Tag : artificial-intelligence

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226: Can Facebook Ads Settle Your Office Arguments?

I utterly admire the tolerance for speculation that auctioneers demonstrate day in and day out. My clients and their peers work so very hard at just the chance they might get a decent payday. Few professions I know swing for so many home runs, especially when knowing there’s already a strike or two on much of what we’re selling. As someone who gladly squares up every day for bunts and singles, I don’t know whether to chalk bid caller risk-tolerance up as bravery or insanity.

But that seemingly inherent trait of the folks I serve comes in handy when there’s a disagreement about the content of our advertising. Several of my clients are uncomfortable using text that gets my other clients cheap clicks—words like “liquidate” and phrases like “Buy at YOUR price!” And other customers want details or phrases in their ads that I find superfluous or even counterproductive. 

For almost two decades, I have often acquiesced to the man or woman signing my check (or lost them as a client). Over the last few years, though, I’ve found a compromise that appeals to the go-big-or-go-home mindset of the auction industry. I make a wager of sorts with them: let’s try the advertising BOTH ways, and let the best-performing version win.

Facebook ads offer A/B testing on steroids. At the time of this writing, Facebook’s Dynamic Creative tool allows advertisers to test up to 1,250 versions of a single ad per audience. We can include up to 10 photos or photo collages in the image area, and we can include up to five versions (each) of the sales copy, the bold headline, and the secondary headline. 

On a typical ad campaign, I’ll use multiple options each for the image area, the bold headline, and the secondary headline. (I rarely upload alternate versions of the sales copy.) As my regular clients can attest from my launch reports, it’s common for us to leverage between 18 and 45 versions of each ad in a campaign. Facebook’s artificial intelligence tests each variation to learn which one(s) get the most efficient clicks and then adapts each ad accordingly. So, our ads for the same auction with the same text options can look different to different audiences because each group of people responds differently to different photos and text. That’s especially helpful when we’re advertising the same asset(s) to multiple prospect pools.

Using this tool, we can test whether “liquidate” works better than “sell” or whether “no reserves” outperforms “regardless of price.” I regularly test “online auction” vs “online bidding” as well as “bidding closes” vs “bidding ends.” If it were my auction, I wouldn’t put the location in ads for online personal property auctions, but I’ll gladly include the pickup/shipping location as an option below the photo. If I’m wrong, I’m happy to be wrong. It’s hard to argue with thousands of people who respond to the location instead of my other headlines. The same holds true the other way. If an audience of 283,000 people choose my “Everything must go!” over the location, well then location isn’t as important for that auction as the auctioneer had thought.

Variable content makes advertising democratic in that it allows the consumer to determine how our ads appear to their peers. Without knowing it, potential bidders are voting for the best version of each ad—just by whether or not they engage with the option they’re shown. They’re the best people to settle your advertising disagreements because they’re the ones determining your commission.

Manager is insulting his colleague in an office

So, it goes back to the “person signing the check” after all; and I’m here for it. Facebook’s artificial intelligence won’t help you solve disagreements over whether the new company truck should be Ford or Chevy. The Dynamic Creative tool won’t help you and your partner decide whether or not to keep your mistake-prone nephew on staff. But it will help you settle disagreements over photos and headlines—and give you cheaper Facebook ads with only the best bait on your hooks.

Stock images purchased from iStockPhoto.com

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219: A Safety Net for When I Guess Wrong

Within the span of several weeks, I’ve advertised not one but two complete liquidations of antique stores (for different clients in different states). Both had quality vintage items. Both had catalogs brimming with a large number of lots. But only one became a prime example of why I prefer to advertise with a safety net.

I launched the ads for the first antique store auction on a Thursday afternoon. When I checked my Facebook analytics the next morning, I did a double take. One of the ads was getting results at $1.10 more per click than the other ads in the campaign. I screen captured the stats and emailed my client. I asked if they’d like me to shift some of its budget to the other ads or if it was worth paying extra for these prospects’ clicks. I rarely hear how the estate and antique auctions I advertise fare, and often big-fish buyers in other asset categories are worth the extra cost to get them on the line. (Also, I didn’t have a lot of personal property experience in that part of their state.) So, I leaned on the client’s experience.

The answer came back to let the ads run as they were originally budgeted. When the campaign closed, that ad finished with a cost per click 19.5 times that of the other ads and a cost per landing page view of 20.3 times all of the other ads. The click-through rate finished at a meager 0.66%, while the other ads averaged 7.65%.

So, who were we targeting with that expensive, inefficient ad?

People with occupations connected to antiques. The line of thinking: the prospects most likely to purchase a store full of high-end antiques are people who already own or work in another antique store. We guessed wrong. Thankfully, the other ads carried the day; and the campaign averaged 7¢ per click, even with the expensive ad in the mix. In fact, the most efficient ad for that auction didn’t target any interest categories related to antiques or collecting.

My client wouldn’t have guessed that. But Facebook’s artificial intelligence engine would. And did.

Robots to the Rescue

The longer I advertise on Facebook, the less I trust my strategic instincts and the more I lean on data. I get surprised just about every week by which ads do better than others in the same campaign. Same photos. Same headlines. Just different audiences. Audiences I expected to jump on ads don’t. Prospects that would make sense to most people with any marketing experience prove themselves indifferent to the quality items shown in professional pictures. I can’t tell you how many times I’ve A/B tested images and been shocked by what pictures proved the best bait. Hint: they weren’t the “money shot,” the brochure cover photo, or the main image on the client’s website.

A global artificial intelligence engine, fed by tens of thousands of impressions and thousands of clicks per auction, regularly surpasses my educated guesses. Three days of machine learning can outperform strategy informed by almost 8,000 auctions advertised over 20 years across 49 states. It’s humbling to be proven wrong. At the same time, it’s exciting. That means we as marketers can now adapt our advertising in real time to fickle realities and head-scratching trends. 

Robot Consultants for Print Media

I still have clients who refuse to leverage paid social media advertising. Others only throw spare budget at it. They either don’t believe it can bring them buyers or have yet to see a buyer come from it. I can’t argue against their experience or results, but I offer this counter thought: what if you used Facebook to learn what kind of audiences respond to your ads, what kind of headlines work best, and what images get the most people to your website? What if you then adapted your other media to what’s working in your Facebook ads? Your print media, signs, and email marketing could grow more effective because of the immediate feedback that social media ads provide.

Recently, a client asked for my opinion on a change to a tiny plat map in several small newspaper ads. I told her that I wouldn’t recommend using plat maps at all—particularly small ones—in newsprint. I’ve learned from Facebook ads that people typically respond to ground photos, drone shots, and oblique imagery at higher rates than plat maps, orthogonal aerials, and multi-parcel outlines. (Tract layouts are tertiary information for buyers; they don’t need to know boundary shapes until they decide they are interested in what’s inside them.)

It’s just opinion until you have data. 

Train Your Own Robot

I’m not telling you to avoid using aerials. I’m suggesting that you A/B test them yourself. Test photos vs videos, collages vs slideshows, ads vs promoted posts. Test headlines. Test spending more in the first half of a campaign vs the second half. Test whether you should advertise to past web traffic or past Facebook interactors or neither.

This pragmatism most helps the auctioneers who focus on the same one or two asset categories. It’s easier to see trends when most of your auctions are like-kind. If that’s not you—if you are a generalist or your specialty is a geographic area more than an asset type—I highly recommend you team up with a specialist. That can be a broker, a dealer, a journalist, a collector, a vendor, or another auction company. The added expense on your current auction could give you tremendous insight for future auctions. It might even pay for itself on the auction at hand because guessing wrong can be expensive. 

Thankfully, Facebook’s robots can make mistakes less costly—if we let them do their work. If we’re humble enough, we can have a safety net for the high wire act of advertising auctions. 

Stock images purchased from iStockPhoto.com