Matching gears

Data Talks, Episode 8: Identity Resolution

Episode Eight: Identity Resolution

Host: George L'Heureux, Principal Consultant, Data Strategy
Guest: Scott Smith, Principal Data Advisor

What is ‘identity resolution’ (also referred to as ‘matching’)? Simply put, it's when you're connecting your organization's data to a trusted set off commercial reference data. Matching is a critical and worthwhile step, whether you’re doing basic data cleansing, cleaning up your CRM, or augmenting your data with the richness of third-party data assets.

At Dun & Bradstreet, we match data to the Dun & Bradstreet Data Cloud and provide a D-U-N-S® Number – a unique identifier for a business – unlocking the richness the Dun & Bradstreet Data Cloud has to offer into the customer environment: business demographics, firmographics, predictive indicators, and more.

 

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George L’Heureux:
Hello everyone. This is Data Talks presented by Dun & Bradstreet and I'm your host George L'Heureux. I'm a principal consultant for data strategy in the advisory services team at Dun & Bradstreet. Here in advisory services, our team is dedicated to helping our clients to maximize the value of the relationship with Dun & Bradstreet through expert advice and consultation.

George L’Heureux:
On Data Talks, I chat each episode with one of the expert advisors at Dun & Bradstreet about a topic that can help consumers of our data and services to get more value. Today's guest expert is Scott Smith. Scott is a data strategy consultant at Dun & Bradstreet. Scott, how long have you been with the company?

Scott Smith:
Well, George, I'm proud to say I've spent my entire career at Dun & Bradstreet and I've been in positions everything from a financial and credit analyst to participating on our product teams, to leading teams and probably the most significant amount of time I've spent in an implementation role working directly with our customers, so probably two decades worth.

George L’Heureux:
There's not a lot of people who can say they've spent their entire career with a company. I think it must say a lot about the interest level in the work that you found within Dun & Bradstreet.

Scott Smith:
Yeah, it's really interesting. I'm part of what we call our data advisory services team and really at a high level and what our team does, we work with our customers to translate and interpret the meaning of D&B data and we're trying to help them with integration and consumption into their own environment. So what's interesting about that, I spend the majority of my time in our ... we have a really tremendous team on data advisory services with a lot of experience and we spend most of our time trying to help customers really understand data and helping them to get the most value from their purchase with Dun & Bradstreet.

Scott Smith:
So I'll give you one analogy, George. I think this is a really good one. If someone buys a high-performance car, typically they will be able to drive that vehicle off the dealership and get from point A to point B. Likely, they won't take advantage of all of the features and functionality until they're educated about it, until someone actually shows them what that high-performance car can do. So it's meant to perform at a very high level, but until someone actually educates them and walks them through, they're not really seeing the full potential of that vehicle.

Scott Smith:
So it's really the same thing with D&B data. When our team gets involved, we're helping our customers fully understand the data and maximizing the value and really, basically, we're trying to help them get so the data performs at a very high level.

George L’Heureux:
Well, I'll tell you, after we get done with this conversation, Scott, I'm going to have you come over and tell me what that one button in my car does that I've never used and still haven't figured out.

Scott Smith:
Sports mode, yeah.

George L’Heureux:
What we had wanted to talk today about was identity resolution, what a lot of people call matching. Let's start with the basics. What is identity resolution?

Scott Smith:
So you've heard matching, you've heard identity resolution. Simply put, it's when you're connecting your organization's data to a trusted set off commercial reference data. That's really what it comes down to. So I work with customers all the time where you have customers, let's say, trying to clean up their CRM, they're doing some basic data cleansing, removing extraneous characters from their data, trying to clean it up with the right data, for example, trying to link it.

Scott Smith:
And we have many customers that really the ultimate goal here is to augment what they have in their environment with all the richness that Dun & Bradstreet has to offer in terms of data assets. So that's really matching - is trying to merge those two together. And I think in my experience we're looking at our customers are really taking advantage working with D&B because we have right now 420 million entities in our Data Cloud.

Scott Smith:
So, it's really the goal here is to match to our Data Cloud and to give them, what we call, a D‑U‑N‑S Number, which is a unique identifier for a business. Once we do that, we unlock all the richness of the D&B Data Cloud into their environment. So really that's the first step in my mind. That's really the key is unlocking that first step with matching our identity resolution so they can get to all that richness. So demographics on a business, firmographics, predictive indicators and that type of value.

George L’Heureux:
So how would customers do this if they're not using Dun & Bradstreet? I mean, that seems like it has to be something they'd have to build themselves.

Scott Smith:
Yeah, well, that's a good question. And, George, we do see customers that are making that attempt to do their own matching. So there's MDM merge-match software packages out there. You see a lot of customers trying to do that type of activity. There's an exact match, a phonetic fuzzy match, that type of thing. But the key here is they're trying to do it without a referential third party like D&B. So that's really the difference here. Also, we provide that vast rich insights. I mentioned 420 million records that we're currently tracking to in our Data Cloud, but the other benefit is really the D‑U‑N‑S Number. I mean that's something around the world that is adopted as a unique identifier and really a trusted source.

George L’Heureux:
So how does the additional data help in matching and what the additional value does that D‑U‑N‑S Number bring after the match is complete?

Scott Smith:
Yep. Well, I think, really, there's a couple of different benefits to our customers leveraging the D‑U‑N‑S Number. I first want to tell you that the referential data is something that we really find beneficial because right now out of the 420 million records, you can imagine just the rate of data dynamics and data changes on an hourly, daily basis for that volume of records, right?

Scott Smith:
You have businesses that move, you have different owners or CEOs come in. Businesses are expanding, contracting, hiring employees, laying off employees, that type of thing. And all these dynamics are taking place and we're tracking in what's called our match reference file. So the benefit to that is we take that 420 million and you break out all these different match reference points. Now you're over well over 1 billion match reference points.

Scott Smith:
We're tracking the legal name of the business, the trade style, the registered name. We're looking at the business address. The current business address, former address, maybe the owner's home address. So all these different match reference points we have the functionality with identity resolution at D&B to leverage that vast array of match reference points. And our goal, again, is to match to the right entity within our Data Cloud. And so I really think that's what sets us apart and that's really the benefit that D&B brings.

George L’Heureux:
You hit on it there, and I want to follow up on that.

Scott Smith:
Yeah.

George L’Heureux:
We've got these more than a billion match points that we can match against. Great. Let's say we match and we return a D‑U‑N‑S Number. What are we doing to make sure that our customers have that trust that we did it right and that we gave them the right answer?

Scott Smith:
Yeah. That's really a good question because I think the matching in general is customers are trying to understand why the match was made and how it was made, right? So the metadata that we offer behind the scenes is really valuable in that process. So we have not only a confidence level that we're able to say, "Hey, at a confidence code 10, we're matching that precisely to a candidate in our match reference file all the way down to a zero, which is an unmatched." But we also have what's called a match grade string, which is really measuring the accuracy of each of the key components of a match. So the business name, the address information, it could be the phone number, we're going to score those and our algorithm will then correlate that to the confidence code. But in addition to that, we'll also provide what's called a match data profile, an MDP code.

Scott Smith:
And the benefit there is, I mentioned before, let's say a business moves to a different location. They expand their operations, they moved down the street to a larger facility. We're going to be able to tell why we matched the way we matched. If we matched exactly to a business address, to a record, but our customer has a totally different address, we can explain why. We have that metadata behind the scenes that we can leverage.

George L’Heureux:
And that enables the customer to sort of, I guess you might say, double check. I don't know that I even like that word, but they can look at, like you say, why it happened. They don't just have to take our word for it. And that tends to be something that we talk about with clients all the time.

Scott Smith:
Yeah. And I think the benefit to having the match metadata is also we can fine tune. We can really customize our match environment based on the customer's use case. That is really our charter here because if you think about one use case on one extreme, I work with a lot of our large banking customers, for example. So I'll use an example as underwriting, if you're in an underwriting situation and you're approving a potential contractor for a line of credit, for example, or a commercial card, you want to make sure that you have some stringent rules in place to match to the right record in the Data Cloud.

Scott Smith:
I mean, we got to make sure that's right to vet that business out or from a compliance standpoint, you can have other customers that are leveraging a totally different use case for marketing. The match rules might be a lot less stringent for that type of application. So using that metadata behind the scenes, we're able to almost turn the dials, if you will, to either accept or reject, depending on your use case. So it is very tuneable and customizable.

George L’Heureux:
Well, let's get a little tactical here. Someone's listening and they're not currently using Dun & Bradstreet match capabilities. What are the minimum requirements? What do we need from a customer in order to try and attempt to match?

Scott Smith:
Yeah. That's an excellent question. When our team gets involved with an engagement, that's really one of the first items of discussion, the task on the list, because if you think about our match technology, the minimum requirement is a name and a country. But if you have on the input coming into the process, if we can have the business name, the complete address and correct address for the physical location, potentially the mailing address, the city, state, the zip, the postal code. If we can have a phone number, maybe even a URL or an email address, the more data points and even a business registration ID, for example, or tax ID, the more input we have, the better chances we'll have a higher match to the match reference file.

Scott Smith:
The other process that I always emphasize is more is not necessarily better. We have to have the right data populated in the right fields. So that's part of our, at data advisory services in terms of diagnostics on the front end, we're working with our customers to help them understand how we can get to the best possible match, the highest possible match rate so that whatever their use case is you'll see the benefits downstream.

George L’Heureux:
So let's talk about why you do this real briefly. If you're a customer and you're not currently matching to get a Dun & Bradstreet D‑U‑N‑S Number, what are some of the risks that you're taking on for your business across a couple of different use cases?

Scott Smith:
Yeah. That's great and I'll go back to my underwriting example. If there is a potential, let's say they're using their own software, for example, and potentially not matching to the right business or doing a lot. And there's a lot of manual work involved to do your own homegrown, I guess you can call it, match algorithms. And so if you're matching to the wrong business from an underwriting standpoint, there's obviously a potential for write-offs and bad debt. You get into that angle of losses.

Scott Smith:
On the flip side of that, if you're in a marketing environment and you're not capturing or onboarding the right business, you're losing out a potential revenue stream. So I really think the third part of that is leveraging back to the D‑U‑N‑S Number.

Scott Smith:
D&B is able to connect business entities and affiliated companies through the D‑U‑N‑S Number. So I could be operating as a subsidiary of a parent company or a headquarter company. And just having that D‑U‑N‑S Number allows us to link and associate business entities together. So tremendous benefit, whether it's compliance or supply management or risk management or marketing, all those different use cases. There's a monetary, there's a return on investment for each one of those use cases, so that the higher match we can get to the Dun & Bradstreet Data Cloud, the better. And again, the whole goal is to unlock all the valuable data assets within that Data Cloud so the customer can make the right decision.

George L’Heureux:
So before we wrap up, let me ask you if there's one key takeaway that you would want listeners to this or people watching this to walk away from this conversation, what would that be?

Scott Smith:
Yeah, I would say it all starts with matching or identity resolution. It's finding out the correct entity and matching to the right D‑U‑N‑S Number. I think that's really the first key benefit. The data advisory team, we have a deep understanding of our match reference data and our metadata. And we have been involved in many, many engagements from a data stewardship standpoint. The process alone, we've successfully implemented the match optimization process in data advisory services hundreds of times over the past few years. So our team's approach can really guide our customers with this process and we've been really successful with it.

Scott Smith:
So I guess the key takeaway is connect with the data advisory services team and we'll work with your customer to make sure that we get the highest possible match rate so that whatever their use case is, whatever their goals and charter is, we'll see success.

George L’Heureux:
All right. Well, thanks, Scott, for taking time to participate and share some of your expertise on this topic with us today.

Scott Smith:
Certainly. Thank you, George.

George L’Heureux:
Our guest expert today has been Scott Smith, the data strategy consultant here at Dun & Bradstreet. This has been Data Talks. I hope that you've enjoyed today's discussion. And if you have, we encourage you to please let a friend or a colleague know about the show. And if you'd like more information about identity resolution, match optimization services, or any of the topics we discussed on today's episode, visit www.dnb.com or reach out to your company's Dun & Bradstreet specialist today. I'm George L'Heureux. Thanks for joining us, until next time.