One of the great advantages of programmatic is access to audience data.
On top of the first-party data a business might hold, there is an enormous supply of third-party data that can be added to enhance targeting. Despite this, a CIM report this year found that 50% of all marketing is deemed ‘irrelevant’ by the audience it reaches.
Clearly, advertisers and media agencies are still struggling to make the most out of audience data. With this in mind, I would like to share Brainlabs’ approach to using audience data effectively, along with some real examples of insights based on data from programmatic campaigns.
How to use data to improve targeting
Analysing data accurately is a skill in itself, requiring creativity and a methodical approach.
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 and third-party audiences – to further enhance targeting.
2. Analyse the results
The audiences you initially target are very rarely the most high performing. With a DSP (demand side platform) 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 behaviour, demographics – you can identify the most suitable for your campaign.
3. Test and test again
It’s true that data can be misleading, which is why you need to apply a certain scientific rigour 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, 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.
Current DSPs make the practical aspect of this easy. The difficulty lies in gaining the assent of the marketing team. There is a lack of faith in the insights of data analysis because it is often counter-intuitive, 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 here in the name of greater relevance, and of course greater performance.
Insights from programmatic
Programmatic is leading the way in terms of access to data, and having platforms that enable continual analysis and adaptation.
We had a finance client, for example, that was sure its audience were millennials with relatively low or modest incomes. Yet the data revealed that one of their highest performing audiences were actually people who were interested in high-end cars – very different to the type of person they expected.
A retail client believed their product appealed equally to both genders, but the evidence showed a considerable difference in favour of women. Based on this they adapted their previously unisex creatives to be aimed at women, and saw a major uplift in conversions.
Sometimes data tells marketers things they simply wouldn’t have considered. A client of ours learned that serving ads on the first two weekdays of the month had a massive positive impact on CPA. Another client learned their best performing audience were people living in semi-detached houses in the north of England, for which there wasn’t really any logical explanation. Still, by building this audience into their targeting, there was a massive uplift in conversions.
Not all data insights lead to recommended strategy change. If art lovers happen to also love hot desserts, this doesn’t necessarily mean you should target for this – it could be more a reflection of their interest in Jamie Oliver, a characteristic anyone who has run programmatic campaigns before will know is pretty much true for any audience – don’t know why, but everyone seems to love that guy.
The value of data
Audience data does not only enhance targeting, but can be used to build up an understanding of the digital identity of a brand’s target audience. As the quality of third-party data improves – especially following the implementation of the GDPR (General Data Protection Regulation) next year – applying a methodical approach to data will help advertisers to ensure relevance, and to inform their entire marketing strategy.