Using data modelling to boost audience insight and pinpoint those consumers ready to make a purchase can increase value to advertisers, drive inventory revenue and improve the user experience, says Paul Barnard, Media Director at Sirdata
The rapid advancement and adoption of programmatic technologies has created a digital explosion. However, two key issues need addressing to enable digital publishing to improve revenues and ensure it is a pivotal part of an advertiser’s marketing strategy.
The first is the continued rise of ad blocking and the effect it is having on publishers sustaining and growing revenue. The second is developing premium inventory that reassures advertisers in terms of quality, transparency and performance.
So as a publisher, what more can you do to address these issues? Most of you are continually refining your data and investing in programmatic technology to deliver increasingly personalised and targeted campaigns for your advertisers. And, yes, this does mean that consumers are getting more relevant advertising, but there is an important missing link: intent – are the consumers you are targeting in the right mindset to make a purchase?
Someone who is not ready to buy is unlikely to respond to an ad no matter how relevant it might be in terms of demographic and context. Hitting consumers with a relevant ad at that key moment of intent is the secret ingredient publishers need to add real value to advertisers and deliver a better, more appropriate user experience.
Most publishers create their own first party data by using the services of a data management platform, helping to make sense of their user traffic and segment them into specific audiences. Many then sell this valuable customer data to their advertisers as part of the targeting process. Third party and increasingly second party data also play an important role in this process, often adding reach and helping to fill any gaps in their first party data.
Through building a partnership with a data modelling agency, a publisher can refine their data to be focused on audience intent. A modelling agency will gather huge volumes of data from a plethora of websites and data sources and use its expertise of understanding consumer behaviour to extract individual users based on varying signals of purchase intent.
The modelling technique involves both statistic and semantic analysis algorithms, enabling the transcription of web and mobile users’ browsing patterns to provide clients with a predictive data set of users in the market to purchase a particular product or service.
The process works by semantically scoring both the content and context of a page and turning this information into a binary data point and assigning it an intent value. This page is studied not only in isolation, but also in conjunction with multiple other sources where a particular user is seen, enabling a detailed view of that user’s purchase behaviours and triggers. The data is scored and processed in real-time ensuring the targeting can be applied whilst a user is still active.
This approach is something that brands and ad agencies are now starting to explore and implement throughout their marketing strategies, specifically around customer intent or ‘pre-targeting’ – engaging consumers when they’re about to buy rather than using historical purchase data. Mirroring this approach at supply level is something that will help put a publisher in a better position to capture more from their advertising budget.
The good news is that the publisher/data modelling partnership does not have to be expensive and can be set up as a value exchange if you can find the right data modelling partner that would like access to your first party data. In return for sharing behavioural information, the agency can create custom live intent segments and audiences that publishers can offer to their advertisers.
The result significantly improves a publisher’s premium inventory, ad targeting, overall yield and, just as importantly, the user experience, by delivering advertising that is more relevant and interesting. This approach could play a significant role in improving the overall performance and experience of the digital display ecosystem.
Paul Barnard is Media Director at Sirdata.