Since I began this blog in August, I’ve often talked about linking communications tactics to business results. Sounds great, but how do you do it?
Making the link really lies in finding the right measurements, because only measurement tells the marketer if a tactic has succeeded or not. Again, this statement sounds easy, but how can marketers figure out which measurements matter when they typically have more data than they know what to do with?
Turning really huge amounts of data from a coal seam of information to a diamond of insight really requires commitment in terms of executive buy-in, analytics know-how and technology integration. However, most marketers who have some access to data can get a good start on the work with a little elbow grease.
I’ll explain how and give a recent example.
Typically, business objectives involve sales in some way, either in the outright (“grow sales by X% this year”) or by inference (“grow market share”). However, merely knowing how many sales a business made tells the marketer relatively little. The data we want involve those that tell why sales are what they are.
So, my example. Earlier this year, I reviewed quarterly sales results for a telecommunications marketer that divided the data into six regions and three product groups. For the most part, sales had fallen across all products and regions, save one region, which saw huge gains. The client asked me to analyze those data.
A quarterly consumer survey constituted the only data I could lay my hands on at the time. As with the sales data, the survey broke out results over the six regions. It also featured the very useful Net Promoter Score and brand attribute scores, which cover what consumers think of the brand.
I’ll discuss Net Promoter another time, but suffice it to say that it best resembles the “check engine” light on a car dashboard; it generally tells the marketer whether a customer satisfaction problem exists rather than the nature of the problem. Unfortunately, some of the regions had increasing Net Promoter scores even with declining sales, so I had to rule out a correlation between customer satisfaction and sales.
Next, I started to look at the individual brand attribute scores. Specifically, I looked at customer service, a notorious sore point for the telecommunications industry. (If you like your cellular, phone, Internet or TV provider, you don’t have much company.) Once again, however, some regions had increasing customer service scores and declining sales and vice-versa. To make a long story short, the same lack of correlation held true for every other attribute.
In the end, I surmised that regional offers had more to do with sales than anything else, since I knew that my client as well as their competitors often resort to aggressive promotions to drive new customers.
The answer represented something of a let-down; marketers who rely on promotions to drive business find themselves in an expensive proposition. However, this systematic approach allowed me to understand the dynamics of the business better and help me make more relevant suggestions to improving business.
To be fair, this approach takes a willingness to sit down and stare at piles of numbers, something many right-brainers out there may feel loath to do. However, this analysis gives marketers a good read on what really matters to their business.
So I encourage you to go pop the hood on your measurement. Like your car’s engine, it may be a bit dark and sticky, but it can be very powerful.
Making the link really lies in finding the right measurements, because only measurement tells the marketer if a tactic has succeeded or not. Again, this statement sounds easy, but how can marketers figure out which measurements matter when they typically have more data than they know what to do with?
Turning really huge amounts of data from a coal seam of information to a diamond of insight really requires commitment in terms of executive buy-in, analytics know-how and technology integration. However, most marketers who have some access to data can get a good start on the work with a little elbow grease.
I’ll explain how and give a recent example.
Typically, business objectives involve sales in some way, either in the outright (“grow sales by X% this year”) or by inference (“grow market share”). However, merely knowing how many sales a business made tells the marketer relatively little. The data we want involve those that tell why sales are what they are.
So, my example. Earlier this year, I reviewed quarterly sales results for a telecommunications marketer that divided the data into six regions and three product groups. For the most part, sales had fallen across all products and regions, save one region, which saw huge gains. The client asked me to analyze those data.
A quarterly consumer survey constituted the only data I could lay my hands on at the time. As with the sales data, the survey broke out results over the six regions. It also featured the very useful Net Promoter Score and brand attribute scores, which cover what consumers think of the brand.
I’ll discuss Net Promoter another time, but suffice it to say that it best resembles the “check engine” light on a car dashboard; it generally tells the marketer whether a customer satisfaction problem exists rather than the nature of the problem. Unfortunately, some of the regions had increasing Net Promoter scores even with declining sales, so I had to rule out a correlation between customer satisfaction and sales.
Next, I started to look at the individual brand attribute scores. Specifically, I looked at customer service, a notorious sore point for the telecommunications industry. (If you like your cellular, phone, Internet or TV provider, you don’t have much company.) Once again, however, some regions had increasing customer service scores and declining sales and vice-versa. To make a long story short, the same lack of correlation held true for every other attribute.
In the end, I surmised that regional offers had more to do with sales than anything else, since I knew that my client as well as their competitors often resort to aggressive promotions to drive new customers.
The answer represented something of a let-down; marketers who rely on promotions to drive business find themselves in an expensive proposition. However, this systematic approach allowed me to understand the dynamics of the business better and help me make more relevant suggestions to improving business.
To be fair, this approach takes a willingness to sit down and stare at piles of numbers, something many right-brainers out there may feel loath to do. However, this analysis gives marketers a good read on what really matters to their business.
So I encourage you to go pop the hood on your measurement. Like your car’s engine, it may be a bit dark and sticky, but it can be very powerful.
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