The executives in any company are interested in whether the online/mobile efforts are translating into profitable revenue for the company. They aren’t really interested in the number of people coming to a site or using an app or subscribing to the service. So how do you provide your senior management with the rolled up data that they need to prove the value of your efforts?
I’m reminded of a time years ago when I was responsible for doing performance testing of my then employer’s Telco grade mail server. The mail server provided ongoing metrics in terms of number of subscribers, message delivery, user behaviour, and mail relay throughput. This information was used by operators (customers) on the current use of the system. The performance testing was different; it was an internal activity with the purpose of providing sizing information for capacity planning guidance for our customers. The same metric information was used as criteria for measurements, the intent and design of the experiment is what was different. I used to liken the difference between these two activities, as the first being similar to a journalist who has to provide an unbiased article and the second to an editor that provides an opinion piece.
How does this story translate to what we are trying to do in terms of measuring the value of our online/mobile marketing efforts? I would like to suggest that most people, who are doing what they consider as analytics, are doing the first type of exercise. Collecting site metrics to provide information on what is actually operational statistics. The C-suite is looking for the second type of exercise, measurements that provide information on the performance of the business as well as provide indicators on possible future growth. For me this is the difference between metrics and analytics.
To produce this more relevant type of report we need to consider the following:
Define what it is you want to measure
The C-suite is the best source for what you want to measure. Whether you ask your senior management right out from day one, or provide them with something and then adjust according to their reaction to it, may depend on your relationship with them. These questions are both your starting and end points. They are what you are looking for when you design your analysis and the answers will be the meat of your final report.
Some examples are:
- How many converted leads did we achieve last month? What was the marketing cost per converted lead?
- How long does it take to convert a visitor to a lead?
- Is the freemium model transitioning leads into paying subscribers?
Look at current metrics collection as a source of information
You are likely collecting the raw data that can feed into these conclusions, or using a marketing automation tool that is doing it for you. In fact, for me the rawer the data is the more likely you will be able to interpret it. A key point in analysing metrics is to look at the data over time, rather than counts. Knowing how many unique visitors you had visit your site last month will not provide you with the answer to the “how long does it take to convert a visitor to a lead” question. Tracking some of those unique visitors, recording the time of their first visit and the time of their purchase, will provide an average time for conversion. For example, you could glean the above information by post-processing a log of time-stamped subscriber actions that include sign-up, visits, and purchases. This is something that marketing automation tools, like Eloqua (Oracle), do when scoring leads.
If the data you are collecting doesn’t support the questions you are asking then change what you are collecting – don’t change the questions.
Present the report as an Executive summary of results
Executives don’t want to troll through pages of information. Design your report to present your conclusions. Sometimes, I think that we are afraid to do this because it both starkly shows our failures as well as our successes. You may be surprised that management is open to discussing failures, if it is clear what you will change in the future given that information.
By all means, have your supporting data at hand. The second tier management team is likely going to want to see it. And the operational teams may want the raw details to see how things are working. The C-Suite won’t have the time.
In Conclusion
We likely are collecting the raw information that we need to provide this type of interpretation, though most people in the trenches don’t see that. We don’t have to re-engineer our metrics collection. What we need to do is to clarify the intent of the collection, design how we interpret the data and present results in a manner suitable for a C-suite audience.
