Connect, Unify and Enrich: How to get your data in the best shape of its life!

Data is brilliant isn’t it? It tells us so much about our customers, we can use it to inform campaigns and it tells us when those campaigns are working. It’s true that marketers love data and lots of it, but it’s got to be organised and choreographed correctly if it’s going to be of much use.  

It’s a bit like an athlete or a bodybuilder. They need to consume lots of calories, protein, carbs and supplements to help build the physique they want – but all of those are wasted if they’re not put to work with the right training techniques and routines.  

And the inputs and training regimes regularly change over time to match the athlete’s goals.   So how can we get your data into the best shape of its life? We’re going to use the single customer view data fitness technique: Connect, Unify and Enrich.

Step one: connect

The amount of customer data you’re able to collect is vast – but that can result in a huge, overwhelming mass of data, which can make analysis difficult, often impossible.  

In the same way an athlete has lots of data to understand, not only looking at their food intake, athletes also need to track their progress using all sorts of data points – speed, weight, strength, flexibility, heart rate, with elite athletes tracking deeper analytics like blood pressure or oxygen levels.  

Looking at all of these in isolation won’t provide the true picture of their progress.  

It’s the same for marketers. Quite often you have to work with several different data sources – some of them huge – and often scattered in different places or on different platforms.  

They’re all important, but they’re more valuable and reveal deeper and more compelling insights, if you can connect them.  

Crucially, marketers should make sure they’re connecting the right data sources using the right software, so it can be easily analysed when needed.  

When luxury travel provider Elegant Resorts wanted to offer their customers more personalised campaigns, they had to take the first step of building a single customer view. This involved connecting together unique data structures and complex customer journeys.  

Thanks to the custom integrations, the tour operator now has a connected picture of their customers enabling them to now automate and personalise its communications with clients and easily segment against all customer, booking and browse behaviour data – something which wasn’t possible with their previous solution.  

This led to higher customer engagement and higher conversion rates across the customer journey from quote to booking.

Step two: unify

 Once you’ve got your data all into one place, it needs to be consolidated to match individual customers.  

This isn’t a single process that takes place at one point in time, it’s a continuous activity performed at regular intervals. This ensures your customer data is accurate and relevant, and it’s where the foundations for personalised communications are laid.  

Back to our training metaphor, this is where an athlete takes a full overview of their diet and biometrics, and matches relevant data to whatever goal they’re working towards. Data quality and data matching go hand in hand here, and the result is data structured around the customer.  

There are so many brands that still keep their data siloed. As a result they’re not able to pull any rich customer insights, measure across the customer journey or create engaging experiences. This is just a waste of marketing expenditure.  

Working with unified and accurate data brands can personalise multiple areas of a single campaign, tailoring messages to reach multiple customer groups.

Step three: enrich

When athletes are training, they monitor their progress and how their body is reacting to a programme. They use this information to make changes to their exercise regime, dialling muscle groups, weights or targets up or down as required as they achieve their goals.  

For marketers, it’s about using any relevant new information you learn about a customer to shape your responses. Knowing about browsing history, abandoned baskets, purchase history, returns history – even choices of delivery or payment methods enrich your understanding of how customers are engaging with your brand.  

But customers change as their circumstances change – and it’s important to keep your customer data fresh to continually enrich your knowledge of, and relationship with, your customers.  

Introducing predictive models can be used to enrich customer data to help understand and predict future actions.   This allows for triggered marketing messages which could, for example, re-engage lapsing customers or automatically target predictive segments with their latest products and offers.  

This can lead to a significant reduction of customer churn and this continuous enrichment of data helps grow the overall value of the customer database.