The power of propensity: Understanding this measures role in your marketing efforts

Written by Zoé Baillieux on Aug 5, 2019 3:44:33 PM

Almost every marketing leader and expert will tell you that modern marketing is all about measurement. Being able to estimate the ROI of marketing spend by attributing customer actions to tactics has given companies a reason to allocate bigger budgets to marketing each year.

A 2018 report from Kantar, a global media research consultancy, predicted that the measuring tools and methods marketers rely on will evolve rapidly in 2019. While most marketers remain fixated on standard metrics — cost per click or cost per impression, for example — technology is allowing us to incorporate a wide new range of factors into our measurements. Chief among them is consumer propensity.

The term may be familiar, but not everyone fully understands it in this context. In general, propensity refers to the natural tendency of customers to convert without exposure to additional media. Quantifying this tendency is tricky because consumers are constantly exposed to media, but it helps to think in terms of “incrementality.” That is, will spending an extra dollar here drive more conversions?

If you’re spending a lot in a place where customers already are likely to convert (i.e, consumer propensity is high), it’s going to look like that money is well-spent — even though it likely is not. On the flip side, spending in a place where consumers are less likely to convert but are more affected by your media might look like a bad investment on the surface — yet it may not be.

Perspective is critical

Optimising media spend is an ongoing, complex problem for marketers. Because there are many possible ways to spend more efficiently, the key is to pursue constant improvement rather than one perfect solution. To do this, marketers need timely and accurate feedback on their media performance. That's where multitouch attribution comes in, but attribution models are only as valuable as they are accurate.

Marketers ultimately must generate more sales while spending more efficiently — reaching the right consumers in the right place at the right time in the face of ruthless competition and constant change. A major component of this is understanding the momentum of consumers moving toward conversions.

If that momentum is already in the direction of a conversion, why invest more resources into a sale that was likely to happen anyway? If momentum is not working in your favour, you have to consider how your resources can best work to build traction.

When calculating propensity, acknowledge that every person has a natural likelihood to convert — regardless of whether that person is exposed to advertising. If someone is an existing customer, then the propensity to convert is different from that of a prospect. Historical consumer activity (such as previous purchases or website visits) and known consumer factors (geo, activity online) are critical to determining consumer propensity and the true incremental contribution of marketing.

The bottom line? You need to understand the big picture (and work hard to mitigate unconscious biases) if you want measurements to be useful. If you were tracking body weight as a measure of health without also knowing people’s height, for instance, you would make a lot of misinformed judgments. As a data point, consumer propensity provides critical context and puts the rest of your data into perspective. Here are three ways to incorporate it into your measurements:

Factor in your evolving brand equity

Building brand equity typically requires a lot of upfront spend. Once it’s established, you can taper spending while still getting most conversions — but your data may not reveal that.

If you're a new business or in a highly competitive space, you may need to spend a lot to generate interest and awareness; it might also take many years to build that brand equity. Once you establish it, though, you’ll have customers who know your brand and want to buy what you're offering. If you’re still spending heavily on them, you’ll need to make adjustments.

By calculating consumer propensity to make a purchase and incorporating it into your measurement models consistently, you're able to detect when the tides shift. You can then adjust and reallocate your spend according to what's happening currently instead of relying on insight that is a year or two old.

Accept that there are no timeless solutions

Many executives struggle to grasp this fact. In reality, current solutions might not work a year from now — you constantly should be trying to figure out the right solutions, and calculating for propensity is one way to do that. Knowing who's showing up with a high propensity to buy can help you decide whether you're spending ad dollars effectively — you don't want to be wasting limited marketing resources on customers who will be converting regardless.

You do still need to generate interest, and people need to show up with an intent to buy. Understanding the time component of propensity (knowing when customers are likely to buy or when interest tends to subside) will enable you to spend more efficiently.

Don't 'set it and forget it'

It's marketing. You're not mapping the human genome or measuring the force of gravity. You're measuring interest in buying something that you have to sell, which is always changing.

Even if there were a “perfect” solution, hypothetically, it wouldn't stay perfect for very long because of fluctuating variables. No single measurement technique will work for the next five years, which can feel overwhelming — but it shouldn’t. Find a partner firm that can help you develop and implement solutions that will work today but also can evolve for tomorrow.

Markets are always changing, which makes constant measurement critical. Tastes change, preferences change, ads get stale, new competition emerges. Complacency leads to failure. The need to measure your efforts is unlikely to change, but the accuracy of your measurements can increase if you begin to factor in consumer propensity.

 

Article taken from Marketing Tech, written by Brian Baumgart

Topics: Retail, Predictive Marketing, Exclusive interviews

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