The future looks bright after cookies are goneAugust 2021
For many brands, Google’s decision to delay the phase-out of third-party cookies in Google Chrome until the end of 2023 due to “mounting industry opposition and the feedback it received when testing possible replacements” means additional time to prepare for this critical change in the company’s capabilities to collect, measure and activate audience data for marketing purposes. It will also give Google some extra time to adjust and develop its technology to deliver alternatives to third-party data.
Preparing for the cookie to crumble
With the end of third-party cookies, companies will need to adjust to limitations associated with their ability to collect, measure and activate data for marketing purposes. There will be less data available, measurement will become more complex and companies will need to adapt to a privacy-centric reality. Within this context, first-party data will play a key role in building capabilities that will be required to replace measurement and activation as we know it.
The future measurement strategy will focus on the following key priorities:
1. first-party data
2. customer experience
3. data source connection
4. predictive analytics and holistic measurement
First-party cookies are at the centre of this new landscape. A first-party cookie is a code that gets generated and is stored on users’ computers by default when they land on a company’s website. This type of cookie helps site owners to improve the user experience by remembering passwords, basic user data and other preferences.
Also, a first-party cookie tells companies what a user did while visiting their website, how often they visit it, and other basic analytics that can help brands develop and automate effective marketing strategies by relying on this data. Unlike third-party cookies, however, we cannot activate user-related data on websites that aren’t associated with the company’s domain, which means retargeting isn’t possible.
In addition to first-party cookies, the ‘unique user’ strategy will play an equally important role in understanding user behaviour in all touchpoints (not only on the website). Many companies that have an online and offline presence should be able to uniquely identify their customers and provide them with a secure, privacy-first identification process anywhere they shop. With the unique user ID comes the need to broaden and further enhance a company’s loyalty program and omnichannel experience, which should ultimately provide value and reward for continued engagement and quality data exchange.
Customer experience (CX) is all about your customer’s perception of their combined experience with various aspects of the brand or business. CX is hugely important because ultimately it may lead to more repeat purchases, recommendations, and in our case, the ability to collect high-quality first-party data. In order for this to happen, customers need to perceive the value they get in return for sharing their personal information.
Therefore, beyond the tech aspects, brands need to think about broadening and enhancing their loyalty programs and the value they are able to add through great (personalized) content, customer service, and user experience on the website, to name just a few. Last but not least, surveys and feedback loops will help brands identify needs and respond accordingly.
Predictive analytics and holistic measurement
Google Analytics 4 already has potent predictive analytics capabilities, which rely on machine learning to provide data-driven insights that help advertisers and businesses predict future user behavior. For instance, churn probability, purchase probability and revenue prediction are all metrics available in GA4, which can be used not only for reporting and insights, but also for generating audience segments for marketing campaigns.
Other tools, such as BigQuery can help create models based on algorithms and data collected from different sources in the organization to predict future purchase behavior of specific customer segments by implementing a scoring system. These models can provide insights for both the business (product development, pricing, distribution,) and marketing – with native connection in Google Analytics 360, we can create audience segments to activate them on DV360 (display and video campaigns).
Moreover, not only because third-party cookies are disappearing, but also because there’s a clear need to better understand the omnichannel user journey so that we can provide excellent user-centric experiences, the approach to measurement needs to be re-evaluated as well. A more holistic approach can combine a mixed media modelling (online, offline channels) with brand measurement (lift, recall, positioning) which can take place on a quarterly basis, in addition to the daily data-driven attribution on GA4.
People, process, then technology
Many organizations, especially the large ones, find it challenging to keep up with technological changes and quickly reach the next levels of digital maturity. For instance, you’d be surprised to realize how many companies still rely on last-click attribution models or how many implement no automation at all. The new reality is yet another opportunity to accelerate the digital transformation process, otherwise risking even further stagnation.
Hopefully this time around, companies will put the focus on building skilled teams that are able to work together with common objectives linked to overall business performance, instead of starting with technology. Tools alone cannot deliver without capable people with clear mandates to implement processes and drive change.
Luckily Google gave advertisers a bit more time to get ready, but it doesn’t mean you should wait.
Illustration: Monika Sroga