Exciting New Tools for B-to-B Prospecting

Finding new customers is a lot easier these days, what with innovative, digitally based ways to capture and collect data. Early examples of this exciting new trend in prospecting were Jigsaw, a business card swapping tool that allowed salespeople to trade contacts, and ZoomInfo, which scrapes corporate websites for information about businesspeople and merges the information into a vast pool of data for analysis and lead generation campaigns. New ways to find prospects continue to come on the scene—it seems like on the daily.

Finding new customers is a lot easier these days, what with innovative, digitally based ways to capture and collect data. Early examples of this exciting new trend in prospecting were Jigsaw, a business card swapping tool that allowed salespeople to trade contacts, and ZoomInfo, which scrapes corporate websites for information about businesspeople and merges the information into a vast pool of data for analysis and lead generation campaigns. New ways to find prospects continue to come on the scene—it seems like on the daily.

One big new development is the trend away from static name/address lists, and towards dynamic sourcing of prospect names complete with valuable indicators of buying readiness culled from their actual behavior online. Companies such as InsideView and Leadspace are developing solutions in this area. Leadspace’s process begins with constructing an ideal buyer persona by analyzing the marketer’s best customers, which can be executed by uploading a few hundred records of name, company name and email address. Then, Leadspace scours the Internet, social networks and scores of contact databases for look-alikes and immediately delivers prospect names, fresh contact information and additional data about their professional activities.

Another dynamic data sourcing supplier with a new approach is Lattice, which also analyzes current customer data to build predictive models for prospecting, cross-sell and churn prevention. The difference from Leadspace is that Lattice builds the client models using their own massive “data cloud” of B-to-B buyer behavior, fed by 35 data sources like LexisNexis, Infogroup, D&B, and the US Government Patent Office. CMO Brian Kardon says Lattice has identified some interesting variables that are useful in prospecting, for example:

  • Juniper Networks found that a company that has recently “signed a lease for a new building” is likely to need new networks and routers.
  • American Express’s foreign exchange software division identified “opened an office in a foreign country” suggests a need for foreign exchange help.
  • Autodesk searches for companies who post job descriptions online that seek “design engineers with CAD/CAM experience.”

Lattice faces competition from Mintigo and Infer, which are also offering prospect scoring models—more evidence of the growing opportunity for marketers to take advantage of new data sources and applications.

Another new approach is using so-called business signals to identify opportunity. As described by Avention’s Hank Weghorst, business signals can be any variable that characterizes a business. Are they growing? Near an airport? Unionized? Minority owned? Susceptible to hurricane damage? The data points are available today, and can be harnessed for what Weghorst calls “hyper segmentation.” Avention’s database of information flowing from 70 suppliers, overlaid by data analytics services, intends to identify targets for sales, marketing and research.

Social networks, especially LinkedIn, are rapidly becoming a source of marketing data. For years, marketers have mined LinkedIn data by hand, often using low-cost offshore resources to gather targets in niche categories. Recently, a gaggle of new companies—like eGrabber and Social123—are experimenting with ways to bring social media data into CRM systems and marketing databases, to populate and enhance customer and prospect records.

Then there’s 6Sense, which identifies prospective accounts that are likely to be in the market for particular products, based on the online behavior of their employees, anonymous or identifiable. 6Sense analyzes billions of rows of 3rd party data, from trade publishers, blogs and forums, looking for indications of purchase intent. If Cisco is looking to promote networking hardware, for example, 6Sense will come back with a set of accounts that are demonstrating an interest in that category, and identify where they were in their buying process, from awareness to purchase. The account data will be populated with contacts, indicating their likely role in the purchase decision, and an estimate of the likely deal size. The data is delivered in real-time to whatever CRM or marketing automation system the client wants, according to CEO and founder Amanda Kahlow.

Just to whet your appetite further, have a look at CrowdFlower, a start-up company in San Francisco, which sends your customer and prospect records to a network of over five million individual contributors in 90 countries, to analyze, clean or collect the information at scale. Crowd sourcing can be very useful for adding information to, and checking on the validity and accuracy of, your data. CrowdFlower has developed an application that lets you manage the data enrichment or validity exercises yourself. This means that you can develop programs to acquire new fields whenever your business changes and still take advantage of their worldwide network of individuals who actually look at each record.

The world of B-to-B data is changing quickly, with exciting new technologies and data sources coming available at record pace. Marketers can expect plenty of new opportunity for reaching customers and prospects efficiently.

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

The ‘A’ Word—Learn It, Love It, Live It!

I attended a seminar earlier in January held by the Direct Marketing Club of New York titled “Annual Outlook: What to Expect in Direct & Digital Marketing in 2012.” The main speaker at the event was Bruce Biegel, managing director at the Winterberry Group, a strategic consulting firm that focuses on advertising and marketing.

I attended a seminar earlier in January held by the Direct Marketing Club of New York titled “Annual Outlook: What to Expect in Direct & Digital Marketing in 2012.” The main speaker at the event was Bruce Biegel, managing director at the Winterberry Group, a strategic consulting firm that focuses on advertising and marketing.

For those of you who have never before attended an event where Biegel presents, I highly recommend attending one if you get a chance. He’s a highly engaging speaker with many interesting insights gleaned from years of experience in the field, and backed by the research and analytics of the Winterberry Group.

The focus of the presentation was a review of the marketing and advertising world of 2011, along with some predictions for 2012. According to Biegel, 2011 was the year in which many firms intensified their focus on reporting and analytics tools. For 2012, he predicted many marketers will finally begin to pursue true multichannel integration across their firms, driven by data, analytics and the quest for cross-channel attribution. He touched on the term attribution repeatedly, referring to it as the “Holy Grail” of multichannel marketing.

In a marketing sense, I define attribution—or the “A-word” for the purposes of this blog post—as the act of determining what marketing channel or budget was responsible for generating a particular action: be it a click, lead, order, etc. As a direct marketer, I just love this word. And you should, too. Attribution is where the rubber meets the road. Attribution is what separates the men from the boys, the measurable from the immeasurable, direct response from … well, branding. Not to disparage brand marketing, but I think I can speak for most—if not all—colleagues in the industry when I say that demonstrable attribution is really what has always separated direct response marketing from branding—analytics that essentially give us the ability to calculate the actual ROI of every precious marketing dollar we spend. Enough said.

But, let’s face it, there’s a dirty little secret in the direct response community that those outside of it might not necessarily be aware of. The fact is that attribution has not been all it’s cracked up to be over the past 10 years—and a far cry from an exact science, to say the least. We have the Internet to thank for that. To elaborate, let’s take a moment and turn back the clock around 15 to 20 years, and think back to a time in which the Web did not play such a prominent role in our lives. Back then, most direct response marketing was done via direct mail, catalogs and inserts, as well as DRTV. In this relatively simplistic world, customers could only really place orders using the return mailer or by calling a toll-free number. That was it. Since each piece was stamped with a keycode, attribution was as easy as: “Could you please tell me the five-digit code on the bottom right-hand corner of the order form” … and we knew with certainty why the sale originated.

Then along came the Web—and, with it, an entirely new channel for consumers to interact with their brands. And this is when things got confusing. Let’s say, for example, a consumer received a postcard or catalog from a company. In place of calling the toll-free number, he could instead go to Google and search for the website, find it, locate the products he’s interested in and place an order. Now who gets the credit for the sale? The direct mail team? The search engine marketing team? The catalog team? The email team? All of them? None of them? The fact is, there was really no scientific way to tell for sure. The gears of attribution broke down, creating a vast gray area of uncertainty where the worlds of traditional and new media converged. This was the direct marketer’s dirty little secret in the age of Web 1.0.

To deal with this mess, new techniques and technologies invariably emerged to bring some order to the chaos. Before long, many marketers turned to the concept of campaign-specific landing pages to send their cross-media (or cross-channel) customers to. At least this bypassed the regular website and kept and sales or leads it made in one bucket, separate from the home page and other Web traffic. This was a huge improvement.

Then other technologies like personalized URLs, or PURLS, entered the mix. Gimmicks aside, PURLs work because they are a tool for attribution—not because they give someone a link made out of their name. Sure, giving someone a personalized link is nice … but that’s only window dressing and obfuscates the real value of this cross-media technology. PURLs help marketers attribute activity to the direct mail channel. That’s it in a nutshell. Now of course, there are additional benefits, such as improved Web traffic rates resulting from personalized content, and higher website conversion rates due to a simplified workflow on a landing page that’s been optimized for this purpose alone. But the real value of this technology is attribution—and don’t ever let anyone else tell you otherwise.

Similarly, across other channels useful cross-media technologies emerged like QR Codes, which really solve in mobile the same issue marketers face on desktop Web browsers—namely, the inability to properly track and attribute cross-media actions resulting from their offline campaigns. When push comes to shove, sending individuals to purpose-built, mobile-optimized landing pages, personalized or not, enables precise tracking and measurement, not to mention a better overall user experience and, presumably, a higher conversion rate, too.

Looking forward, the next stage in attribution will most certainly need to deal with the advent of Web 2.0 and the world of social media. Seeing as firms are now making investments in social media strategy, CMOs are going to want to attach some kind of ROI calculation to the mix. Now, of course, you could pretty easily argue that it’s absurd to try to assign any type of ROI to social media in the first place. In that vein, Scott Stratten has a great blog post called “Things We Should Ask The ROI Question About Before Social Media” on UnMarketing that does just that pretty convincingly. But that’s an argument for another time and place. Regardless of whether you feel it’s a smart policy, I think it’s safe to say that where the marketing dollars go, pressure will ultimately follow to show value (ROI).

At the same time, regardless of what dollars are being spent and how these expenditures make CFOs hyperventilate, social media can and do generate sales for organizations. This is an indisputable fact and should not be up for debate anymore. What is in question is the ability of firms to track what happens in social media and attribute the activity to this emerging channel. As we speak, we’re starting to see the introduction of the first generation of effective tools (SocialCRM) that track social media interactions among pools of prospects or leads, and make them available to marketing teams for actionable analysis and follow up. Very cool stuff. But, of course, social media data are only one piece of a much larger puzzle, named “Big Data.” I briefly touched on Big Data in a previous post titled “Deciphering Big Data Is Key to Understanding Buyer’s Journey.”

Actually, on that note, I think this is a good place for me to call it a day. Not only am I running out of space for this post, but that last thought will make a great segue to my next post, which will address the amazing transformation that is taking place within many firms as they deal with the endless volumes of unstructured data (Big Data) they are tracking and storing every day. This wholesale repurposing aims not only to make sense out of this trove of data, but also to break down the walls separating the various silos where the data are stored, such as CRM/SocialCRM platforms, social media websites, marketing automation tools, email software, Web servers and more. Stay tuned next time for more on this topic.

Until then, I welcome any questions, comments or feedback.