to run $1 million of TV advertising to drive traffic into stores during this one-day extravaganza. Using the reach and frequency data we get from our media department, combined with our assessment of the likely impact of the advertising copy, we estimate that about one million incremental customers will visit our stores on that day. If only 5% of them purchase at our average gross-margin per transaction of $20, we break even, right?
Unless, of course, it rains. In that case, our media will reach far more people watching TV inside, but far fewer will venture out to shop. Or maybe the weather will be fine, but one of our competitors will simultaneously announce a major sale event of their own featuring some attractive loss-leaders to entice traffic into their stores. Or maybe there will be some geopolitical news event that disturbs the normal economic optimism of our customers, causing them to cancel or postpone buying plans for a while.
Any or all of these things could happen. It only takes one to completely mess up the projected return on the $1 million investment in sale advertising.
This structured risk-assessment approach will highlight investments that are more prone to external risk factors and modify their rosy expectations accordingly. In the end, high-risk, high-reward initiatives may be just what’s required to achieve business goals, but wouldn’t you rather know that’s what you are approving, instead of finding it out later when high hopes are dashed?
Friday, December 02, 2005
First of all, the fundamental orientation for the process starts off on an "inside/out" track. Middle managers tend (emphasize tend) to have a propensity to view the role of marketing with a bias favoring their personal domain of expertise or responsibility. It's just natural. Sure you can counterbalance by naming a team of managers who will supposedly neutralize each others' biases, but the result is often a recommendation derived primarily through compromise amongst peers whose first consideration is often a need to maintain good working relationships. Worse yet, it may exacerbate the extent to which the measurement challenge is viewed as an internal marketing project, and not a cross-organizational one. Measurement of marketing needs to begin with an understanding of the specific role of marketing within the organization. That's a big task for most CMOs to clarify, never mind hard-working folks who might not have the benefit of the broader perspective.
Second, delegating elevates the chances that the proposed metrics will be heavily weighted towards things that can more likely be accomplished (and measured) within the autonomy scope of the marketing department. Intermediary metrics like awareness or leads generated are accorded greater weight because of the degree of control the recommender perceives they (or the marketing department) have over the outcome. The danger here is of course that these may be the very same "marketing-babble" concepts that frustrate the other members of the executive committee today and undermine the perception that marketing really is adding value.
Third, when measurement is delegated, reality is often a casualty. The more people who review the metrics before they are presented to the CMO, the greater the likelihood they will arrive "polished" in some more-or-less altruistic manner to slightly favor all of the good things that are going on, even if the underlying message is a disturbing one. Again, human nature.
The right role for the CMO in the process is to champion the need for an insightful, objective measurement framework, and then to engage their executive committee peers in framing and reviewing the evolution of it. Further, the CMO needs to ruthlessly screen the proposed metrics to ensure they are focused on the key questions facing the business and not just reflecting the present perspectives or operating capabilities. Finally, the CMO needs to be the lead agent of change, visibly and consistently reinforcing the need for rapid iteration towards the most insightful measures of effectiveness and efficiency, and promoting continuous improvement. In other words, they need to take a personal stake in the measurement framework and tie themselves visibly to it so others will more willingly accept the challenge. There are some very competent, productive people working for the CMO who would love to take this kind of a project on and uncover all the areas for improvement. People who can do a terrific job of building insightful, objective measurement capabilities. But the CMO who delegates too much responsibility for directing the early stages risks undermining both their abilities and their enthusiasm -- not to mention the ultimate credibility of the solution both within and beyond the marketing department.