In Part 1 of this series, we explored -The new future without third-party cookies, Clean Rooms, and Walled Gardens.
In this part, we deep dive into:
- The Core Pillars of Consumer Data
- Where to from here? How to navigate your way in the post cookie world
The Core Pillars of Consumer Data
Let's have a look at the new pillars of a post cookie world that hold the key to targeting, measurement and attribution throughout the digital ecosystem:
1. First-Party (1PD):
This information is collected directly from consumers, which is then leveraged to provide a personalised advertising and content experience. The importance of 1PD, is now more emphasised than before as brands are encouraged to understand their target audience in even greater detail to futureproof their marketing strategies.
The landscape is changing, especially when it comes to privacy and web safety, and with that, consumers are holding a lot more power when it comes to sharing their information - and who they share it with.
While first-party data is the most accurate and least expensive type of data to leverage for paid digital media, it requires explicit consent during information collection to continue utilising it. With the shift from third-party to 1PD, the content delivered will have to be even more engaging if brands expect users to opt-in. (Read more about our First-Party Data Strategy)
2. Second-Party (2PD):
This information is collected by an external company, directly from their own user base - also known as "platform data". Advertisers can then purchase and access these segments to strengthen their 1PD for deeper insights and increased sales.
Google, Facebook, Amazon and the likes are one of the largest 2PD sources, with easy to access segments, ready made within their respective ad platforms.
3. Third-Party (3PD):
This information is acquired from companies that aggregate data from other sources, who don't have direct relationships with the user (such as publicly available sources of information, registration data) and are licensed for use by advertisers.
Despite it providing the most scale, advertisers only get limited visibility into data collection practices and quality, as this data cannot be tracked back to individual users. Moreover, it can be expensive as advertisers have to pay a CPM to use this data for activation.
4. Contextual Targeting:
Contextual targeting is where brands take the content of the web page into consideration and display ads – which is typically segmented based on keywords or topics.
This helps brands to avoid showing their ads alongside undesirable content. With the 3PD & cookies being phased out, we expect to see contextual targeting have a renaissance, with curation of content coming into greater focus.
With the machine learning sophistication and use of Natural Language Processing (NLP), it has allowed brands to have a deeper grasp of the context and sentiment of every webpage. This is achieved through various techniques such as deep text and image analysis, use of 1PD for building media look-a-likes, crawlers, real-time creative optimisation,
5. Proximity Targeting:
We expect a shift in the amount of proximity data that advertisers can access, as well as the accuracy as mobile providers opt to enhance their privacy settings – another recent example from Apple allowing location settings to be measured approximately.
Many location providers collect location coordinates from third-party applications on mobiles, with little to no knowledge from the user that were/are being tracked. The walled gardens are set to benefit from this change, as they have a clear value exchange to the end-user in supplying location data, such as the use of Google Maps, which in turn will opt them into providing ads based on geolocation.
6. FloC – Privacy Sandbox:
As we see the industry move away from the concept of 1 to 1 marketing, the use of modelling and profiling groups of aggregated users has become more common. These solutions are not new, with look-a-like modelling previously being used to help deliver incremental audiences and reach, however they are being evolved, with scrutiny focussed on their accuracy and performance as a core component of a targeting method.
Google's solution on audience profiling, as outlined above, is called FloC (Federated Learning of Cohorts). FloC uses an algorithm that monitors the sites visited within the Chrome browser and models groups of these users, with the ability to model and run 1st party data against them. This is similar to Facebook's "interest-based" or "user profiling" methodology.
Where to from here?
As the digital world moves away from having accessible unique identifiers, whether this is in the form of a cookie, device ID or using graph technology, we will see a shift away from one-to-one addressability. Instead, the advertising world will be based on modelled data and look-a-like audience segments - aggregating users into larger cohorts.
To future-proof your digital strategy, advertisers should explore;
- Contextual targeting is one of the handful solutions that businesses must test to prepare for the new future of digital targeting.
- Prioritise first party data: 3rd party data brokers will continue to decline as the commercial models become exposed to legal risk of privacy concerns, making the ownership of 1st party data more critical than ever.
- Explore channel personalisation : identifying users as they engage with you can help drive better experiences, and revenue. Leveraging data from your own first party lists, and matching with observed identity signals through a database or identify graph, to customise the experience according to the end user.
- Update to Google Analytics 4 (GA4): if you are currently using Google Analytics, we recommend upgrading it to GA4 by the end of 2021. GA4 goes a long way to help combat the potential loss of cookie data by using multiple identity spaces to recognise users across environments. Here are some of the benefits of upgrading to GA4 (Resolution Digital can help assist with this transition. Please reach out to your account manager or contact us)
- Review your measurement approach: new privacy laws will continue to introduce restrictions on how an activity is tracked and measured, limiting the amount of data points directly available to use in marketing, meaning a holistic view of performance is crucial to success.
Deploying some tried and tested measurement techniques, such as media and marketing mix modelling, can serve to replace cookie-based attribution or randomised yet controlled (A/B/n multivariate) testing model.
The advertising and marketing industry is in the midst of massive change, and it requires businesses to evolve, adapt and develop long term strategies to continue to drive growth and revenue.
While these steps are imperative for your business to keep up with this ever-evolving digital world and ready for the cookie-less future, they can be a bit overwhelming. We are here to help you navigate and understand the challenges that are unique to your organisation. Contact us to learn more.