Identity resolution bridges online and offline customer recognition gap - new episode of Everything You Need to Know: Data & Customer Experience

Relying on computers to predict probabilities can be tricky too: “Computers love certainty. The outcomes are only as good as the data and rules we give them,” says Mole.

In the video (full transcript below) Mole suggests a more advanced technique, known as “knowledge-based identity resolution” to recognise individuals through their major life moments, such as marriage or moving home as well as their everyday interactions.

“Knowledge-based data keeps up with the speed of life and allows the marketer to not deal with fragments and fractured views of people but one view and all of them resulting in smarter, deeper, more relevant insights.”

Last week’s episode examined how marketers can solve the missing data connection. Next week’s episode will cover how to activate the data in the new data-economy.

Future episodes in the series will tackle the new customer view, and how to combine online and offline data.

Video transcript

Welcome to Everything You Need to Know: About Data & The Customer Experience.

I hope you will spend a few minutes in a short taxi journey to talk about omni-channel customer recognition. Perhaps the most crucial cog of them all because everything else is built upon it.

The ability to know who an individual is online, offline, mobile, instore and everywhere else is every marketer’s Holy Grail whether they realise it or not.

Why? Because the better you can recognise someone, the more you can make marketing people-based, more relevant, and deliver a better customer experience.

Let’s take an example.

A client, one of Europe’s largest retailers told us that if they can take a potential customer and move them from the anonymous to the known state, they can increase the ROI by as much as 800%.

That’s a huge result, but is it really that surprising when you remember that by identifying the individual, they can connect the right data to the right people, create a richer and more accurate customer view, and smarter insights. Which all adds up to more relevant marketing, people-based marketing, and a better customer experience.

We’ve talked about the importance and value of customer recognition but we might as well talk about how challenging it is too. We live in a world of constant change and let me give an example of that.

In the UK alone, on average every day, about 9,590 households move, 1,496 people marry, 810 divorce and 2,011 people retire. These are huge lifestyle changes and intent data of the highest potential value, if you can recognise the customer as they move across these different identities, both physical and digital.

Customer recognition is difficult in both the online and offline worlds. Let’s start with offline and let’s look at Jane Sarah Smith.

She may buy a car as Jane Smith and may book a holiday as J Smith. She may marry or move or both. And it’s entirely possible, that Jane Sarah Smith of Manchester is now Jane Brown of Brighton.

How can we possibly know that’s one and the same person?

The problem with traditional matching techniques, often know as fuzzy matching, is we’re asking computers to do what they don’t like doing. Computers love certainty. They love 1s and 0s.

Now we may use computers to predict probabilities all the time. The outcomes are only as good as the data we give them and the rules. If we take Jane Smith, and ask a computer to compare Jane Smith of Manchester with Jane Brown of Brighton, how can a computer deduce it’s one or the same person when the only thing in common is one word. Jane.

Knowledge-based matching is an advanced technique that uses a rich data-set and knowledge-base of different representations of the same individual as they move through life.

This means that as people move through those big lifestyle changes, such as marrying or moving home, you can identify them as the same one person. And knowledge base keeps up with the speed of light and allows the marketer to not deal with fragments and fractured views of people but one view and all of them resulting in smarter, deeper insights.

Customer recognition is hard in the offline physical world but in the digital online space there are a whole new set of challenges.

Take me as an example. I have an email address to log on Wi-Fi and social sites but it’s not my main personal email. And then there’s my work email and I’m pretty sure, I’ve got two or three other email accounts that I log on to occasionally.

I have access to two PCs, one’s business and one’s personal. I’ve got access to two tablets and five mobile numbers associated with my name. One’s mine, one’s business, and three are family. Only one of which I am ever really likely to answer. That’s a lot of digital personas wrapped up in one person.

Then there are cookies, which most websites use to ‘remember you’, but they are increasingly regulated and almost non-existent in the mobile space.

Cookies can help deliver a much better person-centric experience. But some people are suspicious of them or more accurately, they may delete them.

The online world is a growing mass of fragments of data that are really difficult to link to one person. However today there are advanced techniques, a range of online identifiers used in privacy compliant ways to really ensure that you’re targeting and talking to the right person. My colleague Richard from LiveRamp will explain more in a later episode.

In short, omni-channel customer recognition allows you to recognise your customers online, offline across all of today’s channels and devices. All of which means smarter more accurate insights that drive a better customer experience.

Those insights can only come from the data itself and it’s activating the data in the new data-economy that we will be covering in the next episode.

Know enough about customer experience yet? Test your knowledge in our quick quiz.