Programmatic has created the opportunity for truly data-driven marketing. Yet still, 50 percent of all marketing is irrelevant to the consumer, according to the latest Chartered Institute of Marketing report. Why?
There are two main reasons: ineffective campaign management and a general reluctance to adapt marketing strategies according to data. Marketers need to be more willing to listen to audience data, and agencies need to get better at translating it into actionable insights.
For the agency running the campaign, there is a logical process for optimizing targeting, which any decent DSP (demand-side platform) should enable you to do.
1. Start with what you’ve got
On top of whatever first-party data you have, you can add audiences from third-party data providers, selected according to the characteristics you might expect your customers to possess. DoubleClick allows you to also perform an audience composition report — which works out the match ratio between first-party data with third-party audiences — to further enhance targeting.
The audiences you initially target for are very rarely the most high-performing. With a DSP such as DoubleClick, you’re able to create an audience performance report, which compares the targeted audiences with the ones you actually reached.
Based on the millions of targeting options — in the market for, interests, recent browsing behavior, demographics — you can identify the most suitable for your campaign.
It’s true that data can be misleading, which is why you need to apply a certain scientific rigor to how you use it. All the targeting types at your disposal — audience, keyword, category, website — can feed into each other, until you find the optimal targeting options.
Thousands of different targeting strategies can be A/B tested rapidly using automation tools, and the reliability of data can be measured according to its performance. By the end, there should be a high degree of certainty in the efficacy of the new targeting strategy.
4. Adapt Current DSPs make the practical aspect of this easy. The difficulty lies in gaining the assent of the marketing team.
There’s often a lack of faith in the insights of data analysis because it can be counterintuitive, or at least contradictory, to the convictions of the brand. But so long as there is trust in the agency running the campaign, marketers ought to take a leap of faith in the name of greater relevance, and of course, greater performance.
A well-managed programmatic campaign should help a brand know its customers well beyond its original understanding. The insights gained also can be used to shape a brand’s marketing strategy, so long as marketers are willing to act upon them.
With a financial services client, for example, we identified that the most likely time for customers to search for a loan was during the first two weekdays of the month, which led to an obvious, highly productive change in their marketing strategy.
With another client in the same sector, targeting ads to commuters drove a much higher performance. Insights from the data led our client to design ads, related to contactless card payments on the tube, personalized for commuters. We also found their customers tended to be interested in high-end cars, which was contrary to their expectation of a younger, less wealthy audience.
A retail client learned that women were more likely to buy their product, having previously used gender-neutral creatives. By adapting their ads to appeal specifically to women, the client saw a major uplift in conversions.
With another client, cross-device analysis demonstrated that many desktop conversions began with a mobile search. (Originally they were only able to see conversions, rather than the device paths that led to a conversion.) This encouraged them to invest more in mobile optimization.
We learned that another client’s best-performing audience tended to live in semi-detached houses in the north of England. By adding these audiences into the campaign, our client saw lower CPA (cost per acquisition) and a major uplift in conversions.
Data provides insights that marketers cannot predict, and often wouldn’t even think to research.
No one can hope to fully understand their audience, or to ensure 100 percent relevance, but we can at least get much closer to it than that ever before — so long as we are all willing to use data to its fullest capacity.
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