Propensity modeling and audience engines: how well do you really know your audience?

But today the industry faces some well-documented challenges: the demise of the third-party cookie (a key targeting tool); an increasingly privacy-focused environment; and pressure to address environmental impacts.

Meanwhile, consumers are not always fans of online ads; 44% of UK consumers are often annoyed by them.

Combining these factors with the cost-of-living crisis having a real impact on disposable incomes, it's critical for brands to engage with people in a way that meets their needs, and in doing so helps to win trust.

Tactics for tough times

There's a solution for organizations prepared to invest in truly understanding their target audiences. This might sound obvious, but a downside of digital is the ease with which ‘spray and pray’ tactics can be, and are, adopted).

The consumer (first-party) data that companies amass as part of day-to-day business operations (transactions, registrations, lead generation) holds the key to this solution. All of this data can help a brand to strengthen its understanding of customers and make its marketing campaigns relevant and timely (in other words, interesting) to encourage consumer trust and generate permissions to communicate.

But data on its own, particularly when it comes from disparate and often silo-ed sources, is not enough. Today’s technology needs to be harnessed to collate and manage the huge volumes generated so that it delivers value.

Artificial intelligence-based audience engines are a powerful option: sophisticated tools that enable brands to make intelligent use of their data to facilitate more effective transactions with customers, whether by raising awareness at the top of the advertising funnel, or driving sales at the bottom.

Action specific in-depth audience insight

A brand launching a new marketing program and using an audience engine to ingest and analyze its first-party data can determine what works when it comes to getting the desired action from people by looking at the user journeys across their websites.

Which pages do people start on? How did they get there? Where did they click and go next? How long did they stay on each page? And so on, until they build a complete picture of users' path-to-purchase.

Comparing the journeys of millions of site visitors that have not yet performed the desired action to those of the users that have lets the algorithm split people into hot, warm, and cold prospects.

This is propensity modeling. It removes guesswork from the marketing equation; the combination of data and the audience engine can indicate precisely what works for which people, and who is most likely to perform the desired action.

With insight into users’ intentions and likelihood to purchase, marketers can hyper-target specific audiences that have shown interest, making it highly likely that, with the right creative at the right time, they will engage. Brands that get it right, demonstrating their understanding of consumers and their preferences (and using it to deliver content that is of interest) will build trust. That makes it more likely that communications from them will be welcomed.

An audience engine in action

At Artefact, we're seeing tangible results from this approach. For example, a sexual health brand assumed its core consumers were young males, but purchase data showed that this was only part of the story. That group certainly bought the products, but young females were also major customers – albeit via different path-to-purchase. The latter first engaged with content on the website which included discussions on preventing sexual diseases and unwanted pregnancies.

This finding helped the brand to truly understand its customers, and it showed that within that group there were different audiences, each of which required different messages and content in order to engage.

Analyzing journeys (with data and an audience engine) was a key driver in knowing what makes customers tick, and using that knowledge to deliver what they want.

Insight demonstrates understanding

Even with increasingly precise targeting, today’s consumers are all too often recipients of marketing messages that do not meet their personal criteria.

But targeting people based on the bigger picture – what motivates this audience to engage in the first place – allows brands to show that they have understood their incentives and interests. With this insight they can make better targeting and creative decisions to reach the right audience in the right way, delivering on each consumer’s specific needs.