SEGA is coming out with what might be the last, best hope for the Alien games franchise: Alien Isolation. It takes place 15 years after Alien and 42 years before the events of Aliens. It involves Ripley’s daughter (who was noted in Aliens but was cut from the movie) who is investigating her disappearance and winds up on a space-station that is, of course, inhabited by an Alien. In short it is a well designed (the screen shots look like they are from ‘alien’) reasonably intelligent, possibly worthy addition to the Alien canon and, especially, to the hit-and-miss legacy of Alien computer games.
That may or may not have interested you.
Why it interested me was this: I got an ad for it in my Twitter feed. Now, I have bought—and played—every Aliens game on the market. I even, kinda, enjoyed the hugely maligned Colonial Marines. I’m a sucker for Aliens games—but I hadn’t heard of Alien Isolation. When it appeared in my Twitter feed as a promoted Tweet I was intrigued.
I don’t have any gamers on my Twitter feed. I don’t blog (mostly) about computer games. I’m not active on any computer gaming fora. The Tweet was clearly a targeted advertisement—someone in the Alien Isolation marketing food-chain had paid money to get their message out to me: and they were right to do so. I’ll probably buy the game.
So the question is … how? Pitching Alien Isolation to me is the holy grail of direct marketing because:
- I was not aware of it. Maybe I shoulda been (and when it came out I definitely would have been)—but I am a pre-order market for them which makes it worthwhile.
- It is deeply interesting to me: I paid for Colonial Marines which I knew was bad. This is in my sweet spot for interest. It is perfectly targeted.
- It is not ‘obvious.’ While people who know me would, at very least, be able to guess I’d have interest in an Aliens game, (a) there is so far as I know zero evidence of that in my Twitter feed, (b) no tracking cookies or other browser-based intelligence that could give it away, and (c) remarkably little digital data on that at all (Steam would show two Aliens games in my library—but that’s about it).
What Does Big Data Know About You?
I’m reading Patrick Tucker’s The Naked Future. He’s a futurist who envisions a time in the not-so-far future (say, 5-10 years) where the vast amounts of telemetry we produce (our digital footprint) is able to expose our present—and likely future to everyone (well, at least us—and some big data providers, most likely). He covers things like OK Cupid’s predictions of love from online matches. He talks about crime prediction techniques that use ambient data to tell where the next crimes will likely be committed. He talks about a drone program that sees cities in real time.
There are chapters on how data mining could create custom educational plans, how earthquake prediction could work, and so on. The upshot of the analysis is this: even today—much less in the future—we produce enough data about ourselves for predictive engines to make some very good guesses about what we might like, who we might like, or where we might be located.
In the future this could improve dramatically.
On The Other Hand
On the other hand, almost NO ONE is doing as good a job as Twitter did with the Alien game. Let’s see:
- BP Driver Rewards. A better way to purchase gas … I guess.
- Drivers Auto Mart: A way to sell my car.
- T-100 Thyroid Support. I don’t need Thyroid pills … I don’t think.
- Small Valves Save Lives: An ad for replacement aortic valves without open-heart surgery
- Fidelity Investments: Financial services
- Equifax: Get a credit report
- Merril Edge: Online stock trading.
Now, I don’t drive a whole lot. I don’t need (so far as I know) heart valves or Thyroid pills. I already have credit protection so I’m not that concerned about my specific report. I will need a new car in a year or so—so the car thing isn’t stupid—but it’s not useful to me now. I already have a Merrill Edge account. In other words, it’s all either a complete miss (Merrill Edge wasted resources pitching to me) or an almost complete miss.
Amazon should be one of the best at predicting what I’d like. After all, they know what I’ve already spent a ton of money on—not just through Amazon—but through their Amazon Chase credit card. What do they show me?
- Some graphic novels in the series I’ve already got (a new East of West release)
- Some cell phone chargers. I’d researched them and bought a couple as gifts.
- Some Wi-Fi stuff, a keyboard, a phone head-set. I bought a new wireless router a few days ago. I got a keyboard months ago. I got a few phone head-sets a week ago.
- Pens that go on your keychain (I bought one two weeks ago). A key-chain (the one I bought a while ago)
- Some cables (I got one a while back), a headset for the computer (I got one a while ago)
- Some Transmetropolitan graphic novels (good—but I have them)
- A wallet (I got a wallet a few weeks ago)
- A bunch of Minecraft stuff (I got some minecraft stuff for gifts)
In other words: If I already bought it, Amazon wants to pitch it to me. This is stupid: If I already bought it, I don’t need it. Amazon should be one of the best and instead they’re one of the worst.
Twitter hit it off with the Alien game. They also want to sell me a subscription to shaving razors that interests me greatly. On the downside they pitched Sarah Palin’s something-or-other which isn’t a stupid guess—but is definitely a miss. I went and looked today and didn’t see any promoted tweets so there’s that (periodically I’ll get a World News Daily tweet promising some bring-down-Obama news).
Why are these (save for Twitter) all so bad?
Why Is Predictive Selling So Bad?
I’ve done some research. The reason it seems predictive selling is so bad is because Google isn’t doing it. What do I mean? Well, the problem is three-fold:
- The basic data … isn’t good. I went to AboutTheData—Axicom’s public service to see what they knew about me. You have to enter everything but your bank account number into that sight so I don’t suggest it—but for me?
- They got my birth date and gender right. My ethnicity is technically right—but I’m … erm … White Hispanic—not Hispanic.
- They have my marital status as single. Wrong.
- They have my political party as Republican: you can decide if that’s right or not.
- They don’t know much about my occupation—but they think it’s Professional / Technical
- They know where my house is—fine—but they have no idea what I drive.
- Household economic data is … catastrophically low. They clearly have no idea what either I nor my wife makes.
- They know nothing about my household data or interests.
- I tried the WatchDogs app—it’s for a game, but it’s good. It analyzes your Facebook data and finds: You—it can locate me with 92.8% accuracy, Who I care about “Collateral Damage”)—it found nothing. Stalkers (close FB friends—a few), Liabilities (people who tag me and thus expose me). Obsessions (it found my Hapkido martial arts school) and Scapegoats (it was people I know but am not close to and would ‘sacrifice’).
- IT grossly underestimated my salary, got my age and residence right.
- It says I’m most likely found in the gym (not bad)
- Google’s profile is pathetic. It has a correct age range and knows I like action movies—but that’s about it (NOTE: Google knows much, much more than that about me—but that’s what, apparently, advertisers see).
Secondly? The data is not being shared. Lots of players see part of the picture but only one (Google) sees nearly all of it.
- My favorite movies (Netflix knows—but is not sharing). Google sees my alert emails when Netflix sends me something. Knowing which movies I watch would tell you a lot about my personality and would definitely allow other movie makers to pitch me shows I might enjoy.
- What consumer goods I already own and how happy I am with them. I need to buy a TV and have searched it on the web and Amazon—but Best Buy doesn’t know this (nor will they).
- What my hobbies are beyond a narrow range. A human searching me on the web could find out, easily, about many of my hobbies and areas of interest. This would allow marketing. Google has much of this data—but is not leveraging nor sharing it with, for example, game vendors.
- What my aspirational goals are. I have been looking at cars I like—Google knows this. So do tracking cookies—but it would take someone doing some serious work to know what I expect to pay … and even worse, when I expect to buy one (I hope not for a year or two).
- What my reading interests are (Amazon knows this—or should, but is not being insightful with it). Amazon’s book suggestions are horrible. I’m well aware my favorite authors have many books out. Show me some books that I’m not aware of.
- What my pain points are—what I would pay to have done for me. The shaving razor subscription is good here (I hate shopping for razor blades). No one else is coming close (grocery delivery would make my day).
This upshot is this: We produce all this telemetry. Our phones track us every minute of the day. Our web-searches show our interests and thinking. Our email content shows communication and importance. Facebook shows how we want to present ourselves. Twitter knows what (short) messages get our attention—and which voices we are interested in. Amazon knows what happens when “interests level” breaches the “action” threshold. Steam (and Amazon) know which games we buy. Steam knows which games we play.
Netflix knows what our interests are for 1-2 hours a day (estimated). HBO knows if we’re watching Game of Thrones—so does Comcast.
The two problems are that (a) the data is not being shared and (b) there is precious little insight coming out of the recommendation engines these multi-billion dollar companies have. Netflix is trying—yes. But there’s no excuse for Amazon’s recommendations and Facebook’s ads. Where data does exist it is often out of date and patchy (Axicom) or simply contained (Facebook). When we use a data-gathering source in a limited way (LinkedIn) the picture may not be complete.
When we use a source comprehensively (Google) the data is unstructured. The tools to take full advantage of this do not yet exist.
Technology should solve the insight problem if we can get good enough sample sizes to mine and smart enough systems to ponder the mess of information we’re producing. We should see strides in that in a few years and big ones in a decade but I have to wonder. I think there is a fundamental missing piece here which is creativity. The idea that Twitter is searching the space of video games is interesting—but I’m not sure that’s actually what’s happening here. I don’t see any other evidence for it (no other games).
Machines can produce emergent behavior which feels like creativity but they do not yet actually create it. The horizon for making out-of-the-box leaps about what I’d want may be beyond the 15 year horizon I’m looking at here. The (very smart) TV show Person of Interest speculates that a machine that is capable of predicting human behavior has to be “at least as smart as a human” (in its own way, at least) and I think they’re maybe on to something there. If product placement was always handled with the skill that Michael Jordan played basketball, for example, we wouldn’t call it ‘product placement’—it’d just be ‘stuff we see in movies that we recognize.’
So there’s a level of skill in targeted advertising and a level of line-of-sight and a level of intuition and creativity that I think our current Big Data vendors are simply nowhere near approaching. I was frankly surprised at Axicom’s level of errors about me. I’m kind of insulted by Amazon. I think Facebook is patently naive. Twitter … interests me. Is a curated 140-character environment somehow more structured when it comes to understanding the user? Maybe so.
Is Google, for all their access to me, simply unable to get me a game I’ll almost surely buy? Or were they just not approached with the ad? They’ll see this post. Their massive data-banks will store it. Their engines will analyze it … and they’ll learn … nothing? I think we’re probably more than a decade away from Patrick Tucker’s Big Data Utopia.