I often joke that if Google’s motto is “Don’t Be Evil”, Exversion’s motto is “Be As Evil As Humanly Possible”. We are– to be frank– sneaky bitches who enjoy being sneaky bitches.
When your company is tiny, bootstrapped, and marked for death by just about everyone who matters in startup land being evil becomes a righteous pursuit, a sort of noble savagery that inevitably charms people who remember what it’s like to fight for the survival of your dream.
For me the distinction between (forgive the term) endearing evil and the sort of startup evil that creates backlash and bad PR is power dynamics. Are you being evil to protect your power base? To hoard more privilege than you need at the expense of others? Or are you being evil because you’re on the losing side of an inherently unfair game? Are you struggling against silly rules and resource-controlling systems that people with the right friends or the right names on their degrees get to bypass?
Is it a shock to anyone that this is not a meritocracy? No? Have we finally dispelled this notion? Good.
Sure, if I’m any good at my job there will come a time when Exversion will be big enough and strong enough to get it’s way and then it will fall on me to channel my natural sneakiness into other, less malevolent, pursuits … like … I don’t know, creating elaborate honeypots to annoy Chinese hackers maybe.
Thankfully today is not that day so I can spend my time passively highjacking my competitors Twitter accounts to promote Exversion.
First let me clarify exactly what I mean by “highjack”: No accounts were hacked, no passwords compromised, no spam was sent to anyone either via direct message, tweet or other sources. The victims of my shameless evil had no disruptions in their normal Twitter experience. The security and stability of Twitter as a service was not violated.
Here’s how we did it.
Like All Things Evil, It Started On Facebook
Someone, somewhere, at some point an article from DailyTekk landed on my timeline. I had never read DailyTekk before and soon found myself pulled into a vortex of links. What are the 10 best box-on-the-month subscription services I’ve never heard of? Top seven apps for organizing my life? Go on…
Page after page of articles listing apps I had never heard of but immediately wanted to try. I just kept browsing, going deeper and deeper into the site until I had ten tabs open with different DailyTekk articles.
At some point I came across fledgling Twitter engagement service Flounder. This is when the fun started.
Flounder is a neat little idea: it tracks the activity of your employees’ (or team members’) personal Twitter accounts and looks for interactions. If a conversation between a team member and another Twitter user goes longer than three interactions, Flounder follows the user your team member is talking to from your startup’s account.
Well, what could it hurt? I figure … I’m not especially active on Twitter anyway, let’s give it a try and see what happens.
While I was setting up an account for @exversiondata I realized that Flounder asks you for the Twitter accounts of your team members and never… actually … you know CONFIRMS that they work for you in any way. No authentication. No message that you’ve been added to a group. Nothing. So I added Jacek to my group. True, he left the company months ago… but since he still lists Exversion on his Twitter bio I figured he was fair game.
Then I got to thinking: there was nothing stopping me from putting my competitors on my Flounder team. That way I would be automatically reaching out to people passionate about data without having to do any work actually identifying them.
Oh but then I thought… wait. Why stop there? I can take this to a whole ‘nother level.
The Follow Back Is Dead, Long Live the Follow Back
When Twitter was new, following people was an excellent way to get them to follow back. Not so much anymore. But then follow back isn’t the real goal here. Getting more followers would be nice, but what we really want is to expose new people to Exversion. Get them curious, so that they click on the link in our Twitter profile and maybe sign up for an account. Alternatively they might click on our timeline and read a few blog posts on this blog, that would be good too.
The following acts as a first contact point. The user will get an email, letting them know we exist and telling them a little bit about us. For some that will be enough to piqued their curiosity … I read somewhere that it takes at least three touches to trigger a conversion. Then I read somewhere else it takes 8~10 touches. So whatever, let the bs marketing people split hairs over this, the point is one contact is not going to be enough. We need to follow up with these new friends.
Luckily, there’s a really easy way to do this: favorite their tweets. According to Adorer 30% of people follow your account after you favorite one of their tweets. This was actually not the first time I had heard something like this.
So I wrote a quick script that picks the most recent accounts @exversiondata is following, pulls their tweets, looks for the word “data” and favorites one tweet.
Then I registered a cron job to have this script run every day at 10 am.
As Flounder finds new people to follow, every day for two or three days those users get a notification that we have favorited one of their amazing, brilliantly written tweets. They don’t get spammed incessantly with unwanted contact. They just get pinged, casually and unaggressively a few times.
The first day using Flounder I noticed that @exversiondata had followed my friend Jay who I often converse with over twitter. So the damn thing works, awesome.
The second thing I noticed is that @exversiondata is suddenly following the twitter accounts of the guy who made Flounder and Flounder’s parent company– SNEAKY BITCHES!! Although I suppose given what I’m up to I don’t have the right to complain. LOL. Okay whatever, they can have a follow back if they want. I don’t mind.
By the end of the day I not only had a couple follow backs, but a query from someone who wanted to use our service for a big scary data project, and a handful of new followers not at all connected to this scheme (thanks Twitter algorithms!). The rate of follow backs stayed at 10%~15% throughout the whole experiment.
This was a big surprise. If you had asked me before this experimented started I would have said simply following someone was not enough to entice them to follow you back. People are too cynical, too bombarded with corporate messaging, there are too many spam bots on Twitter. It will never work.
But it does work, maybe not as well as it did when Twitter was new and people were more naive but if you’re targeting individual users most likely to be interested in what you’re doing simply following people does still have an impact.
And that’s not even the best part of this experiment. The most dramatic change was in traffic from Twitter, which more than tripled in a week. This is the data on referrals from Twitter, starting a month ago … can you tell when this experimented started?
Even more impressive is how much longer these the average visitor stayed on the site during this experiment:
Slow Burn Hacking
The growth was gradual, a few people pinged every day, but effective. After all, too much and we would have risked attracting negative attention from Twitter itself, which sort of defeats the point doesn’t it?
As much as we all wish for the excitement of instant explosions of growth, the slow burn is harder to track and more closely resembles legitimate user behavior. Because the bot doing the favoriting was only drawing from a pool of users identified through the networks of data companies it was unlikely to favorite something unsuitable by accident. In general it would only favorite three-four tweets a day and follow about 15~20 people a day hardly the kind of automatic management that tends to piss of Twitter. (Of course depending on how well this post does on HackerNews, we get be suspended tomorrow!)
Other than occasionally picking up the odd random account (DominosCareers? Really?) the system was really quite good at identifying people we would otherwise want to follow anyway and helped us participate in some really interesting data conversations.
Another fun, incredibly evil, side effect of this kind of hack is that the people who are most likely to tweet a company directly tend to be customers with problems. So you are pinging people right when they are most likely to consider alternatives to whatever they are currently using.
On the other hand, it’s hard to tell how effective this strategy will be outside the data community. Despite the great fanfare over “Big Data”, there are too many underserved areas. Only a handful of startups working on open data, version control, normalizing and cleaning data. A few more than that working on the collection of data itself. In other markets where every five minutes there’s another startup launching the same tactic may not have the same effect.
Still, what warms the evil core of my heart is the fact that the better your competition’s social media strategy is, the more effective they are at reaching out and developing conversations with potential customers, the easier it is for you to identify these people. Their outreach delivers the best potential evangelists for your project straight to your door, gift wrapped.