Should you consider a different take on CDP (Customer Data Platform) implementation?

Organisations have realised the importance of customer data in today’s business landscape. To create personalised and relevant experiences for their customers, they need to have a comprehensive understanding of the customers’ preferences, behaviours, and needs.

There has been an emerging popularity in Customer Data Platforms (CDPs), but what do you understand by this term?

In this blog, I will outline some of the challenges of implementing a CDP, the initial approaches businesses have taken for implementation, and introduce an alternative strategy which can benefit your organisation.

What is a Customer Data Platform (CDP)?

In the simplest form, users expect CDPs to aggregate all data in a single source of truth, to power marketing through all channels.

However, CDPs can mean different things to different people. They can be a tool for data capture, identity resolution and enrichment, a single view of the state of customers, audience segmentation and orchestration, data activation, and analytics.

Gartner defines a CDP as “marketing technology that unifies a company’s customer data from marketing and other channels to enable customer modelling and to optimise the timing and targeting of messages and offers.”

The not-so-good news is that when it comes to rationalising and putting customer data to work, there is a lot of hype around CDPs, but at an alarming rate of implementation failure. The great news is that top execs are taking customer data seriously.

What are some of the challenges surrounding CDP implementation?

With the rise of digital channels, businesses generate vast amounts of customer data daily, adding to the data silos across an organisation. Marketing teams live and breathe customer data, but they don’t always trust it. There is just a multitude of customer data solutions out there, and marketers are baffled by the range of options available to them.

Disjointed organisational structures and processes don’t help either. Companies increasingly expect customer data platforms to support customer experience (CX) use cases that fall outside of marketing’s direct control, such as the next best action for customer service or customer journey insights. These use cases depend on or overlap with capabilities in IT systems, such as master data management or cloud-based data warehouses.

Despite these challenges, business leaders want to build a cohesive data ecosystem and standardise data collection. They also want a unified customer view and analytics, with CDP customers expecting 5x ROI (return on investment) or higher.

Here are some of the ways that businesses have initiated the implementation of a CDP:

1) Do it yourself

Building a CDP requires an organisation to have a fully resourced development team with heavy involvement from its entire data team. It is key to factor in ongoing support and maintenance required for custom-built CDP solutions over time. However, this approach poses its own set of challenges, and leads an organisation to grapple with questions such as:

- What is the CDP product roadmap?
- How do we make the CDP extensible, adding innovative new functionality?
- What is our staffing plan for when developers leave?

2) Traditional CDPs

Fully integrated CDPs by a single technology vendor are ideal in the instance where “one vendor, one solution” can meet all or most of the organisation’s requirements. However, this is rarely the case — some of the pain points organisations raise with one-size-fits-all CDPs include:

- Rigid data models
- Long onboarding times
- Data redundancy across marketing and analytics tools
- Vendor lock-in and limited extensibility

A lot of organisations struggle with their traditional CDP implementation when they think of the CDP as a disparate system or an extension on the side, effectively disconnecting it from the rest of an organisation’s data stack. This approach is inevitably not aligned with the existing data management strategy and is often exacerbated when marketing teams make these purchases in isolation, leading to struggles with implementation complexities. Furthermore, having additional data platforms may lead to having multiple “sources of truth.” Data teams are challenged with using tools native to the CDP and end up managing audience segments in multiple places.

But there is another approach. Before we delve further into this, let’s touch on some of the broader factors that must be in place:

- A well-defined, documented, and governed customer data strategy.
- First-party customer data. Customers expect personalised experiences with every interaction and organisations are scrambling to implement data infrastructures that leverage first-party data.
- Actionable intelligence on top of your first-party customer data.

An alternative approach: The Composable CDP

With this method, you implement a CDP system as an element of the organisation’s broader data management strategy. Also known as a modular CDP, this approach combines platforms to form a best-of-breed alternative to traditional one-size-fits-all CDPs, to organise, manage and utilise customer data, and build their own unique CDP. It enables modern organisations to manage better their first-party data strategies and leverage their existing investment in a data warehouse.

Teams don’t need to start from scratch. Any work done acquiring data solutions and harmonising data can be pulled forward. When implemented well, composable CDPs can deliver greater functionality by choosing the solutions best suited for their role in the composable stack. Teams have greater agility in replacing pieces of the stack without affecting the whole CDP system when use cases evolve and the organisation grows.

Every organisation has different customer data needs. This is why rigid, all-in-one CDPs aren’t always the answer, and why the composable best-of-breed solution could be a better option.

Consider the following points before implementing a composable CDP:

- Does your organisation already have a data lakehouse feeding and supporting your customer data efforts?
- How mature is your data team and what are their skillset?
- What solutions do they use and how do these fit into your CDP strategy?

Enable teams to make the most informed architecture decisions when implementing their own composable CDP. Marketing and IT can carefully and properly implement each selected component and move faster for less cost, without the vendor lock-in of an all-in-one CDP.

What are the benefits to be gained?

A key benefit of implementing a composable CDP is the phased approach that comes with it — you don’t need to buy a bunch of tools at once. When you buy a traditional packaged CDP, you’re forced to evaluate everything upfront because you’re locking yourself into a single platform. This flexibility allows you to solve the most important problem in front of you and choose the best solution and components for your business, futureproofing and swapping out certain components down the line when your needs change.

Composable CDPs are designed to be easily adaptable to changing conditions and data sources, and organisations can pick and choose the specific data pieces needed for a given purpose. This level of modularity makes it possible to mix and match data sources in a way that is easier than before, creating a solution that’s as flexible as it is powerful. With a composable CDP, marketers can more easily add new data sources, test new marketing strategies, and adapt to changing customer needs, effectively enabling them to use more common agile practices across the entire marketing team.

Most companies likely already have a data management strategy and a data platform in place. With a composable CDP, an organisation can align its teams to its data management strategy and build upon its data platform. IT and data teams also have the ability to move more quickly — instead of starting from scratch, they simply extend what they already have.

Using an internal data lakehouse benefits marketers by tapping into the growing data and people resources within other parts of the organisation. These internal resources can enable marketing teams with richer, more directly actionable customer data across all activation channels. The CDP should be part of an aligned data, marketing, and IT ecosystem.

Composable CDPs can bring in support for new capabilities as they are needed, instead of buying everything upfront. As for ROI, the boost comes from being able to move faster because there is no need to wait for a big implementation to enjoy the benefits.

Conclusion

By implementing a composable CDP, businesses can achieve better data governance through a central repository where customer data is managed — using better data quality and models, accessed directly, leading to improved results. Following the approach outlined above, organisations can achieve an implementation which is modular and future-proof by design, exposing a single or primary source of truth across marketing and other teams.