The advent of programmatic has allowed marketers to leverage their own first-party data to execute smarter buying strategies, activate offline data for cross device targeting and even build new business models.
It is an interesting time for a lot of marketers – particularly those with intent-based data.
What should they do with it? How should they be using it? What additional revenue streams could they generate by using data for third-party targeting?
Let’s look at the example of Ryanair: it has a site that has 60 million+ visitors per month across Europe. The site’s main objective is to sell airline tickets. It runs some ads on its pages, but has yet to dip its toe into programmatic market.
Ryanair has arguably more data signals on traveller intent in Europe (outside of Google, of course) than any other source. Why isn’t it looking at leveraging this data to build new revenue models? How would it even go about it?
Let’s examine the test case for a Ryanair monetisation model:
A DSP and data management strategy?
As its new CMO (yes, O’Leary came in big for me) I understand Ryanair has lots of data; but how do we make sense of all this data? What do I do with it all? If we are to build out this monetisation model, a DMP is required to help segment our intenders.
It doesn’t need to combine any offline (CRM) and online data – yet. A DMP ‘lite’ will be sufficient for the moment
The other thing that will need to be considered is the actual model. Are we looking to use our intent data to power a managed programmatic buy (that would be an IO) on behalf of travel brands – hotels, travel insurance, car rental etc?
If the agencies push back managed buys, can we white label a DSP to enable self-service travel-focused buys? Do we have enough scale to do it?
Regardless of the situation, we are going to need a DSP to buy O&O and third-party inventory.
In the video below, we talk to Dave Reed, managing director, EMEA, about how MediaMath works with advertiser clients with Rakuten and others to leverage third-party data to build out new business models.
In the special ‘Road To ATS London’ TraderTalk we also talk about how advertisers and agencies are looking to onboard offline data to maximise the impact of their online marketing.
Reed discusses how advertisers can restrict commercial cannibalisation. Remember, the Ryanair (our test case in this specific example) objective is to sell airline tickets.
Minimising this should also be an important consideration when deploying the data strategy.
Check lists for advertisers around commercialisation
While the path to executing this strategy looks fairly straight forward for advertisers, it might be useful considering the following key points:
— Is the market big enough for a verticalised data play to justify the investment and resource?
— Is there enough data to scale the opportunity?
— Do you have the internal skill set to make it work?
— The tech stack – build or borrow?
— Does the additional revenue run the risk of cannibalising the core business?
Brands seem keen. MoneySuperMarket, for instance, has made programmatic a key part of its customer acquisition and monetisation strategy. It has taken many years to perfect its model –but only after investing considerable time, investment, and resource.
How many brands will afford an outlier project like this the same consideration?
The opportunity remains significant, nonetheless. Can brands with significant intent-laden data make it work?
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