Big data, big deal

Fairfax Media data commercial manager, Claire Gibson
By Fairfax Media data commercial manager, Claire Gibson | 27 October 2015
 
Claire Gibson

Marketers have always strived to put customers at the heart of their business decisions. The vast amount of data now available on their customers has made that both easier and more complicated than ever.

Right now, data management platforms (DMPs) allow publishers to aggregate customer information along with online behavioural data in order to tailor product and advertising solutions, creating more personalised experiences for their clients’ target audiences.

With DMPs of their own, brand marketers will now have increasingly sophisticated data collection and targeting capabilities available to them. This opens up new opportunities to study and understand consumer habits outside the brands’ owned environments (e.g. their website).

This hunger for additional audience data and a deeper level of insight is leading marketers and publishers to build partnerships around combining their respective audience segments.

Here are a few examples of how DMP data partnerships can work brilliantly:

Audience Insights. DMP partnerships allow marketers to gain deeper insights into the behaviour of their customers once they leave their site. DMPs deliver detailed information about a customer’s media preferences, consumption, life stage, interests, purchase intent, and information on topics they’re passionate about. These insights can help inform campaign strategy, pinpoint the best topics for native content and develop more accurate audience segments.

Prospecting. DMPs provide audience modelling tools that are only made more effective by the scale and accuracy of data at their disposal. This provides publishers, who have their own first-party data, a real advantage in building accurate models (i.e. look-a-like models) when compared to media partners who only access third-party data segments. Marketers can use the breadth of audience data these models provide to inform their prospective customer strategy.

Campaign efficiency. By accessing a brand’s relevant customer segments, the publisher can enrich campaign performance by excluding current customers for efficiency or layering publisher data to strategically target marketing messages to the identified audience segment.

Integrating native content with a data-driven advertising strategy. Publishers have compelling evidence that this works. For example - Fairfax, in partnership with a key tourism body and travel carrier, have just begun a data driven partnership around native content. By segmenting the audience accessing the native content, and tailoring advertising accordingly, users are encouraged further along the path to purchase. Another travel sector company is concurrently contributing purchase data, so Fairfax is also able to attribute actual behaviour to the campaign. This demonstrates a full end-to-end campaign, from the branding elements of content and sponsorships, right through to the purchase. With access to audience behaviour across the full journey, publishers can optimise campaigns and measure the results accordingly.

Measuring the ‘say-do’ ratio. DMPs are myth-busting by challenging the relevance of offline marketing models for the online world. With the ability to link survey data or transactional data to cookies, marketers can measure the ‘say-do’ ratio; comparing what people say they do versus what people actually do. The findings from these online insights will shift the way marketers think about who their audience is online, and who their target segments could be.

It’s clear that DMPs are a powerful resource for linking a myriad of datasets. Sharing data between trusted partners can create a wealth of opportunities and advantages to those involved. By collaboration through DMPs, publishers and brand marketers will be able to harness direct customer relationships, provide superior customer experiences, and ultimately deliver better campaign results. 

By Fairfax Media data commercial manager, Claire Gibson

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