To Get the Best Prospecting Data, Use a Broker

In the data world, brokers represent the interests of the marketer, and develop a deep knowledge of the lists and data available from many sources. Here is a six-step process for finding and working with a data broker who will get you the best data for prospecting campaigns.

Database & CRMMarketers put a lot of effort into campaign planning, but sometimes their prospecting data selection comes as an afterthought. They may forget that the target audience is the single most important driver of campaign success. It deserves attention — and the support of an independent partner, namely a data broker.

In the data world, brokers represent the interests of the marketer, and develop a deep knowledge of the lists and data available from many sources. Here is a six-step process for finding and working with a data broker who will get you the best data for prospecting campaigns.

1. Find the Right Data Broker

Find a data broker with experience in your target audience category. Ask around. Industry associations are a useful source. Find out the names of brokers working with your competitors. Once you select a broker, make that person your full partner.

2. Interview Them Carefully

Interview broker candidates carefully, using the following questions.

  • Describe your experience with lists in my target audience category and my intended media channels.
  • Have your worked for any of my major competitors? (Paradoxically, a yes answer to this question is desirable.)
  • Who would be involved in ma
  • Who would be involved in managing my account, and what level are they?
  • Are you a member of The DMA (Data & Marketing Association)?
  • Do you have business partnerships with other marketing services providers? Explain.
  • Describe your commission structure, any other fees and your billing terms.
  • Provide three client references, including one from a former client.
  • What steps do you follow to ensure an ethical business process?

3. Describe Your Target

Use your market research, audience profiles and personas — whatever richness you can add to the description and the marketing strategy. The broker will convert your description into the language of data, and come back to you with a recommendation for lists and segments (selects) with the closest possible match to your vision. Build in enough time for the broker to research your options and prepare a recommendation for you.

4. Review the Recommendation Thoroughly

Here, too, ensure you have enough time for due diligence. Beware of the data card. Data cards provide details about the sources, uses and characteristics of the list, and are very helpful in determining its suitability for your campaign. But keep in mind that the card is designed as a sales tool. View it with a critical eye.

5. Test the Data

Take a sample of the data to test, if there’s time and if the universe of potential prospects is large enough. If you end up with a sizable file from a single list, consider developing a message specific to the characteristics of that audience.

6. Examine the Data on Arrival

If the data was sent directly to your agency or another third party, request a sample from them. Visually inspect the output for problems like transposed or missing fields, or names that appear to be duplicates. Compare a sample of records against your own database to check for outdated addresses or phone numbers. Ask your sales team to look at names in key accounts they manage.

7. Post-Campaign Review

Post campaign, review the results and share them with your broker. The more information you can provide about your campaign goals, your market, your products, your offer, your past results — the better the broker can perform. This is not the place to be cagey.

This article is excerpted from the white paper “How to Place an Order for Prospecting Lists and Data That Ensures You’ll Get Exactly What You Need.” Get your own copy here. A version of this article appeared in Biznology, the digital marketing blog.

Good News: B-to-B Prospecting Data Is More Accurate Than You May Think

Business marketers are always complaining about their customer data. “It’s pretty bad,” they’ll say. “It’s a mess.” But our latest study shows that prospecting data is surprisingly accurate — well over 90 percent.

PE0214_dataBusiness marketers are always complaining about their customer data. “It’s pretty bad,” they’ll say. “It’s a mess.” Over the last decade, my colleague Bernice Grossman and I have studied this issue, producing a series of five research reports on the quality of the data B-to-B marketers can rent or buy for prospecting purposes. Our latest study, published this week, shows that prospecting data is surprisingly accurate — well over 90 percent. We actually verified the accuracy by outbound phone, thanks to the call center at PointClear.

In past studies, our focus has been on both data quantity and quality, with the goal of giving marketers a sense of how likely they will be to reach all the prospects they want, with minimal waste, using the prospecting data provided by U.S. vendors today.

We were generally satisfied with the method we used to get at data quantity, where we asked vendors to provide company counts in specified sample industries and contact counts at specified sample companies.

But when it comes to data quality, we have long wished for a better method of verifying the accuracy of the company records provided by data vendors. Fortunately, an opportunity arrived with a generous offer from Dan McDade of PointClear to televerify the data samples. PointClear provides lead generation and management services, and houses a sophisticated and efficient call center run by Karla Blalock.

So we invited vendors of B-to-B prospecting data to participate, and we structured a research study to get at the accuracy of a statistically projectable sample of company records from the vendors. The five participants who agreed, and contributed a data sample, are Equifax, Harte Hanks, Infogroup, Lake B2B and Salesforce. Our sincere thanks to them all. (Harte Hanks has since sold its prospecting data business.)

The televerification process took place immediately on receipt of the names, but the analysis was more complex than we expected. Eventually, the skilled analyst David Knutson generously volunteered to work on the research data for us.

Methodology and Process
We asked the vendors to supply records as follows:

  1. All firms located in PA, GA, WI, OH and CO, with $25+ million revenue, HQ locations only.
  2. Company name, address and URL.

We planned to televerify firms that were common to all five participants. PointClear conducted a merge, and called the common companies in random order, stopping when 103 companies had been contacted successfully. The televerification took place during the period of August 28 to September 15, 2014.

The Research Results
Having asked for all headquarters sites of $25+ million revenue companies in five states, we found the company-level data to be generally accurate, above 90 percent.B-to-B Prospect Data Accuracy

Overall accuracy by vendor ranged from 92.9 percent to 97.8 percent. When looking at the accuracy by data element, company name was the most likely to be inaccurate, at 91.2 percent overall. There were some minor (less than 5 percent) accuracy problems with the street address, zip codes and URLs. The state data reports at a perfect 100 percent because the companies were selected on a state level.

Marketers can feel fairly comfortable that the prospecting data they get from vendors is likely to be reasonably accurate when it comes to company names, postal addresses and URLs.

Advice to Business Marketers Ordering Prospecting Names
B-to-B marketers should be prepared for a certain number of errors, due to the inherent limitations of merge/purge software, and software variations among vendors. Business addresses are complicated, with variations like P.O. box versus street address; headquarters versus divisions and subsidiaries; and legal name versus trade name. Marketers need to examine how their vendors maintain data at the company level, and then specifically ask for data to be pulled the way they want it.

Other suggestions for marketers to consider:

  • Take a sample of records for testing, and do your own televerification, before placing a large order.
  • Examine the incoming records for problems.
  • Use a trusted list broker who has a thorough knowledge of the particular vendor’s file.

We hope our research is useful to business marketers who are renting or buying data for finding new prospective accounts. The data may be a lot more accurate than you think.

A version of this article appeared in Biznology, the digital marketing blog.

Prospecting to IT Buyers: How Nine Data Vendors Stack Up

Buyers of information technology (IT) are one of the most valued audiences targeted by business marketers. Globally, these professionals spend $3.6 trillion on hardware, software and technology services. My colleague Bernice Grossman and I recently investigated the availability of prospecting data available to tech marketers for reaching this desirable group, and we found some surprises.

Buyers of information technology (IT) are one of the most valued audiences targeted by business marketers. Globally, these professionals spend $3.6 trillion on hardware, software and technology services. My colleague Bernice Grossman and I recently investigated the availability of prospecting data available to tech marketers for reaching this desirable group, and we found some surprises.

We asked twenty companies who supply prospecting data to business marketers to share with us statistics about the quantity and quality of the data they have on IT buyers in the U.S. Nine vendors graciously participated in our study-specifically, Data.com, D&B, Harte-Hanks, Infogroup, Mardev-DM2, NetProspex, Stirista, Worldata and ZoomInfo. Our thanks to them for letting us poke around under their hoods.

We asked each participating vendor to report to us on the number of companies on their databases in ten industries, by SIC code. We also asked for the numbers of contacts with IT titles in a sampling of twenty firms in those SICs, ten large enterprises and ten small businesses. Finally, we sent them the names and addresses of ten actual IT professionals (people whom Bernice and I happen to know, and were able to persuade to let us submit their names), and we asked the vendors to share with us the exact record they have on those individuals. The results of our study can be downloaded here.

This is the same methodology we have used in past studies on prospecting data available to business marketers—although this was the first study we have done on a particular industry vertical. Our objective is, first, to get at the question of coverage, meaning, the extent to which a business marketer can gain access to all the companies and contacts in the target market. And second, we want to show marketers the level of accuracy in the data available for prospecting-for example, is Joe Schmoe still the CIO at Acme Widgets, and can I get his correct phone number and email address?

The answers to these questions, in general, was YES. The data reported was surprisingly accurate, especially given how much business marketers complain about the data they get from vendors. And the coverage was wide, meaning there seem to be plenty of IT names in a variety of industries for us to contact.

But the data also revealed some interesting trends in business marketing in general and tech marketing in specific.

  • Prospecting data is being sold these days out of massive databases, which makes it far easier for marketers to select exactly the targets they want, by such criteria as title, company size and industry, irrespective of whether a “compiled” or a “response” name.
  • Company counts by SIC varied widely among the vendors, reminding us that data providers may have their own proprietary systems for flagging a company by industry code.
  • Job titles are getting fuzzier than ever. We found real IT professionals using titles such as Platform Manager and Reporting Manager-which makes it tough to know what they really do.

Given these developments, we urge our fellow marketers to probe carefully on data sourcing and categorizing practices, and to specify in great detail exactly what targets you’re going after, when buying data for new customer acquisition. And we suggest that you source from multiple vendors, in order to expand your market coverage potential. Happy prospecting to all.