Formula for a Successful Tracking Study
According to the last few GRIT reports, tracking studies are in decline. Although this trend has been reported for years, we’re still seeing extremely well-done tracking studies on a regular basis. So this begs the question, “why is there a decline in a proven, viable methodology?”… and more importantly, “what are the characteristics of a “successful” tracking study?” Today we’ll focus more on addressing the latter because I think it will help give us insight into the first question as well.
What makes a “successful” tracking study?
A “successful” tracking study has several characteristics. First and foremost, it’s important that you track the “right things.” Do you want to track brand awareness and key attributes? Or, customer satisfaction and loyalty? Problem resolution outcomes?
It’s important to spend time on the front-end to make sure what you’re measuring is directly correlated to your goals. In other words, make sure the questions you’re asking can actually give you the answers you need.
How do you know the “right things” to track?
A comprehensive benchmark wave can be useful to identify those variables/factors which are most related to the core thing you want to understand. For example, perhaps you have a list of brand attributes you would like to track but your ultimate goal is to align the insights from the tracking study with sales. In the benchmark wave, analysis would focus on understanding which of brand metrics are related to future sales?
Tracking studies become more useful when you can use them on a predictive or prescriptive basis. If you want the tracking study to help identify things you need to be on the lookout for, then you want to identify leading indicators to include in your ongoing tracking program. For example, if you know that certain CSAT measures are a 3-month leading indicator of future sales, then when you start to see a decline in these CSAT measures you take immediate corrective action to minimize the negative impact on future sales. Leading indicators are a way of using tracking studies for predictive purposes.
You can also identify changes you want to make in your “activities” which will impact the key dependent variable – the measure you care most about. Should you change messaging? Your media? Are you tweaking your product or service delivery with the hope that CSAT will improve? To the extent that you can tie your activities to key tracking study measures and ultimately to desired business outcomes, you are building a feedback loop. This is classic stimulus-response – we do “X” and we expect to see “Y.”
Identify specific messages and stories that will impact critical beliefs. What things can you say to move the needle or alter perceptions? Once you know what the critical beliefs are that you need to change, you need to figure out the ‘things to say’ which will help you accomplish that.
How often should you be collecting this data? The timing depends on the “cadence of the business” and on practical realities such as cost and manpower resources. Ideally, you would want to track continuously; but, practically it might be monthly or quarterly. In our experience, annual studies may not give you enough frequency to make the learning very actionable … it’s interesting information, but the feedback is so far removed from actions that you might take that the feedback effect is quite weak.
Why are tracking studies in decline?
It seems like a well-designed and executed tracking study program will provide valuable information that drives action-oriented decisions; which result in improved business outcomes.
So why the decline in tracking studies? Perhaps it’s because there are too many “bad” tracking studies being done. My hunch is that this trend of “bad” tracking studies is tied to the increased use of self-serve, micro- survey platforms. Research has always been a “garbage in, garbage out” process. The success of tracking studies is tied to how well the client (and research company) can align the right questions to the desired business outcomes.
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