Back in 2005, I proudly debuted my first audience database for a b-to-b media company focused on residential construction. Working with our fulfillment company, Iâ€™d pulled together all the subscribers from forty-some magazines and email newsletters into one consolidated database.Â â€śLook at this!â€ť I told the sales and marketing groups working with surveys and events and webinars. â€śRather than just pull a list for our home builder magazine versus our remodeler magazine versus our architect magazine, we can identify all the builders and remodelers and architects we reach across all our products.â€ť The response was pretty much:â€śWow, thatâ€™s great! But for this particular effort, we only want to focus on remodelers. So letâ€™s just use the remodeler magazine list.â€ťYes, for all our hype about audience integration, many b-to-b marketers still think of audience as a mailing list or email list for each product and brand. Maybe itâ€™s because weâ€™ve done such a good job of establishing brand identity for advertisersâ€”â€śIf you want to reach Group A, you have to use our Magazine A!â€ťâ€”thatÂ we find it hard to look beyond brand and see our audience as one pool of customers whom we touch through multiple channels.Even many of the new integrated database systems being offered by fulfillment and email vendors focus on audience as a collection of lists. Iâ€™ve worked with several systems that simply compile multiple lists, so that an individual involved with several products ends up with multiple separate records. Yes, those individual records are matched up, so when you combine lists youâ€™ll get a de-duplicated total. But the database is essentially just a big merge-purge, with no real integration of the records.That type of database is sometimes called a â€śunifiedâ€ť structure, as distinguished from an â€śintegratedâ€ť structure that builds a single consolidated record per individual. On a practical level, you can see the difference in the actual process of building a selection. Can you start by selecting all customers with a particular characteristicâ€”everyone in certain states or with a valid emailâ€”regardless of what list they are in? Or must you always start by selecting List A and then List B and then List C, and combining the three for a de-duplicated total?Both approaches have their advantages. A unified database is generally simpler to set up and manage. The structure makes it very easy to add new lists from multiple sourcesâ€”a big help for media companies struggling to combine contacts and registrations from different channels. You donâ€™t have to map each new source to update a consolidated individual record, with endless business rules for when one mailing address should override another or which business demographics have priority. The â€ślist firstâ€ť query process of a unified structure also matches the way many of us think about list selection. In fact, if all you really need from your audience database is the ability to create targeted lists for promotions, a unified database will more than meet your needsâ€”and probably cost substantially less in both time and money.However, if your company is looking beyond easier list creation, and hopes to move into the big data world of communication and advertising targeted by individual behavior, then a simple unified list of lists wonâ€™t take you too far. You will need a true integrated database structured around the individual audience member, with a single record that ties together all of that individualâ€™s registrations and history and activity. I think most b-to-b media companies are still struggling to find big data business models that work in our small industry-specific niches. Most donâ€™t need a true integrated audience database right now. But if you are picking a database solution today, keep in mind the structure you may need tomorrow.
One of the promises always made by consultants and system providers offering integrated audience solutions is â€śthe single view of the customer.â€ťÂ â€śYouâ€™ll tie together all of the ways you reach your audienceâ€”publications, newsletters, web traffic, webinars and eventsâ€”and be able to see how each unique member of the audience engages with you.â€ťItâ€™s a promise that puts stars in the eyes of b-to-b media executives. But beyond a few mysterious references to â€ścomplex algorithms,â€ť very little gets said about the nuts and bolts involved in creating that single view. Namely, how do you match up all those engagement records from dozens of files and registration systems to make sure you correctly identify each unique individual?Â Â Identifying the single customer used to have a much less glamorous nameâ€”de-duping. One of the most basic steps in the controlled circulation audit process was to check for duplication, and catching duplicate subscribers was (and still is) an obsession for managers and fulfillment companies. We even had inside jokes about it: One Halloween, the circulation staff at a big bto-b publisher dressed the same, wore name tags with their directorâ€™s name slightly misspelled, and called themselves collectively the "Dupes of Earl."We would de-dupe lists for new subscriber promotion against our existing database, and de-dupe the responses again as we added them to the file. Then we would run a suspect dupe match and do a clerical check to identify duplicates the computer hadnâ€™t caught. After all that, the auditor would find yet more duplicatesâ€”although we hoped few enough to keep within BPAâ€™s (supposedly top secret) auditing tolerance.Â Â What makes de-duping such a challenge? Well, to start with, we have all the normal variations in names and addresses that slip past a computer match. But in the b-to-b audience, it isnâ€™t enough to pin down the same name at the same address. What about individuals who had offices at more than one of their companyâ€™s plants? Those who switched jobs mid-year and showed up at two different companies? People who got magazines at their home address as well as the office?Â Knowing how much work it takes to identify duplicates in a controlled circulation list of 50,000 or so, Iâ€™m always floored when database companies brush by the question of how they will match up unique individuals across several million records drawn from multiple sources. And Iâ€™m even more dismayed when some admit that they simply rely on the new â€śunique identifierâ€ťâ€”an email address.At first it makes perfect sense: While everyone at the same business location shares one mailing address, each has a separate and unique email address. You cannot even create identical email addresses that point to two separate, unrelated inboxes. If you have one email, you have one individual. Right?Well, half right. Yes, one email address equals one inbox. But a surprising number of businesses still have inboxes shared by multiple individuals. And a much larger number of individuals use multiple addresses. In my last company, I did an analysis of the 1.5 million records in our corporate database, and discovered that nearly 20 percent of our audience members had more than one email address on file with us. And 4 percent of our email addresses were connected to more than one individual at the same company.Â Â If we had assumed each email represented a unique individual, we would have been hugely misled about the true size of our audience.For the purpose of sending out an email blast, it may be enough to de-dupe by address only. But to accurately identify one individual across many points of engagement, and deliver a single view of each customer, we canâ€™t avoid the tough, old-fashioned work we learned with controlled circulation. Accurate identification takes multiple levels of matching, multiple points of contact information, and usually some clerical clean-up after those â€ścomplex algorithmsâ€ť have done their best. Itâ€™s not glamorous, but itâ€™s a challenge we have to face to make our databases accurate and reliable.Who knows? Maybe someday, at a Halloween party, weâ€™ll see an integrated audience database team dressed up as the Dupes of Earl.
â€śThis was supposed to be a list of engineers at the car manufacturers. Why have you got so many people in here at supplier companies, like Bosch and Goodyear?â€ťIt was aÂ reasonable question. The BPA statement for our automotive industry magazine showed the circulation neatly categorized by vehicle manufacturers and automotive parts suppliers, and then by job. I should have had no problem delivering a list made up only of design engineers at companies like Ford, GM, and Honda.Or so you would think.As I explained to the sales rep fuming over the list heâ€™d requested, all those BPA numbers really represented was how many people checked a particular box on our subscription form and had one of twelve words in their job title. Yes, we had suppliers who checked the car manufacturer box, just as we had design engineers at Ford who checked â€śotherâ€ť because (as they would explain in precisely lettered corrections) â€śthere is no manufacturing at this location.â€ťMy ten year old son accidentally put it best, when he said something about Dad needing â€śmore describers for his magazine.â€ťÂ Â â€śThatâ€™s right, Matt,â€ť I told him. â€śI donâ€™t just need more subscribers. I need subscribers who describe themselves the right way.â€ťTwenty-five years later, that remains an issue with b-to-b audience databases. We pride ourselves on how much we know about our audiences. We can target by industry, by job function, by annual revenue, by products bought or specified. Yet almost all our information still comes from a controlled circulation process with inherent weaknessesâ€”not the least of which is relying on individual customers to categorize themselves.Who knows if some respondents are genuinely confused by our questionnaire, or just not paying attention, or trying to make sure they get a free subscription?Â The end result is people at big companies saying they have less than $100,000 annual revenue, while mom-and-popsÂ show up among giant multinationals. Auto glass repair shops mysteriously become window and door manufacturers; a Dennyâ€™s restaurant gets classified as a fine dining establishment.Or, as happened to me with a publication called Big Builder, hundreds of subscribers who workedÂ for the single biggest homebuilding company in the country, at the height of the housing boom, claimed their firm sold fewer than 100 homes a year.Maybe this wasnâ€™t such a big deal back when our primary focus was the BPA statement. After all, everyone dealt with pretty much the same errors, so our overall numbers were still valid for comparing one magazine to another. But today, our clients want to target the audience database in new ways, to find contacts in very specific companies and markets.â€śI want to reach the owners of the top 25 kitchen and bath remodeling companies in 32 metropolitan areas.â€ťÂ Thatâ€™s a typical request. A list of whoever checked the K&BÂ box on our qual form doesnâ€™t quite cut it.We need a new structure for the b-to-b audience database, one built around companies as well as individual audience membersâ€”a structure that can function as a business directory and contact management system just as much as a list for sending magazines and newsletters.For the Big Builder magazine I mentioned above, we stopped reporting subscribers by the answers they gave individually. Instead, we linked subscribers back to their companies, and then used published data to identify how many homes those companies built annually, how much revenue they had, and so on. Not only did this give us a more impressive BPA statement (and yes, the whole process was audited), but the information was far more accurate than what we were getting from individuals puzzling over a subscription form.Linking audience by company is not a simple matter. You have to struggle with endless variations and misspellings of company names, keep track of mergers and takeovers, figure out who is the parent or subsidiary of what. We need to push our fulfillment and database companies for tools to make that process easier and more accurate, and move away from the focus on the sacred qualification form.Our clients donâ€™t sell to people who check boxes. They want to reach specific companies, and the right people in those companies. Theyâ€™re looking to us to identify our audience in the same way.