Cookie Life - Part 2: Targeting without third-party cookie

To follow up on the status quo on cookieless future, we would do our first dive on cookieless targeting as it offers an opportunity to launch very quickly.

We will give here a quick look into what are these targeting options. How to leverage it properly and why contextual is the trendy solution that all media agencies are talking about.

Which targeting relies on what? What is targeting? Which targeting is affected by third-party cookies?

To go back to the status quo article, I mentioned different targeting options currently in use. Let’s clarify which ones will remain alternatives in the future framework.

• SocioDemo: using sociological and/or demographic characteristics to target eg. Age group would be possible via Cohorts / FloC or opt-in data. We will cover it in part 3
• Geolocation: relating to the use of lat-long positioning of the device use, this relies on realtime data that can be deactivated but do not rely on third-party cookie.
• Behavioural: privacy laws also aim at the capacity to follow users from one site to another. So this will be affected by the loss of third-party cookies.
• Time/season based: based on external circumstances- e.g connected to the weather forecast, time of the day, or temperature, it is not affected by cookies.
• Contextual: based on the content of the hosting page, this is not influenced by cookies. 

Why contextual targeting is (once again) cool?

The name is explicit - advertising in context - car insurance presented on a blog presenting car model reviews and comparisons. It is not new, we even used it before the internet existed! Yes, the print channel had Interest titles which was a great opportunity to talk to niche audiences. It is still used for specialized products like hobby groups or sport material aficionados.

It emerged in digital advertising in the same way as an offering to help focus advertising based on interest, digitally, it requires to employ a technology which recognizes index or “read” the content of the page to analyze its content and allocated it to a “context” group.

Google Adsense (created in 2003 thanks to the acquisition of Applied Semantics) is a good example of the usage of contextual advertising solutions based on keyword-indexing. It has its detractors as it also created an enormous volume of sites uniquely design to attract Adsense ads by aggregating some other sites’ content on a topic, not bringing particular quality to the market.

The main benefit of contextual advertising is relevance: there is no need of knowing who the person is if you just need to know what she wishes. It is based on real-time interest instead of past behavioral data analysis. It increases the chance of conversion when approached properly (let’s talk about next) as it focuses on the theme of the content and not the person reading it, It is offering an alternative to all companies which have not started collecting their own customer’s data (let’s talk about that too).

How to leverage the targeting options that are not relying on cookies?

As said, Google pushed back the end of third-party and many marketers sighed with relief. It is just an opportunity to ensure we do not fall behind. There is no time to waste in starting to develop internal knowledge of the most efficient channels for your brand outside of this cookie world.

One essential solution entails allocating a budget for a clear test and learn approach potentially using the SMART framework: Your general objective remains to understand which targeting is the most relevant to create awareness or convert to sales (as both are important to run on a long term focus)

1. Establish hypothesis
2. Determine how you will measure success
3. Define a time and budget limit
4. Assess results
5. Share learning

To make your “test and learn” budget in contextual advertising a success.

• Adapt the creative to a contextual environment, relating to the right topic assignment rather than the consumer-centric approach.
• Monitor closely the performance of each context and associated creative to learn which are the best matches.
• Internal factors can play a role in each activity, do not hesitate to use granular monitoring solutions to deep dive into your results when needed.

For Context

The scalability of the campaign also depends on the quality of the contextual sorting. IAB has released a list of general categories on which website pages can be classified. It offers an opportunity for any publisher to list itself in a category of content, but this is still generic. In contrast, the niche of a context can end up impossible to scale as not enough content will be available.

Good AI leverage Natural Language Processing (NLP) can now determine the sentiment of the pages which reduces the risk of brands being presented against non-relevant or offensive content. It avoids excluding entire categories out of fear of falling against the wrong news (e.g. breaking news section, user-generated content such as reviews and forums). There are good pre-bid solutions now starting to be integrated as part of the brand safety offer of adservers. Check your options.

For other external factors

Build your company knowledge of the influence of external factors by approaching such categories with solid test & learn hypotheses and structure including the creative drawing a clear picture of this option for you. Depending on your service or product, the advertising can be tested on:

• Location
• Weather
• Time of the day
• Period of the year

It is worth paying attention to these factors when running campaigns, it can save you cash by adding an extra relevance layer to your campaigns.

To close

Remaining independent from large providers is a strategic decision to make, whereas it is always possible to choose to rely on a walled garden solution to provide the required data to leverage. No company should feel doomed to adhere to the technological limitations dictated by the market.

Alternative targeting does not rely on third-party cookies can yield great performances once the understanding of the best approach is integrated. As it relies not on consumer-centric data, it requires assimilating a new mechanic and that implies testing. As long as Google offers time for that, there is not a second to waste in starting to build knowledge.

The next stop will be, first-party data collection and leverage, stay tuned.

Sources:

• https://en.wikipedia.org/wiki/Contextual_advertising
• https://iabtechlab.com/standards/content-taxonomy/
• https://digiday.com/media/personalization-diminished-gdpr-era-contextual-targeting-making-comeback/
• https://www.criteo.com/blog/contextual-targeting-campaign-guide/
• https://go.iab.com/rs/786-LBD-533/images/Contextual%20APACIv3.0%20small.pdf
• https://iabtechlab.com/standards/addressability-accountability-privacy/
• https://en.wikipedia.org/wiki/SMART_criteria
• https://www.onlinemarketing-praxis.de/glossar/targeting