Single Customer View: Matching Process

Customer contact data doesn't really work unless it’s all connected up.

Simon Reason
29 March 2019

There’s something deeply satisfying about a crossword puzzle. It’s not just the warm glow of achievement when you put the right letter in the last box, it’s the ongoing process of reaching that point. Every new answer provides insights and clues to the next one. You learn as you go along, your brain feels like it’s sharpening up, and when it’s time to tackle the next puzzle, you’re much better prepared for it.

A fully fleshed-out customer profile is the business equivalent of a prize-winning crossword puzzle. Individual bits of customer contact data are the letters that complete these commercially valuable profiles. All you need to finish the profile puzzle and claim your reward are the clues – but where are they?

The answer is that they’re in the patterns, links and overlaps between all your data. We know that calls to a call centre, email responses, online browsing, web purchases, social media postings, and even regular mail will reveal telephone numbers, email addresses, membership numbers, postcodes and other personal data – but then what? Leaving these morsels of customer contact data in a raw, unsorted state is a massive waste, because the real power of data lies in its connectability to other related pieces. Join everything up and a richly detailed customer profile will emerge.

Data Matching

For many businesses maxed out on day-to-day activities, the extra effort of data matching may seem like one challenge too many. It’s too easy to approach it in the same way as you might an optional extra on a car: nice if you can afford it, dispensable if you can’t. But taking that view will put a real brake on your business’s marketing potential, and it’s a wholly unnecessary restriction too when specialists like Optima are around to take the load off and give you the help you need.

So, what’s involved?

Step 1 - Find Reliable Connections in the Data

To start with, all your information has to be brought together in a single place. Once you’ve established a central data warehouse, you can start to look for obvious and reliable connections and overlaps. These connections will, by association, provide other bits of information that add to your knowledge of the customer.  So, if a customer goes into a store and buys something using their loyalty card, we may know other information about that customer that is linked to their loyalty card, like their email address.  If that customer then buys online and uses their email address we can link this back to the in-store transaction and we know that this online customer also has a loyalty card. And so on.  Through these multiple connections we are able to build a more complete picture of the customer.

Linking up data can be tough though, especially when it’s compounded by the difficulty of establishing the precise ownership of data. If customer John uses an email address to buy online and his partner Janet uses the same email address (via a loyalty card) to transact in-store, who actually owns that address? Is it Janet or John? And what about an individual customer who has more than one email address?  What primary address should be recognised and assigned to their customer record?

Step 2 - Organise Anomalies with Non-Conflicting Business Rules

These real-life data challenges lead us into the second part of the matching process. To begin the mechanism of building accurate and unique customer IDs, companies like Optima will consult with you on the creation of a set of clear business rules aimed at simplifying and organising the anomalies. These rules will be non-conflicting, consistent with your business ambitions, and bespoke to your needs. To deal with the surprisingly common scenario of multiple users of a single email address, for example, your own rules might include different weighting choices allowing you to prioritise the contact responsible for the most recent purchases, or the one responsible for the most valuable purchases.

With the right connections made and the right business rules in place, your data quality will rise to an all-time high, and you’ll have in place a data warehouse that represents a single version of the ‘customer truth’. This master data warehouse can then feed content into the contention-foiling database solutions you’ll need to get around the hazard of a single database solution that’s being unreasonably expected to perform multiple tasks with equal efficiency, but that is a blog for another day.

Don’t leave your data in a disconnected state. Finding the connections and writing clear business rules will put you well on your way to creating a single customer view across multiple channels and line up you up for that big puzzle prize.

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