Use AI to segment and activate audiences in a Customer Data Platform

As the technical and regulatory environment around collecting and processing personal data changes, companies are finding it increasingly difficult to precisely target and measure their audiences. To reach their audiences accurately and optimize their media budgets, brands should review their data strategies.

There is no need to worry because there is a proven solution: the implementation of an AI-based Marketing Engine in a custom-build CDP on Google Cloud Platform.

You can use first-party data to its full potential using this flexible solution, in accordance with regulations. By adopting MLOps for managed activation across all owned, earned and paid digital marketing platforms, audiences can be automatically segmented.

Make the change by building the solution

With the disappearance of third-party cookies and a reduction in first-party data, retargeting and targeting are becoming more challenging. The technologies that will replace third-party cookies won’t achieve the same degree of relevance and volume. The measurement capabilities will be drastically reduced: it will be impossible to track and reconcile all digital touchpoints. Additionally, compliance with regulations will make collecting and processing personal data more difficult.

The ability to deal with these constraints is an opportunity to distinguish yourself

The key is to build a consumer data strategy:

1. Collect first-party data (CRM, website and app browsing, media, PoS, etc.) to be able exploit their full potential;
2. Build a flexible and tightly integrated ecosystem of systems and apps to activate this data and measure marketing action performance; a Customer Data Platform, or CDP, which I will discuss later in this article;
3. Enrich first-party data with external data, third party data such as socio demographics, and second-party data that is data that is legitimately shared with another company.

We have developed this kind of solution several times, both in B2B such as for FD Media Group and in B2C and D2C Ecommerce.

Optimize and personalize your campaigns with AI and Marketing Audience Engines

Creating relevant and easily reactivatable segments is essential for personalizing and optimizing digital marketing campaigns. This is the role of Marketing Activation and Analytics Clouds that are being built on the Google Cloud Platform. Google Cloud is most suited for this if you ask me. It is the ease of build and ease of integration of Google Cloud, and the native integrations with the Google advertising and measurement ecosystem such as Google Ads, and Google Analytics.

A number of algorithms can be used to aggregate these data, some of which are outlined below:

• Scoring: calculation of a specific value at the visitor or customer level, or assignment to a group at a segment level. Input features may include browsing data, purchase history, email interactions, socio-demographics, etc. After distinguishing targeting strategy using these scores, the onsite/in app and advertising content (messages, creatives, offers) can be customized for each population. This also helps optimize media investments through biddings adjustments based on the value attributed to an audience segment.
• Clustering or look-alike: assembling audience communities and connecting them to marketing activation platforms to enable audience extension.
• Rules based audience: in ecommerce, rule-based audiences can be made using transactional activities (checkout date, coupon applied, etc.), marketing actions (email opened, promotion entered, etc.) or even product details (eg. type of product, color or type purchased).
• A/B testing and Insights: isolation of part of the audience to verify the relevance of digital strategies and created audiences. In this way, segmentation capabilities can be continuously improved.

Through MLOps, continuous training and segment creation can be automated. Advertisers can feed these audience segments into their activation platform ecosystem in near real time.

Conclusion

How can you successfully engage in your first party-driven digital transformation journey? Crystalloids’ top 4 recommendations:

1. Build a strategy to own and expand your first-party data (digital assets, data quality, data governance)
2. Create a long list of use cases and prioritize according to uplift gains and ease of implementation with the help of a partner who knows what works and what doesn’t
3. Build a CDP on Google Cloud yourself with help of a specialized Marketing Analytics partner. In most cases we see a packaged / off the shelf CDP is not the (only) solution because you need to be able to tailor to your situation in an flexible and cost effective manner because there is no single solution that fits with your current and unknown future requirements.
4. Next to MLOps. adopt principles such as MarketingOps and DevOps to be able to execute on the CDP by aligning the CDP technology with legal, creative, content, and UX.

If you need advice on how to build a strategy around your first-party data or if your company is thinking about building a CDP on Google Cloud and looking for an expert partner on this subject, please schedule a meeting.