Twitter’s Monetization Model: On the Mark, or Off-Target?

As Twitter moves to pilot its first experiments in monetization, it might be interesting to speculate on its prospects for success. To help, I'll go through some of the elements of success and failure that have been proven in the last twelve years or so of online advertising experimentation. Without all of these elements being in place, ad-supported models have tended to fail.

1. Large enough audience to matter. Wrapping some ads around content or functionality geared to a relatively small audience is tricky on a number of levels. First, no one in the press cares, and investors don't care. Most importantly, advertisers and agencies don't care, since there's not enough to buy, so you get lumped into remnant or at least underpriced network inventory unless you've got a really smart little sales force. Second, any hiccup gives you a greater chance of killing the golden goose of whatever you wrap the ads around. Third, you lack statistically significant data for testing and refining, so it's hard to perfect. Fourth, related to the third point, dipping a toe into the water becomes difficult. Large publishers can run tests without alienating anyone as they test the model in a small sliver of the content.

2. Targeting by keyword. Publishers and ad mavens have bent over backward to insist that targeting can be based on concepts, personalization, demographics, and factors other than keywords. Even Google, the King of Keywords, began fairly early in its attempt to paint the keyword as only one sub-facet in the global effort to better align advertising with user tastes and intent. (Bonus: that effort to blend into the woodwork might have helped Google in court if trademark and patent lawsuits really started to escalate out of hand, or if they started losing cases so badly that they'd need to substantially revise their business model ahead of schedule.) Deny it all you like, but keywords still "click" with advertisers. Users like them too, because it's a way of seeing relatively relevant ads without feeling too creeped out. Keywords triggering relevant text ads and offers are the display-advertising-in-content cousin to permission marketing as it was conceived by Seth Godin for email. Somewhere, a line can get crossed. Keywords do a really great job of helping advertisers and users connect without that line being crossed as often.

3. Doesn't get in the way, or even at times enhances the experience. Advertising is a necessary evil to some, but to a substantial part of the population, it's a buying aid or even a cultural experience. Glossy ads in fashion magazines are part of the "art" and "positioning" and are seen as less intrusive than advertising that really "gets in the way" of reading an article online. The same goes for billboards by the highway: an eyesore to some, they're a part of cultural history to others -- and hence, provide free buzz over and above the advertising cost. Burma Shave was before most of us were born, but chances are, you've heard of the roadside signs.

4. Is in a place online that people willingly go to or are addicted to, rather than being an app that is a bit cumbersome to use, take-it-or-leave-it, overly incentivized (paid in points or cash to "surf,"), or weakly appreciated but maybe a flash-in-the-pan. Related to this, the user base has to understand what the owners plan to do around advertising and what kind of "trade-off" they can expect. Do they get involved in using something for one reason, then find it's infected their user experience or device (i.e. "scumware")? Or is the format and the trade-off relatively transparent?

5. Isn't susceptible to "banner blindness". For the time being, we can consider this one relatively unimportant, as initially, enough advertisers will be lining up to try new things where the audience is big enough and attention can be grabbed. But performance marketers are turned off by ads that don't perform, and historically these types of ad formats have had limited upside when compared with personal, anticipated, and relevant communications (especially when the latter are connected with keywords). You can be "big" with the support of brand-building advertisers, but with the approval of direct marketers on top of that, you can be huge... because then any advertiser, large or small, can justify it to themselves or to someone on their board of directors. And agencies too can come up with those justifications.

To look at some quick examples:

  • Intrusive or oversized display ad formats -- leaderboards, "popovers," garish animations, etc. -- have had mixed success. They've driven online advertising to a degree, but somehow got surpassed by little old search, despite their reach. That's because they fail on counts 3, 4, and 5, and aren't even all that great on 1 and 2.
  • Weird apps like Pointcast, eTour, and Gator eventually fail because people uninstall the apps, don't install the apps, etc. Performance is uneven and users squeal. To incentivize users to do things they wouldn't otherwise do, you either deceive them or pay them too much (thus killing profit). Fail all around.
  • Point 4 relates to Facebook -- in both senses. The network effect and addiction factor actually outweigh the fact that Facebook has been particularly brazen in doing wacky, unpredictable, privacy-invading things to its users. Facebook is very strong on point 1 and has point 2 covered also. Because its audience is very large, it can be cautious relating to points 3 and 5, monetizing below "potential," thus leaving long-term potential on the table. Huge win.
So how about Twitter? Twitter's scheme sounds like it will largely succeed on points 1 through 4. The ad revenue, once disclosed, will appear pitifully small for the first year or two. As long as trust is built gradually and testing provides insight, that revenue should pyramid up over time.

Some will question whether users will remain addicted to Twitter long term. Facebook is an entire social environment, and Twitter still feels like a "feature," a quick hit, despite a large user base on paper. That one hangs in the balance. Perhaps the litmus test for any would-be top-tier destination would be: are users choosing to download and keep their favorite mobile app related to that content, brand, function, or community, in the most accessible place on their mobile device? Will people get bored with them and stop? Will ads be easier to ignore on mobile devices? Will people look for versions of apps that allow them to ignore ads? (That's where point #3 really comes in.)

Change will be rapid, but based on these criteria, it appears that Twitter has the correct fundamentals and the right strategy in place for a long-term win. But if Facebook has a two-year head start here, you still have a nagging feeling that Twitter just needs to keep hitting certain user targets and to look reasonably dangerous revenue-wise, for the more realistic goal of selling the company to Google or Facebook.

Don’t Go to Google, TripAdvisor, or OurFaves for Restaurant Reviews

If you come to my town, where's the best place to go to look for that perfect restaurant, or opinions about a place you're considering dining at? Me. Seriously.

And maybe a few of my friends.

We know the truth.

You can sometimes get some of that truth from Toronto Life and Zagat.

Once in awhile, we'll maybe go write a review on Yelp. But probably not. If you ate at 50 places a year and 30 of them are really good, you'd tire of writing it up.

So, if you go to Google's review aggregation that includes results from TripAdvisor, OurFaves, and Google itself... you'll see a bunch of inexplicable one-star reviews for some of the best restaurants in the city.

"I could barely see my food..." Have you heard of ambience?

"The staff was unfriendly..." ... after you put ketchup on the filet of sole.

"Cramped..." Sorry it isn't the Rainforest Cafe.

Don't get me wrong: I'm a big fan of user-generated content and recommendations. Unfortunately, when you go to TripAdvisor, you often have to wade through the most inexplicable, knuckle-dragger "reviews" of some of the best hotels and restaurants known to mankind.

It's also an interface issue with Google's review aggregation, though. The Harbord Room actually averages four stars on Yelp... but you wouldn't know this from Google's tally, which makes it look like there are a lot of dissatisfied visitors, and the average looks like it's just over one star.

You know what? Just let me make the reservation, and if the place is no good, I'll take full responsibility. :)

In the meantime though you could trust good reviewers like this guy.

Don’t Go to Google, TripAdvisor, or OurFaves for Restaurant Reviews

If you come to my town, where's the best place to go to look for that perfect restaurant, or opinions about a place you're considering dining at? Me. Seriously.

And maybe a few of my friends.

We know the truth.

You can sometimes get some of that truth from Toronto Life and Zagat.

Once in awhile, we'll maybe go write a review on Yelp. But probably not. If you ate at 50 places a year and 30 of them are really good, you'd tire of writing it up.

So, if you go to Google's review aggregation that includes results from TripAdvisor, OurFaves, and Google itself... you'll see a bunch of inexplicable one-star reviews for some of the best restaurants in the city.

"I could barely see my food..." Have you heard of ambience?

"The staff was unfriendly..." ... after you put ketchup on the filet of sole.

"Cramped..." Sorry it isn't the Rainforest Cafe.

Don't get me wrong: I'm a big fan of user-generated content and recommendations. Unfortunately, when you go to TripAdvisor, you often have to wade through the most inexplicable, knuckle-dragger "reviews" of some of the best hotels and restaurants known to mankind.

It's also an interface issue with Google's review aggregation, though. The Harbord Room actually averages four stars on Yelp... but you wouldn't know this from Google's tally, which makes it look like there are a lot of dissatisfied visitors, and the average looks like it's just over one star.

You know what? Just let me make the reservation, and if the place is no good, I'll take full responsibility. :)

In the meantime though you could trust good reviewers like this guy.

Can Search Engines Sniff Out "Remarkable"?

I never tire of listening to experts like Mike Grehan speaking about the new signals search engines are beginning to look at, because it's so important to bust the myths about how search engines work.

To hear many people talk, today's major engines are faced with little more than a slightly-beefed- up, slightly larger, version of a closed database search. Need the medical records for your patient Johnny Jones, from your closed database of 500 medical records, just type in johnny or jones or johnny jones, and you're good to go. Isn't that search, in a nutshell? It is: if you can guarantee that you're referring to a nutshell like that. But with web search, it's nothing like that.

The World Wide Web now has a trillion pages or page-like entities... that Google knows about. (They don't know what to do with all of them, but they'll admit to the trillion.) Some observers estimate that there will soon be five trillion of these in total, too many to index or handle. Who knows, maybe 10% of that could be useful to a user or worthy of indexing. But until some signal tells the search engine to index them in earnest, they'll just sit there, invisible. That's out of necessity: there's just too much.

The difference isn't only quantitative, it's also qualitative. User queries have all sorts of intents, and search engines aren't just trying to show you "all the pages that match". There are too many pages that match, in one way or another. The task of measuring relevancy, quality, and intent is far more complex than it looks at first.

And on top of that, people are trying to game the algorithm. Millions of people. This is known as "adversarial" information retrieval in an "open" system where anyone can post information or spam. The complexity of rank ordering results on a particular keyword query therefore rises exponentially.

In light of all this, search engines have done a pretty good job of looking at off-page signals to tell what's useful, relevant, and interesting. The major push began with the linking structure of the web, and now the effort has vastly expanded to many other emerging signals; especially, user behavior (consumption of the content; clickstreams; user trails) and new types of sharing and linking behavior in social media.

This is a must, because any mechanical counting and measuring exercise is bound to disappoint users if it isn't incredibly sophisticated and subtle. Think links. Thousands of SEO experts are still teaching you tricks for how to get "authoritative" inbound links to your sites & pages. But do users want to see truly remarkable content, or content that scored highly in part because someone followed an SEO to-do list? And how, then, do we measure what is truly remarkable?

Now that Twitter is a key source of evidence for the remarkability of content, let's consider it as an interesting behavioral lab. Look at two kinds of signal. The first is where you ask a few friends to retweet your article or observation, and they do. A prickly variation of that is where you have a much larger circle of friends, or you orchestrate semi-fake friends to do your bidding, with significant automation involved.

But another type of remarkable happens when your contribution truly makes non-confidantes want to retweet and otherwise mention you. When your article or insight achieves "breakout" beyond your circle of confidantes, and further confirming signals of user satisfaction later on when people stumble on it.

Telling the difference is an incredible challenge for search engines. Garden variety tactical optimization will work to a degree, mainly because some signals of interest will tend to dwarf the many instances of "zero effort or interest". But we should all hope that search engines get better and better at sniffing out the difference between truly remarkable (or remarkably relevant to you the end user) and these counterfeit signals that can be manufactured by tacticians simply going through the motions.