By: John Moran, MSA Analytics COE Leader and VP Analytic Strategy & Insights
For our household, this time of year is special as we prepare for our school’s annual Father-Daughter dance. Enjoyed by our elementary school-age daughters and lumbering dads alike, despite our customary complaint of progressively declining range of motion.
Looking about the room, studying the happy faces of the whirling kids, I was struck by the importance of the event. We strive to be there for our daughters; amidst the many demands placed on us and the little time we have with them. It is often through unique occasions like the dance that we dads get to know our kids more deeply, and make our impact.
Analyzing customers is a lot like this. 3 principles come to mind.
1. Unique insights often come out of special events or situations
Sure, we study customers all the time, reporting on their purchases, assessing the impact of new pricing, segmenting on brand usage, predicting new product uptake. That’s what I’d call seeing them through an ordinary day-to-day lens.
But when was the last time we really got to know them through less common circumstances – seeing their behavior in a new light as they respond to different decision situations and influences?
We do this by spending quality analytic time with cohorts of customers as they encounter new shopping environments and brand decision stimuli.
It's in these unique occasions that we learn so much more about their true beliefs and decision-making criteria as consumers of a category. Insights derived from a wide range of cross-situational observations hold the key to creating lasting brand equity and life time value.
For example, what if we could observe the change in behavior of a particular cohort of brand users – say those who frequently switch brands but are loyal to a particular retailer or channel – toward a planogram change supported with in-store promotion? These kinds of insights could help us take action to target (or optimize) retail environments and shelf sets for improved trial or repeat purchase.
Studying shopper behavior in different purchase environments and competitive circumstances reveal their changing needs, preferences and loyalties, pointing to new actions for engaging them.
- 2. More inputs don’t necessarily produce a better outcome, and can distract from the true purpose
The running joke between my daughter and me is how high the bar will go each year for making the dance the best ever. In years past it was a tux, a dozen roses as a corsage, practicing moves beforehand...This year we kept it simple. And had just as good a time (improving ROI).
In the business world, We live in a big data era. We’re bombarded with new sources of data, new technology to better integrate data, and emerging analytics tools to speed insights. Certainly big data analytics is opening new frontiers to insights about customers, but it is not always true that more data ensures more insights. It’s about having the right data for the right business question.
If we stay focused on answering the core business question, getting there can be surprisingly resource efficient. Too often we get distracted by what can ride along. Like adding related business questions that are better left for a different analysis.
For example, “Which stores are most likely to increase unit growth from our new trade program?”
starts out as the primary endpoint for a predictive study design, and key input to field deployment. But as internal teams seek supporting insights, the study evolves to a general store segmentation, which trades off some predictive insights for broader observations. We must help our business partners get full value from analytics by staying true to the essence of the analysis, with a mind toward resource management. Each analysis has a high opportunity cost.
- 3. Behavior isn’t static, so understanding the drivers of behavior can help us take more effective action
This year, amidst the requisite play list of “Dancing Queen”, “Y.M.C.A”, and “Dancing on the Ceiling” I was surprised to hear Joni Mitchell’s classic folk song, “Both Sides Now”. It is a beautiful song that considers clouds, love, and life from different perspectives. Through different experiences, what was once believed becomes less certain, making the subjects seem situational and random, and resignedly, unpredictable.
How apropos for our world of brand investment, where overly optimistic and one-sided views of a brand can at times win support in growth-challenged organizations.
To effectively build brands that last, we must know consumer behavior during the ups and downs of the business cycle. We like to think of brands (and our children) as having predictable, steady growth rates until they reach maturity. Predictable growth makes for easier forecasting and planning, and adds some certainty to scenario-based decision-making.
But brands grow in fits and spurts, like kids (some adults, too). They develop opportunistically and situationally, through a wide range of positive and negative consumer, competitor, and market conditions. When these conditions are supportive of the brand’s positioning and target experience, the right investments create synergies in consumer response, accelerating growth beyond a forecast.
We see this today in categories as diverse as autos, tobacco, and prescription drugs. Think of this as wind at your back, and the right tack can realize more of this force. An example of synergistic investment is deploying a program which improves on-shelf availability in retail locations preferred by a brand’s target consumers.
The flip side is making investment choices that are not aligned to evolving performance drivers. As consumer behavior changes during less favorable market conditions, we risk being out of step. Brand growth slows and profitability declines, and we often underperform forecast or expectations.
With marketing-mix modeling gaining as an evidenced-based decision tool, its emphasis on shorter-term promotion impact requires us to incorporate a longer term view of consumer behavior through varied market conditions.
Think about your category’s elasticity – going beyond your brands – with respect to economic and other overarching environmental factors. Model behavior during periods of varying levels of consumption and sentiments. What impacts the category positively and negatively? This requires a longer term view and historical data of course, but the insights produced are predictive of future situations.
Factors such as price gaps to substitutes, e-commerce trending, gas prices, and seasonality are some examples of factors to model for understanding impact on categories. Market leaders use these types of conditions to get new views of consumer behavior to plan future engagement strategies.
Lastly, seek to identify events and circumstances that are positive and negative to the brand given the brand’s positioning / experience. Market conditions can effect brands in a category differently. A headwind for some is opportunity for others, if the right investment choices are made that align with changing consumer behavior and brand response.
Use these insights as supplemental input to decision making, giving important counter balance to the short term focus of marketing mix model ROIs and contributions.
Time spent with someone special, doing something special, can’t help but have a lasting impact. The insights we gain about customers and daughters in all sorts of situations – both positive and negative – give us guidance for supporting, communicating, and encouraging the right actions that produce great outcomes.