DM Data Clinic: Finding new customers without cookies

In the latest in our series of articles, designed to provide advice on data-driven marketing strategies, we look into marketing in a cookieless world.

The Decision Marketing Data Clinic, in association with Sagacity, is open to all companies and organisations big and small. If you have a burning issue which you would like advice on please email us at info@decisionmarketing.co.uk

The loss of third party cookies means that tracking audiences in programmatic is not only a challenge, but the decline in targetable audiences is also resulting in stiffer competition between brands.

Third party cookies have been on the decline for a while, with stricter privacy settings, the growth in privacy-focused browsers, ad blockers and incognito browsing, and changing regulations all taking their toll.

For consumers, this might sound like good news – despite a less personalised browsing experience – but for marketers, brands and agencies it’s becoming increasingly harder to successfully track audiences and measure the outcomes and performance of programmatic campaigns. Likewise, the inability to track user behaviour and journeys across different websites is limiting their ability to deliver personalised ads, in turn leading to lower click through and conversion rates.

Limited data can hinder marketers’ ability to gain valuable insights into customer behaviour and campaign performance. And without precise attribution, measuring ROI for marketing efforts becomes more complex. Walled garden analytics compound this complexity, often resulting in the number of sales claimed from each platform totalling more than the total sales generated on a website.

Strategies for a cookieless world
To address these challenges, marketers, brands and agencies need to adopt alternative strategies that include collecting and leveraging first party data directly from customers. We take a look at three of them below, highlighting the pros and cons of each. We’ll take a look at a further three strategies in a future post.

First party data strategies
Many agencies and advertisers are doubling down on first party data collected directly from customers through owned channels (websites, apps, email); investing in loyalty programs, customer surveys, and interactive content like quizzes to gather valuable insights. This data is becoming the foundation for personalisation and remarketing.

Nike and Starbucks are great examples of brands leveraging their loyalty programs to collect user data, enabling personalised marketing without third party cookies.

Pros:

  • High quality and accurate data as it comes directly from customers
  • Fully compliant with privacy regulations since users opt in
  • Enhances customer loyalty and personalisation

Cons:

  • Data takes time to collect and scale, especially for smaller brands
  • Limited reach compared to third party data
  • Requires robust data infrastructure to manage and use effectively

Data clean rooms
For tech companies and advertisers, clean rooms provide a privacy-safe environment where advertisers can combine their first party data with publishers’ data to find insights and build audience segments. Platforms like Liveramp/Habu, Infosum and Snowflake offer clean room solutions to allow data sharing without exposing sensitive user information. A good example of this would be a large CPG brand using a clean room to match its customer data with a retailer’s sales data to measure campaign effectiveness.  

Pros:

  • Privacy-safe way to share data without exposing PII
  • Enables collaboration between brands and publishers for deeper insights
  • Enhances measurement of campaign effectiveness, especially for walled gardens

Cons:

  • Complex and costly to implement and maintain
  • Requires technical expertise and alignment between partners
  • Limited real-time capabilities due to data processing times

Customer data platform (CDPs)
Brands are increasingly using CDPs to unify first party data across multiple touchpoints, creating a 360-degree view of their customers. Using CDPs like Segment, Tealium and Treasure Data helps brands consolidate customer data for personalised marketing. Airbnb, for example, uses a CDP to centralise customer interactions and deliver personalised experiences.

Pros:

  • Unifies data from multiple sources, creating a 360-degree view of customers
  • Enhances personalisation and customer experience across touchpoints
  • Enables better segmentation and targeting based on real-time data

Cons:

  • High implementation cost and complexity
  • Requires ongoing data management and quality control
  • Needs significant investment in integration and data security

Being able to track the user back to the individual enables a brand to select the audience based on real world knowledge of who they are, and target them specifically. This also makes it possible to see the results – e.g. the number of people that converted – and analyse a campaign’s success and how powerful that marketing channel is.

In the next DM Clinic, we’ll examine three more strategies for negotiating a cookieless world.

Dean Standing is chief revenue officer at Sagacity

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