A Powerful New Use for Your Bidders’ Email Addresses
Most auction companies maintain a list of their registered bidders—for email and direct mail. Some go further and sort those lists of buyers according to spend levels, frequency of auction participation, and/or particular asset categories. Those segmented lists become almost mandatory tools for attracting a company’s core auction buyers.
The rest of their auction budgets then typically go to educated guessing, trying to find more people who are (1) interested in what we have to sell and (2) comfortable with the auction method of transaction. That educated guessing might or might not prove efficient, depending on whether or not past bidders have been asked what media informed them about the auctions in which they participated.
Now there’s a tool, though, that falls in between your proven bidder lists and your educated guesses. It’s called a lookalike audience, and it’s a service of Facebook.
Here’s how it works. (You can watch the introductory video here.) Start with your in-house database of email addresses and/or phone numbers. Export any part of that list into a .CSV or .TXT file—with each prospect’s information on a separate line. Under the Ad Manager area of your company’s Facebook business page, you can then import that list. Facebook then takes from 30 to 120 minutes analyzing the profiles they find for the people on that list, comparing them across thousands of datapoint Facebook users create with their likes, shares, and posts. When that data crunching is complete, you will have a unique list of people who share a lot of common denominators with the people who already bid at your auctions. You can tell Facebook how strict you want to be with the sifting. In other words, rather than being connected by a few generic common denominators, you can require more datapoint to match.
Here’s the cool part: you can then have your Facebook advertising targeted to that list. More importantly, you can apply that demographic profile to any geographic area. So, if you want to find more people like your current bidders in the area you already cover, you can go after them more efficiently. If you’re conducting an auction in a new geographic area, you can overlay those common denominators there, too. You can pick a radius from a single city or multiple cities. You can select entire states, if you want to canvass a wider area.
John Schultz, one of my clients and one of the instructors for the new Auction Marketing Management designation, has found that Facebook can locate about 40-50% of the people on his bidder lists (because people like me use different emails for their Facebook than they do other purposes). From that 50% of your list, Facebook can find common denominators about 50% of the submitted contacts. So, you’re looking at roughly 20-25% of your list that will become the basis of your Facebook list. That means that the bigger your initial list is, the more accurate Facebook will be at finding matches. That low percentage isn’t a hurdle—unless your in-house list is small—because you’re going to be multiplying it later, anyway.
If you sell different asset categories, you can create and save different lists for each one. You can use the lists as often as you want, and you don’t have to pay extra for this service. Facebook looks at it as just another list selector.
You can still run your promoted posts for the general population, since Facebook makes finding outliers cheaper than in newsprint, direct mail, and other media. Now, though, you don’t have to rely on guessing through the demographics you individually select—for Facebook ads or for purchased email and direct mail lists.
Another benefit is that people who already see your marketing message in email will probably see reinforcing impressions when they check their Facebook. That’s one more interaction that could trigger a click to your website and eventually a bid.
Facebook isn’t the first company to offer this demographic extrapolation and replication service. They are, however, the first to do it for free. Also, with more than a decade of consumer data and more than a billion users, they have more datapoint to use for comparison.
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Photo purchased from iStockPhoto.com