How to build the data foundation for marketing automation in a large organisation
It is every organisation's ambition: to send the right message at the right moment to the right customer. Small organisations can easily tailor their marketing accordingly, but for many large organisations, with customer bases made up of millions of data records, it is a considerable challenge. Yet personalised communication and content at scale are precisely the answer to further growth.
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Why large organisations get stuck
Large organisations, or enterprises, which have often grown through acquisitions and by expanding their product portfolios, inevitably build up a complex data landscape. Customers exist across multiple systems with different IDs, and campaigns run on bespoke solutions that are hard to scale. Marketing automation then offers a way forward, but organisations often lack the right technological infrastructure and a solid data foundation. The decision to implement a CRM platform such as HubSpot is therefore the right one, but organisations forget just how much it involves.
Technology is the final piece, not the starting point
One of the biggest misconceptions in CRM and marketing automation projects is that the CRM platform will solve the problem. Yet the steps needed for a successful implementation are not about the technology; they are about the people who work with the CRM and have to master new processes and about establishing a solid data foundation. The weakest link in the combination of people, process, information and technology ultimately determines whether you develop the capability to make your marketing automation a success. Technology is an enabler; the other three factors determine success.
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Start with alignment and use cases
Before you purchase a single CRM licence, there must first be a shared understanding amongst your teams of how to solve your organisation’s scalability problem using marketing automation. An obvious but effective way to get on the same page is through workshops. Bring your marketing, IT and BI teams together in the same room. Let the marketing team explain the challenges they face. Let the IT team hear what’s happening on the other side of the organisation and show the BI team what data is available and how it’s structured. The shared language and understanding that emerge during these workshops are the basis for everything that follows.
From those workshops, you can then work towards a detailed implementation plan, including use cases. Think of specific campaigns you want to be able to run. What do they require? Which data? Which architecture? What needs to be in place first? This level of detail shows what marketing automation can deliver, which also makes it much easier to win over the board.
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The data model: the heart of it all
Only once your teams are aligned and the use cases are clear can you build a data model that can handle the complexity of both your customer base and your organisation.
In a large organisation, a customer is rarely a single, simple record. Consider an organisation with multiple services per customer, where the person who signs the contract is not the same person who receives the communication. Or customers who move house, switch contract types or give someone else access to their account. None of these changes should disrupt the customer relationship. A robust data model accounts for this complexity and is therefore essential to your automation.
By not loading all available data but instead working with IT to determine which data marketing actually needs, you keep the system manageable. The result is a single source of truth: complete and up-to-date customer profiles, campaign segmentation based on behaviour, automated triggers and centralised consent management. All from one CRM platform.
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From implementation to a new way of working
Once the data foundation and the CRM are in place and the first campaigns are running, something shifts within the organisation. Marketers who previously depended on IT for every change now build workflows themselves. Teams that never ran A/B tests now routinely test which variant converts better. And campaigns that used to take weeks are now built in days. Marketing automation becomes a way of thinking and working.
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And AI?
This naturally raises a follow-up question: what role can AI play within marketing automation? Here too, the same principle applies: AI amplifies what is already there. Without a sound foundation, AI mainly produces noise. It is only with a well-structured data model, reliable integrations and clear processes that AI becomes useful. You can then deploy it within your CRM for next best action logic, for automatically generating content variations, or for predicting customer behaviour.
Three key lessons
If, as a large organisation, you choose to professionalise your marketing automation by implementing a new CRM platform, a fair few steps come first. In summary, there are three key lessons to draw:
You are not just implementing new technology; you are building a capability. Before you choose a CRM platform, think about your people, processes, information and technology. Alignment between teams always comes before the platform. The technology you choose is the final piece, not the starting point.
Your data is the foundation, not an afterthought. Invest first in a future-proof data model. Without a solid foundation, you are building your CRM on sand, however good the platform may be.
Make your goals specific for everyone involved. Abstract ambitions don’t convince anyone. Specific use cases do. If you show the board which campaign you’re going to run and what it will deliver, it becomes much easier to gain their support.
Want to know how to build the data foundation for marketing automation in your organisation? Get in touch with our experts.