Steps to Data Collaboration
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Data Collaboration: 6 steps to get started

  • Graham Tricker
  • 4 min read

In the final post in our series on data collaboration, our VP of Sales UK Graham Tricker looks at how you can start preparing your business for the future of marketing.

Data collaboration is the future for most businesses. In a post-third-party cookie world, it’s the only way to establish the deep, holistic understanding of your customers needed for effective and efficient marketing. And it’s essential for building the foundations for your future use of AI in marketing.

Convinced? That’s important, because conviction is vital in getting started. Change is incredibly hard to achieve in most organisations, particularly if you don’t have a burning platform. You need to persuade your colleagues that data collaboration will transform the business and ready it for the privacy-first, personalisation-driven future. After that, everything else should be straightforward.

The journey to the collaborative future

There are six steps you need to take;

1. Build the business case. Firstly, identify your long- and short-term goals. The long-term goals of your business should form the context for your initial data collaboration trials. You might want to develop a new revenue stream, identify a new target audience or launch a new product.

Build a ‘Test and Learn” approach to rapidly iterate through hypotheses to identify the use cases that can deliver value and be scaled up.. These should be simple, high-value use-cases. They need to demonstrate what data collaboration can deliver, without involving significant resources or risks.

Then think about your KPIs. What are you going to measure, and how will you measure it? Ideally, you should choose use cases that make it easy to measure both costs and results, rather than one whose results are difficult to untangle from other activities outside your control.

2. Find your allies. It’s unlikely you’ll be able to pull this off alone, so build relationships with the colleagues whose help you’re going to need. This will likely include management level people in marketing, analytics, data, tech, procurement and even your agencies.

Most importantly, you’re going to need an executive sponsor. This will be someone who has the vision and credibility at the exec level to secure budget, resources and approval.Finding this person will also influence the choice of your first project. If you pick one within their sphere of influence, where success will make them look good, they’ll be more likely to support you.

3. Choose the right partner(s). Deciding what your first project is going to be will simplify your choice of partner. Audit your data resources and establish whether there are gaps to deliver the initial use cases.. Then look for the businesses that have the data that adds value to these use cases, this could be accessing premium data such as demographic, attitudinal or cross market buyer audiences that are readily available via 3rd party data supply, or it could be a complementary brand or partner that has valuable data to exchange.  

Once you’ve established your partnership, you need to bring together the crucial people from both sides. Who those people are will depend on the ambitions for the project, but it should include analytics and data experts.

4. Choose your technology. How are you going to facilitate data sharing? We looked at this in an earlier post (Why Marketers Are Falling In Love With Data Clean Rooms) but, to summarise, anyone investing in a data clean room should look for:

Identity Infrastructure: A privacy enhanced technology that ensures each party has its own unique customer identifiers, allowing customer data to be shared safely. 

Flexibility and interoperability. For maximum speed and efficiency, your clean room should be usable by all the partners, and be agnostic of each party’s technology stack or media platform you want to leverage. 

Respect for the principle of data minimisation. Your clean room should only allow users access to the data they need for the specific task they’re working on. It should also enable businesses to collaborate on data without the data leaving their Cloud or Data Warehouse (this is known as taking the code to the data, rather than the data to the code).

5. Set the rules. You need to agree processes and service levels to ensure your data collaborations meet your company’s requirements around data provenance, governance and permissioning. Then you need to turn those into contracts.

6. Analyse the results. Repeat. Not every use case  you run will deliver the results you want, but every one will contribute to your knowledge and understanding.

Take a deeper dive into ‘creating brilliant customer experiences with data collaboration’, or ‘navigating the data collaboration revolution’ with our ebooks. 

Communication is key

Ultimately, the success or failure of your data collaboration initiative will depend on your communications skills. From involving key stakeholders at the start to presenting your results to the board, you need to be able to create a clear narrative showing what data collaboration can bring to the business, and what’s required for it to do so.

That’s what this series of posts has been all about, but we also have a lot more resources you can draw on, from case studies to explainer videos to e-books. We’re also always happy to talk about any and all of the issues raised in these posts so, if there’s anything we can help with, please get in touch here.