Cookieless attribution: the key to unlocking value in Digital TV advertising  

As penetration levels for Digital TV reach levels of 70% and higher in mature advertising markets the case for TV advertising becomes even stronger. 

But how do brands who have typically focused their efforts on traditional TV advertising make the transition, or supplement their linear existing activity, in an environment where third-party cookies – which have historically had a central role in activating the channel – are going away? 

Here we take a closer look and consider: 

The tipping point in Digital TV advertising is here

It is clear that Digital TV advertising (for Digital ‘read’ OTT, CTV etc) has come of age as a channel for a number of reasons including: 

Digital TV audience reach is now here vs Traditional TV

For many larger brands who have been focused mainly on audience reach – and perhaps less on the cost of customer acquisition – traditional TV advertising has been the ‘go-to’ advertising solution for a number of years now. And Digital TV advertising has, until relatively recently, been the upstart in the industry. Being held back largely by a lack of audience reach relative to its more mature linear TV counterpart. 

However, as Digital TV penetration has increased – according to Statista, just 11% of households owned a Smart TV in 2014, a figure that jumped to 74% in 2023 – so has spend on the channel. In fact, spending on digital TV advertising increased by more than 25% in 2023 alone in the US– with spend projected to double in the UK by 2026.  

Creating a bridge between brand and performance marketing efforts

One of the highly attractive aspects of Digital TV advertising is the way that it is able to blend the promise of extensive reach, and access to a broad audience, with the ability to measure how you audience engages with, and reacts to, specific advertising. 

So, brand meets performance marketing in a sense.

Without dipping into too much detail, Digital TV advertising has several attractions over traditional TV advertising. Including the ability to deliver more precise targeting, increased interactivity with ads, creative flexibility and a move to time-shifted viewing which prolongs the shelf-life of ads. 

The cost vs reach calculation makes sense too

However, one of the biggest drivers for brands who are coming under increasing cost pressure is the improved cost-to-reach ratio that Digital TV now offers. For many, it offers the potential to double their effective reach by moving to digital at current spend levels – with CPMs for Digital often being half of those for traditional linear TV placements. 

The challenge for these brands is how to achieve that move, with digital TV typically being activated by third-party data gleaned from cookies. For many of them, the promise of the right ad, in the right place to the right person that programmatic advertising was supposed to deliver never came to fruition – so they haven’t invested heavily in the backend infrastructure that was needed to manage third-party data at scale. 

And as third-party cookies are finally removed from the Chrome browser in mid to late 2024, marketers need a new approach to ensure they are able to make the very best of the opportunity that Digital TV now presents. 

As cookies go away effective attribution is key 

Google’s decision to end the use of third-party cookies has a huge amount of relevance here. While everyone is saying that cookies will be going away by the middle of 2024, the reality is that they are going now, with Google announcing it had begun to switch off cookies for 30 million users in January 2024.

Here are some of the key reasons this matters as you look to optimise spend in the Digital TV channel. 

As third-party cookies go so does the data associated with them 

Much of the focus of the discussion about the removal of third-party cookies has been largely technical around the practical aspects of how advertising will be targeted and ‘delivered on the ground’.

However, one of the big side effects of the removal of cookies is that all of the data they collected previously – which was then used to activate channels like Digital TV – is going away too. Along with all of the profiling and targeting capabilities they offer. 

This has a number of key implications for advertisers looking to make the most of the Digital TV opportunity right now: 

  • For brands that have invested in the promise of programmatic, building up costly tech stacks to manage complex third-party data and following a strategy that is largely CPM-based, the removal of cookies is fairly seismic. Leaving them with large chunks of their tech stack that are redundant as cookies are removed and with the need to find an alternative way to track and measure the success of their Digital TV and other ads
  • And for brands that haven’t invested as heavily in programmatic – potentially some of the larger brands who were focused on traditional TV and want to make the jump to Digital TV now – there needs to be a way to measure the effectiveness of their Digital TV efforts

Before we go on to look at their options it is worth a quick detour here to point out that cookies have done a pretty poor job of tracking cross-device, multi-channel journeys as shown in the diagram below.

The problem is that cookie-based solutions like GA (in this case) and Adobe have a limited and broken view of the customer journey when compared to AI driven solutions like our own Corvidae platform. More on that later. 

The re-emergence of contextual advertising as a strategy

Stepping outside of our analysis of Digital TV quickly, there are broader strategic changes in play here. For example, one of the clear side effects of the removal of third-party cookies is an increasing focus on Contextual advertising as a strategy. 

Contextual isn’t new – it has been around for years – but in a world where cookies go away, it makes a lot of sense and many of the world’s largest brands are moving in this direction. It is all about ad relevancy.

So, forget the focus on managing huge amounts of third-party data for targeting and measurement. Simply profile the types of places you want your ads seen – including on Digital TV – using 1st party data to inform your choices and a whitelist policy for where your ads should be shown.

And dispense with the need for costly right person, right time targeting and simply show all of your ads, to all of the people all of the time. But also ensuring you have highly effective, non-cookie-based attribution in place that enables you to accurately assess the impact of your activity at a channel and individual creative level. 

For advertisers looking to isolate the true impact of their Digital TV advertising accurately in a cookieless world – in a non-siloed way that removes erroneous double-counting and over-attribution across channels – it makes absolute sense.

It also allows you to strip out all of the cost associated with managing third-party cookie data and replace it with AI-driven attribution for effective measurement.  

How AI-driven, unified attribution works in a cookieless world

 Unlike standard measurement tools – which rely on cookies and result in broken customer journeys which favour lower funnel touchpoints for conversion (over more valuable middle and higher funnel touchpoints) – AI-driven attribution can effectively rebuild and unify your broken customer journey data, across disparate data silos on and offline.  

Creating complete customer journeys and attributing value across every touchpoint based on the chance of conversion. This not only enables marketers to isolate which campaigns are contributing to conversion and revenue right across the customer journey – but, more importantly, which creative is working. 

This is powerful when combined with the type of Contextual strategy outlined above – and also for marketers looking to isolate the impact of Digital TV advertising in a cookieless world. 

Assessing the impact of TV advertising for a German television shopping company using Corvidae

 It is this AI-driven attribution approach which we used to help a German shopping channel to assess the true impact of its TV advertising. 

TV is a very valuable acquisition and conversion channel for the company and they were aware that a combination of TV and digital channels was influencing their customer journey. However, they wanted to: 

  • have more clarity on the degree of impact that respective channels were having
  • confirm the extent to which TV advertising was driving online sales
  • define the length of time that an ad continued to influence a customer to buy after it had aired (the relative decay curve)

The first part of the process with the company was to use our Corvidae solution to reattribute their analytics data – which included replacing an existing ‘Last Click’ attribution model with a new and improved cookieless model. Which could be applied to customer journeys that were 3 times longer than before. 

We then compared the sales of products whilst the shopping channel was on air, to Corvidae attributed sales data to see what incremental uplift there was during, and after, the ads were shown. This was then built into the overall attribution model.

This near-live, accurate and granular unified measurement across offline and online marketing activity identified that: 

  • up to 40% of all revenue was a direct result of a TV placement, and only 60% should be attributed to digital channels
  • approximately 50% of sales in the week following a TV placement were a direct result of that placement, falling to 10% the following week
  • certain products on air continued to influence online sales up to 3 weeks after the ad was shown. A far slower relative decay curve than had previously been predicted by the team

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How Will The Removal of Cookies Impact Marketing?