Building Your B-to-B Marketing Database

The single most important tool in B-to-B is, arguably, the marketing database. Without a robust collection of contact information, firmographic and transactional data about customers and prospects, you are at sea when it comes to customer segmentation, analytics and marketing communications of all sorts, whether for acquiring new customers or to expand the value of existing customers. In fact, you might call the database the “recorded history of the customer relationship.” So what goes into a marketing database? Plent 

The single most important tool in B-to-B is, arguably, the marketing database. Without a robust collection of contact information, firmographic and transactional data about customers and prospects, you are at sea when it comes to customer segmentation, analytics and marketing communications of all sorts, whether for acquiring new customers or to expand the value of existing customers. In fact, you might call the database the “recorded history of the customer relationship.” So what goes into a marketing database? Plenty.

First, let’s look at the special characteristics of B-to-B databases, which differ from consumer in several important ways:

  1. In consumer purchasing, the decision-maker and the buyer are usually the same person—a one-man (or, more likely, woman) show. In business buying, there’s an entire cast of characters. In the mix are employees charged with product specification, users of the product and purchasing agents, not to mention the decision-makers who hold final approval over the sale.
  2. B-to-B databases carry data at three levels: the enterprise or parent company; the site, or location, of offices, plants and warehouses; and the multitude of individual contacts within the company.
  3. B-to-B data tends to degrade at the rate of 4 percent to 6 percent per month, so keeping up with changing titles, email addresses, company moves, company name changes-this requires dedicated attention, spadework and resources.
  4. Companies that sell through channel partners will have a mix of customers, from distributors, agents and other business partners, through end-buyers.

Here are the elements you are likely to want to capture and maintain in a B-to-B marketing database.

  • Account name, address
    • Phone, fax, website
  • Contact(s) information
    • Title, function, buying role, email, direct phone
  • Parent company/enterprise link
  • SIC or NAICS
  • Year the company was started
  • Public vs. private
  • Revenue/sales
  • Employee size
  • Credit score
  • Fiscal year
  • Purchase history
  • Purchase preferences
  • Budgets, purchase plans
  • Survey questions (e.g., from market research)
  • Qualification questions (from lead qualification processes)
  • Promotion history (record of outbound and inbound communications)
  • Customer service history
  • Source (where the data came from, and when)
  • Unique identifier (to match and de-duplicate records)

To assemble the data, the place to begin in inside your company. With some sleuthing, you’ll find useful information about customers all over the place. Start with contact records, whether they sit in a CRM system, in Outlook files or even in Rolodexes. But don’t stop there. You also want to pull in transactional history from your operating systems-billing, shipping, credit—and your customer service systems.

Here’s a checklist of internal data sources that you should explore. Gather up every crumb.

  • Sales and marketing contacts
  • Billing systems
  • Credit files
  • Fulfillment systems
  • Customer services systems
  • Web data, from cookies, registrations and social media
  • Inquiry files and referrals

Once these elements are pulled in, matched and de-duplicated, it’s time to consider external data sources. Database marketing companies will sell you data elements that may be missing, most important among these being industry (in the form of SIC or NAICs codes), company size (revenue or number of employees, or both) and title or job function of contacts. Such elements can be appended to your database for pennies apiece.

In some situations, it makes sense to license and import prospect lists, as well. If you are targeting relatively narrow industry verticals, or certain job titles, and especially if you experience long sales cycles, it may be wise to buy prospecting names for multiple use and import them into your database, rather than renting them serially for each prospecting campaign.

After filling in the gaps with data append, the next step is the process of “data discovery.” Essentially this means gathering essential data by hand—or, more accurately, by outbound phone or email contact. This costs a considerable sum, so only perform discovery on the most important accounts, and only collect the data elements that are essential to your marketing success, like title, direct phone number and level of purchasing authority. Some data discovery can be done via LinkedIn and scouring corporate websites, which are likely to provide contact names, titles and email addresses you can use to populate your company records.

Be thorough, be brave, and have fun. And let me know your experiences.

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

Create a Bucket List

Whether you’re new to database marketing or a seasoned pro looking for some new idea to get your creative juices flowing, one of the most useful, and impactful, activities you can embark upon is to create what is called a “Bucket List.”

Whether you’re new to database marketing or a seasoned pro looking for some new idea to get your creative juices flowing, one of the most useful, and impactful, activities you can embark upon is to create what is called a “Bucket List.”

No, I’m not talking about a building a list of activities that you and a middle-aged companion wish to complete before you shed this mortal coil. I’m talking about taking a long, hard, and close look at your customers or prospects and getting to know them—really getting to know them—well enough to create broad classifications about who they are, what they do, what they like, and what affinities they share.

Remember, at the end of the day, database marketing is about sending out the right message to the right people at the right time—and, hopefully, achieving the desired response from the customer or prospect as a result. And without proper customer segmentation, this task simply cannot be done cost effectively, if at all.

Now, of course, there are many great customer segmentation models out there you can use. In a great article titled “Selecting a Customer Segmentation Approach” by Andrew Banasiewicz, Director of Analytic Services at Epsilon, four groups are identified: Predictive, Descriptive, Behavioral and Attitudinal.

Out of these four, the Predictive and Attitudinal models are arguably the most popular and widely used. Predictive is a model that uses value segments driven by customer purchase behaviors, extrapolating past behavior into future actions. An Attitudinal model, on the other hand, identifies affinity segments based on respondents’ expressed attitudes toward a company’s brand or products.

Now of course this list isn’t exhaustive and there are other models you can use. One popular alternative is Psychographic Profiling, which is used widely in the B-to-C space. In this model, consumers are assigned into groups according to their lifestyle, personality, attitude, interests and values.

Many B-to-B marketers, on the other hand, may prefer to use a segmentation model based on Firmographic variables, such as industry, number of locations, annual sales, job function and so on. Many software companies, not surprisingly, trend toward usage-based profiling, which includes variables, such as type of device used (desktop, tablet, mobile device), Operating System and so on.

One important fact that’s routinely overlooked is that successful customer segmentation requires taking a holistic approach. This includes aligning a firm’s segmentation goals to its marketing objectives and data acquisition investments. In other words, the data you have will determine not only which model you use, but also what marketing campaigns you’re able to run.

Now of course both data inputs and needs are in flux throughout the firm’s lifecycle. As Banasiewicz points out, for a firm in high-growth customer acquisition mode an Attitudinal model might work effectively for demand generation initiatives among qualified and segmented pools of prospects. Marketing campaigns in this scenario, we can assume, would speak to customer desires and affinities, with purpose of lead generation/nurture.

On the other hand, once the firm has acquired a large pool of customers, it’s not unrealistic to think that transitioning to a Behavioral model using inputs from past purchases will be more effective for running what are now CRM campaigns, focusing on driving lifetime value and repeat purchases.

Different groups not only have different attributes and attitudes, but consume different types of media. As such, they will respond to different types of offers, communicated in different ways and in different places. Where should a firm spend its marketing budget? Online display, email, direct mail, social media, print? … The choices are dizzying in today’s multichannel environment. Having a robust customer segmentation model can definitely help in the decision-making process.

Another important feature of customer segmentation is the realization that different customer groups can not only have wildly different demographic and psychographic identities, but very often will have strikingly varying lifetime values. To the surprise of some, a customer segment with a with younger average age will very often have a higher lifetime value than a group far senior to them, despite having far less disposable income to spend today. This may be based solely on the fact that the younger customers have, simply by being younger, many more years of being a loyal customer ahead of them. Taking this into account, many brands’ obsession with successfully penetrating the youth market should come as no surprise.

Now of course it’s easy to miss the forest for the trees, as customer segmentation is simply a means to an end, not an end in itself. Once you have broken your customers or prospects down into segments, the trickier (and for those who are not data geeks) more fun part of the equation involves devising incentive and reward strategies for each segment, and creating compelling marketing messages and collateral that can be used to get the message out across the various marketing channels. Knowing your customers, this part is a lot easier, which brings me full circle back to my point from the top: Create a bucket list.

Turning Email and Social Synergy Into Opportunity

In marketing — as in candy bowls — chasing too much opportunity can produce nothing more than paralysis or, at best, a dilution of the effort when it’s spread too thinly.

Too much candy isn’t good for you. As appealing as that big bowl of M&Ms looks right now, you know that if you get even get close to it, you’re going to regret it.

The same can be true in marketing. Working with a marketer who is merging three email programs into one campaign management application, I realized very early that there was huge opportunity for synergy of content as well as cross-selling and promotion between the three brands. The marketer was very excited about the possibility of managing the programs in a true CRM-driven fashion. That was only possible once the programs were generated off the same database and integrated at the subscriber level. Until now, the best this marketer could do was run separate promotions with similar offers, then try to compare the impact on revenue and unsubscribes after the fact. There were never very promising results.

With everything managed in one solution, the field is open for new approaches. A quick diagram of the combined customer base by brand showed a very slim overlap between them. At first glance, that feels like all upside — what a great opportunity to expose each brand to new, known audiences. It’s a big bowl of untouched delicious chocolate!

Synergy situations like this do create opportunity. That can be very exciting. But before you get too swept up in dreaming big, consider how important it is to prioritize those opportunities. In marketing — as in candy bowls — chasing too much opportunity can produce nothing more than paralysis or, at best, a dilution of the effort when it’s spread too thinly.

Consider these factors to help prioritize the opportunities before you:

1. Permission. Never assume permission. Period. First, it may be illegal depending on the countries where you market. Second, it’s bad marketing. There’s plenty of cross-sellling opportunities along the existing permission grants that you own today. At the same time, encourage subscribers to sign up for more types of messages from other brands in your preference center.

Lest you falter in your steadfastness, take this tale to heart: We had one marketer recently suffer a big drop in sender reputation and inbox placement. We traced the high complaints to a few campaigns promoting retail partners. Even though it was the marketer’s brand, template and “from” line, subscribers thought the messages were actually from the partners. Complaints were very high, even though the partners were trusted brands themselves. Subscribers knew they didn’t sign up for email from those brands and didn’t stop to check to see if it was a cross-promotion. They just clicked the spam button. Even if you own the partner brands, don’t assume your subscribers know that. I can’t emphasize enough how important it is to gain permission and earn it with every message you send.

2. Audience profile. You don’t have the time or resources to tackle every possible cross-promotion opportunity, so focus on the two to three that have the right criteria — reach, revenue and strategic importance. The latter is sometimes hard to gauge, but it usually involves business drivers, high-value customers or high-visibility projects. Balance those factors out in a spreadsheet so that you have real science behind your discussions. Make sure that every test has an actionable learning so that you can continue to improve and optimize.

3. Brand affinity. Just like in social marketing, customers who already trust you are the ones most likely to take your advice on cross-promotional purchases. Therefore, segment not just by permission status but also by the likelihood of brand affinity that will encourage cross-pollinization of the brands. For example, free online members may have a very low brand affinity and thus are least likely to welcome cross-promotions. Paid members who have purchased recently or have more than one product will be more likely to welcome upsell offers (and not complain).

4. Sales channel preference. A factor that became more important than we initially considered is sales channel — e.g., those who purchase in-store versus online. Not only are there demographic differences between the two, but there are also differences in the way email is used. For example, in this case email wasn’t very successful at encouraging in-store customers to purchase online, but it was effective in generating store traffic. Seems obvious now that we see the results, but of course the magic is in the discovery.

5. Customer life cycle. This is perhaps the most important factor. I’ve found time and again that marketers are way too confident in their assumptions about how interested consumers are in their offers. In fact, you have to start way back in the life cycle for cross-promotions, just as you would with new prospects (which, of course, many of these people are). Nurturing has to start with discovery and exploration. Too many times marketers hit prospects with offers well before they’ve established credibility with them or before they even acknowledge their own needs.

What have you learned from your efforts to create new revenue and customer satisfaction opportunities through data integration? Please share your thoughts and ideas in the comments section below.