In the latest in our series of articles, designed to provide advice on data-driven marketing strategies, we once again look into marketing without cookies.
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In the first article, we examined the challenges that marketers, brands and agencies are facing tracking audiences in programmatic advertising and explained three ways in which they can overcome the deprecation of third party cookies. Here are three further strategies:
Identity solutions and unified IDs
There’s a growing focus on identity resolution – a solution that tech companies and agencies can use to determine identifiers like email addresses or phone numbers (with user consent) to track users across platforms. Solutions like LiveRamp’s RampID and Epsilon’s CORE ID allow advertisers to connect users across channels while respecting privacy. The Trade Desk’s Unified ID 2.0, for example, is an open-source initiative designed to replace third party cookies by using encrypted email addresses, which users can opt in to.
Pros:
- Provides a viable replacement for third party cookies for cross-channel tracking
- Enhances targeting accuracy and personalisation while maintaining user privacy
- Helps in tracking users across devices and platforms
Cons:
- Dependent on user opt-in and consent for data collection
- Can be difficult to scale if users are hesitant to share email addresses
- Risk of regulatory scrutiny if not managed properly
Contextual targeting
Contextual targeting enables agencies and advertisers to use the content of a webpage to determine which ads to show, rather than relying on user behaviour and their past browsing behaviour. AI-powered tools analyse the content of a page in real time to ensure ads are placed in relevant contexts, driving engagement without needing personal identifiers.
Companies like GumGum and Oracle’s Grapeshot specialise in AI-based contextual advertising to deliver ads based on the context of the content rather than user data.
Pros:
- Privacy compliant as it does not rely on user tracking
- Works well in cookieless environments and across browsers
- Scalable across channels and publishers
Cons:
- Less precise than behavioural targeting for personalised ads
- May not capture nuanced user intent as effectively
- Requires sophisticated AI tools to analyse content accurately
Alternative attribution models
As cookie-based attribution declines, companies are turning to incrementality testing, media mix modelling, and AI-driven attribution to measure campaign performance. By combining offline and online data, brands can better understand the true impact of their marketing efforts, and we’ve seen ecommerce retailers using tools like Nielsen Attribution to measure the incremental impact of their digital campaigns.
Pros:
- Provides more accurate measurement of marketing effectiveness without relying on cookies
- Helps in optimising budget allocation across channels
- Suitable for both online and offline channels
Cons:
- Requires historical data and sophisticated analytics to be effective
- Can be time consuming and resource intensive to set up
- Attribution results may be less granular than cookie-based tracking
As we’ve explored over the past two articles, forward-thinking brands and agencies have been busy developing their own cookieless solutions or working with data and technology partners to help their clients.
Implementing a cookieless solution in programmatic advertising activities not only allows marketers, brands and agencies to better measure the performance of a campaign, it’s also future proof. This kind of solution puts the individual first – offering targeted advertising while respecting user privacy.
Dean Standing is chief revenue officer at Sagacity
