The Evolution of Data-Driven Digital Advertising

Cookies are falling apart, but the data apocalypse is far from imminent. Targeting and measurement are not going away, but the processes must evolve. Data and digital advertising will always go hand in hand, resulting in improved ad experiences for businesses and viewers.

Consider Google’s decision to remove third-party cookies as the end of an era that many customers felt disturbing. Now is the time to look for more positive, ethical, and complementary methods to collect and use data to improve advertising and customer interactions.

Trust, Respect, and Consent

Brands must establish a relationship with the consumer, discover how they want to engage and respect their preferences. This is how marketers will start to develop an adjustable first-party data set, which will serve as the foundation for their future targeting and measurement strategy.

The scale will be important, but having identification, first-party data, and consent for each user will be unfeasible and unneeded as the business enters a new era of digital advertising. To retain that trusted relationship with customers, marketers will need to collaborate with publications that share the same values as their users.

Short-term Alternatives to Cookies

Many advertisers will ultimately adopt new targeting and measuring methodologies. There is still scalable inventory with cookies in the medium run, and conventional targeting and measuring ways will coexist alongside more future-proof alternatives. This is an excellent time for marketers to test new targeting and measurement choices when they can be directly compared to tried-and-true strategies and KPIs.

Using this time properly will put buyers in a better position to understand the worth of their investment in a changing world, which may be just a year away. Many publishers and measurement companies are launching new solutions right now. So it is time to test, test, test.

Mid-term solutions

For the majority of customers, relying entirely on deterministic matches across data sets is not an effective approach. Users will grow more aware and protective of their data, and the percentage of users who agree to have their data shared for targeting and measurement with both advertisers and publishers will decline.

The future of measurement will see an upsurge in media mix modeling and multi-touch attribution systems that include representative sample data in their approach. Ideally, digital will continue to distinguish itself from “old school measurement” by offering larger samples and more detailed information about a subset of customers.

In targeting, new solutions are often provided, and some of these will emerge and show the same or improved performance for customers.

Long-term, draw cues from digital audio

Cookies have never been a key source of customer information for audio streaming or podcasting services. However, changes in mobile IDs and consumer privacy expectations have an equal influence. SiriusXM Media is ahead of the curve because it has never depended only on MAIDs for data transmission, giving it a strong, robust identity and first-party data. Consider its approach to audience targeting.

SiriusXM Media has launched a new range of first-party and contextual audience solutions for streaming music. They use classic deterministic audience identification matching to generate a seed audience. These audiences are investigated to expand out to a much bigger audience using probabilistic methods.

SiriusXM Media uses streaming to create a seed audience by combining two lists of identifiers from agreed consumers. The data scientists then delve deeply into the audience’s first-party data (for example, what devices they listen to, what time of day, what content they consume, and so on). They then generate a lookalike audience based only on those first-party data features, erase the seed segment, and give a new first-party audience for targeting streaming inventory. The audiences are then evaluated using a proprietary Soundboard panel to verify a decent degree of accuracy. SiriusXM Media believes this will be a dependable option as the ecosystem evolves.

Similarly, SiriusXM Media collaborates with Comscore to provide a comparable seed audience for podcasts. Comscore creates a thorough map of the material that connects with these consumers by analyzing keywords and surrounding information. From there, SiriusXM uses transcription technology to determine how individual podcast episodes would over-index with desired audience traits, allowing it to target podcast episodes rather than users—a real contextual solution.

Long-term solutions like these will continue to evolve. Whether it’s clean rooms that allow advertisers, publishers, and third-party data providers to securely match audiences or new solutions like UID2 for safely passing audience traits in the bidstream, advertisers should anticipate safer, easier methods to communicate data.

Data-driven digital advertising is here to stay, therefore it’s up to media companies and marketers to stay ahead of the trend.

Source- Adweek