The upfronts events in the US are sometimes held up as being an example of how ‘legacy media companies’ go about trading media. However, as Luis Chaves, Managing Director of Marketing Services at Neustar explains here, selling media up front has its place in the modern world and can in fact be enhanced by modern data and analytics.
The upfronts is a series of events that have become a firm fixture in the US TV & video advertising calendar, with the majority of broadcasters hoping to sell the bulk of their ad inventory before the autumn schedules. Major broadcasters screen their top shows for the coming year to secure guaranteed income as brands and agencies line up to sign bumper cheques to secure the TV audiences ahead of time. In the UK, their British counterparts are still playing catch-up when it comes to upfronts, despite some events by the likes of ITV and Channel 4 and the IAB UK’s digital content upfronts.
Whilst some contrast the upfront model with real-time buying, the reality is that technology is also making up front buys even more viable as it allows advertisers to forecast audiences more effectively and to get a better idea of what to expect in terms of ROI.
Similarly, sellers can learn more about their audiences and charge accordingly. Also, the upfront model plays an important role for the TV industry as it frees up broadcasters to invest in content, which is no small thing when a single series of a show like Game of Thrones can cost up to $100 million. Getting the money ahead of time also gives broadcasters the confidence to make bolder creative decisions, so for example they might be able to decide to turn a pilot into a full series.
On the face of it, the nature of these investments made during upfronts events means brands and advertisers are, to a degree, taking a leap of faith against the likely ROI they’ll achieve from buying spots during a programme that won’t air for a number of months.
But in recent years we have also seen some of the leading media companies make moves to mitigate these risks. For example, NBCUniversal offer guarantees on audiences in the same way they once did with Nielsen, but using more granular — and more accurate — data on their audiences. NBCUniversal has committed to sell $1 billion worth of space based on its programming and audience profiles this year, and alongside NBCUniveral’s own data, advertisers can bring their own to the table.
However, in spite of these sell-side assurances, advertisers still need to seriously evaluate how they will gain from making such large and increasingly complex investments. It is at this point in the cycle that marketing analytics and attribution modelling can prove to be powerful tools to help predict ROI. By pulling in data from a range of sources, advertisers and the brands they support are able to gain an understanding of how a range of factors are likely to affect the results of a campaign.
For example, if the investment is for ad spots during a major sporting event, the advertisers can apply the audience data to the scheduling plan for the inventory to give an indication of who will be watching and how long for. Adding other factors, such as political events, the economy or even the climate at that time of year can affect the model and give a better clue of the probable result, even when done months in advance.
Advertisers and brands also need to incorporate internal company factors into their models. Retailers will need to consider their marketing tactics during the Black Friday period based on previous years’ results and that of their competitors and other external factors, as car manufacturers will need to do around the two registration dates in the UK, or telecoms operators that may want to plan for the launch of a major smartphone brand.
Adding such datasets will provide a clearer picture of what the probable outcome of a campaign will be when run against a specific show or time of year, and help the advertiser to make an informed decision whether to invest. Brands in the UK are already making use of these tools, combining the existing upfronts infrastructures with the newer analytics modelling to gain greater value from their campaign spend.
In future the upfronts have real potential to gain new relevance in the industry and help to boost TV ad sales even further by combining the upfronts model with more advanced analytics and audience measurement. Ultimately, all of this will also benefit the consumer, who is served more relevant advertising that matches both their interests and the programming they’re watching.
