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Data Talks, Episode 10: The Power of Consumer-to-Business (C2B) Matching

C2B - A Powerful Approach to Identifying New Customers

Host: George L'Heureux, Principal Consultant, Data Strategy
Guest: Holly Reed, Data Strategy Consultant

Many businesses get stuck in a rut, mining the same lead list for years and experiencing flat or declining campaign results. One strategy to break free is Consumer-to-Business cross-selling.

Consumer-to-Business, or C2B, is a catchy name for a cross-selling approach where a company can look for business prospects within their consumer portfolio. It’s commonly used by financial institutions, but any organization with a robust consumer base that’s trying to expand their business portfolio can benefit from a C2B strategy.  

In this episode of Data Talks, host George L’Heureux chats with Data Strategy Consultant, Holly Reed, a match expert and 31 year veteran of Dun & Bradstreet. 

 

Read full transcript

George L’Heureux:
Hello everyone. This is Data Talks presented by Dun & Bradstreet. I'm your host, George L'Heureux. I'm a principal consultant for Data Strategy in the advisory services team here at Dun & Bradstreet. In advisory services, our team is dedicated to helping our clients maximize the value of their relationship with Dun & Bradstreet through expert advice and consultation. On Data Talks, I chat each episode with one of the expert advisors at D&B about a topic that can help consumers of our data and services to get more value. Today's guest expert is Holly Reed. Holly is a data strategy consultant at Dun & Bradstreet. Holly, how long have you been with the company?

Holly Reed:
So well, first George, thanks for the invite. So I've been with Dun & Bradstreet for 31 years in numerous roles, including both as an individual contributor, as well as having leader roles within content, operations and then sales support.

George L’Heureux:
So, can you tell me a little bit about what you see as your role in your current position?

Holly Reed:
Sure. So like you said, I'm a data strategy consultant. I really consider myself a subject matter expert in our match technology, as well as the Dun & Bradstreet Data Cloud. I have a deep understanding of the D&B match metadata, and that's really the how and why a match was made. I also am a consultant, so I work both new and existing customers to optimize their match results and to provide recommendations for match improvements. I also have a portfolio that I help support. I have 16 customers within the financial institution segment or space. So, I consider myself a banking expert.

George L’Heureux:
That's great. I know that that segment of our customer base is an area where they take advantage of our topic today quite a bit, and that is we're able to help our customers do what we call C2B matching. So, let's start with first things first, break it down for me. What is C2B matching?

Holly Reed:
Okay, I'll start at the basics.

George L’Heureux:
All right.

Holly Reed:
So, C2B matching, all it is it's consumer to business matching. It's where we can identify businesses associated with individuals in our client's consumer universe. So if you think of financial institutions, they have both consumer and commercial accounts, we can identify those business leads within that robust consumer portfolio. By robust, I really mean the volume of consumers within the portfolio. Using our Match technology and the historical Match Reference File, we can identify individuals who own businesses. So you think of CEOs, presidents, and any other additional executives.

George L’Heureux:
So, help me understand why this is so appealing to financial institution customers. Why would they to do this? Is the quality of leads you get back that much better?

Holly Reed:
So, it's the quality of leads, it's a warm lead and it's easy. I say, it's easy. So C2B provides new leads to cross-sell and upsell, and it really takes advantage of those existing relationships that you already have. So if you think about a bank, a banker or that relationship manager, they may know that consumer, that individual, and how easy would it be for them to, during a casual conversation like we're having, offer a commercial credit card.

Also, they're more likely to open the offer since it's an existing relationship. So you think how many times are you receiving a piece of mail, and you're like, "Oh, I'm not dealing with that institution," you're going to throw it out. So we have an existing relationship, we're going to open it up. If the individual has a personal loan or a credit card, you may have a credit history. So, I have a client who has 44 million consumer accounts and 1.4 million business accounts. So if you think about that, that's a huge opportunity to cross-sell to people you already know.

George L’Heureux:
You talked a minute ago about the different types of historical data points that we could match to. You talked a little bit about CEO, other executives. Is there a way to limit kind of the scope of what you're looking for? I don't want to find someone who's maybe, and I'll put this in scare quotes, just the CFO of a company, I'm looking for just that CEO. Can I narrow it down that well?

Holly Reed:
Absolutely. Really, D&B can fine-tune really their matching dial. Using the Match metadata, which includes confidence codes, Match grade strings and Match data points, along with the historical Match Reference File. So using all of this information, these matching attributes, we can identify what exactly you're looking for. So if you're looking to target the CEO, we can say, "You know what? We only want to provide leads back that have a Match data point of 03, which is the CEO." So yeah, we can definitely utilize that Match data to get to the attributes that you're looking for.

George L’Heureux:
So we've already talked about this in the terms of financial institutions and how they'd use it, the 44 million individual customers that they have and the 1.5 million business customers and how those come together. Are there other segments of our customers, of our clients that would be able to take advantage of this?

Holly Reed:
Yeah. So the one that I think about that's probably underrated, I'm going to say like a tech company. So, they may offer equipment financing or consumer credit cards. So, how great would it be that they're looking at these consumers doing C2B matching? So instead of someone purchasing equipment based off of myself individually, an offer goes out for a business credit card or some type of business financing. When you're looking at C2B, there's so much more profitability within the business products, they're more expensive. So, it's a great opportunity.

George L’Heureux:
So, that's a great example of how we can use it in financial institutions, you and I have seen this really be applicable beyond that though. We were talking about dentists before we started recording this, and I think that would be a really interesting use case to share.

Holly Reed:
Okay. So just as you said, so another area that I've been working with one of my clients is professional designation. So if you think of dentists, so DDS, you think of Esquire, CPAs or MDs, what a great opportunity. You're looking for that type of profession within your consumer universe, your consumer portfolio. So with C2B matching, we can identify really that professional that is also that business owner. Working with this client, we were actually able to get to a 50% match rate from their C2B matching.

George L’Heureux:
Now, how do we narrow it down so that it's just on something, like in this case, dentists? Is that a use of an industry code or is there another approach that we do there?

Holly Reed:
Okay, so for this, it's the use of ... so D&B does have the SIC or the industry code, so yes, we can do exclusions, inclusions based off industry code. But the other key factor with utilizing D&B is that our goal or my goal is to really get you to that actionable, a lead list that you can use. We always approach it as a waterfall.

Now we're not saying that all customers utilize this approach, and with the waterfall, it's really including and excluding leads. So, there's some factors that our customers need to keep in mind. So, are they managing to a pure number of leads? How risk-adverse are they? How are they going to measure the campaign? Those are just a few.

So, let me give you an example of a customer I'm currently working with, and they are not using any waterfall approach, they're basically saying I'm going to measure the success of Dun & Bradstreet by the number of total matches and the number of high quality matches. That's it, there's no inclusion or exclusion. Now, is that the best way to do things? No, but that's how they're measuring success.

The way that we recommend that you really measure success or what approach you should take is a waterfall approach. So, using key filters to include and exclude based on your strategies and the likelihood of the client not being approved. So, the first thing I always tell the customer is remove your current customers, you don't want to market to them. You don't want to waste marketing dollars, but you don't want them to be upset thinking, "Gosh, they don't even know I'm a current customer."

So that's the first thing, but you can also then segment the leads. Are you looking for customers that are less than $500,000 in revenue or less than five employees? You can remove certain industries. Cannabis is on the bad list within certain banks that I deal with, so remove cannabis. The other thing we always say is utilize the D&B indicator. So, we have activity or marketability indicators that we can exclude from your lead.

So the first is out of business, you don't want to market to someone who's out of business. Next, you can look at what we call unable to confirm or UTCs. So, those are records that are showing very limited business activity at that specific site. So, we can't confirm the status of the business. We're not sure if it's out of business, so we're calling it UTC.

Now, most of our customers just automatically exclude UTCs from their leads, however, we have some very smart customers that actually include these UTCs and they test and learn from them, because what they found is that most people forget about this universe of records. So because most people forget about them, when this universe of records receives some type of marketing opportunity, they're the first ones to jump at it. Now you may not always approve, but again like I said, test and learn, see if and when you can use this set of records.

Then the last two, public records. So you can remove open bankruptcies, you can automatically exclude those. You can also look at suits, liens, judgments, and the dollars associated with them. Then lastly would be really the credit worthiness. How are they paying their suppliers? Are they likely to still be in business in 24 months? Are they likely to pay their suppliers? So, those are just a few ways that we can help our clients utilize inclusion and exclusion rules to really get to the leads that they're looking for.

George L’Heureux:
What it really comes down to, it sounds like for me, is that it goes beyond just matching this customer information and finding a business from it, there's all these dials that customers can use to really narrow down their focus and make sure they're getting that lead list that they're really interested in.

Holly Reed:
Exactly. It's the ability to really move the dial to their use case and get to what they're looking for exactly.

George L’Heureux:
So, are there minimum requirements for someone to be able to do C2B matching with Dun & Bradstreet?

Holly Reed:
That's a great question. So absolutely, customer input data has a direct impact on the match quality. You've probably heard the old saying, garbage in is garbage out. So, I truly believe that. We always recommend that specific data points are provided on the input data or the input file. So for example, you want to include first name, last name, physical address, mailing address, if you have it, city, state, zip code, and also telephone number.

So, that's the input data. Then from a volume perspective, no, there is no limit to the number of records that can be provided, because if you think about it, many consumer portfolios consist of millions of records.

The last part of the minimum required, I just wanted to touch that C2B matching utilizes the same technology as B2B matching. We have the historical Match Reference File, contains billions of current and historical data, and those are really those alternative match points that we're using. So CEO, additional executives, executives. On a typical C2B match, the results are about 10% to 15% match, successful match rate.

George L’Heureux:
So Holly, before we finish up, let's talk takeaways. What would you want someone who's watching this or listening to this to kind of walk away and remember from this conversation?

Holly Reed:
I would say that C2B matching can help in a variety of use cases. We've talked about the financial institutions, we've talked about tech companies, professional designations. So if you think about it, it's an easy way to expand your lead pool. You can prioritize your leads on key data attributes, you can find new prospects. You already have relationships with them, so take advantage of it. I know that didn't come across right, but utilize those relationships to build upon them. Then lastly, reach out to your data advisory services team or your client director, we're here to help.

George L’Heureux:
Well, thank you, Holly. I appreciate you taking the time today to join me and to share your expertise on this topic.

Holly Reed:
Thank you.

George L’Heureux:
Our guest expert today has been Holly Reed, a data strategy consultant at Dun & Bradstreet, and this has been Data Talks. I hope you've enjoyed today's discussion, and if you have, I encourage you to share it with colleagues or friends. For more information about what we discussed on today's episode, visit www.dnb.com or talk to your company's Dun & Bradstreet specialist today. I'm George L'Heureux. Thanks for joining us, until next time.