Flowcharting Twitter Friendship Potential

David Bradley, otherwise known as @sciencebase, put together this adorable heuristic flowchart modeling his decision on whether to follow someone back when they follow him.  Says Bradley:

How do you decide whether to follow someone who has followed you? There are some basic filters you can use, like not following back obvious spammers and scammers and generally not following people with protected tweets unless you know them already.

I’ve created a flowchart to help you decide whether to follow someone who followed you on Twitter (click the image to get a fullsize view).

He then goes on disclaim, presumably for the benefit of readers who think they might not make it through this gauntlet:

Incidentally, I am not quite so strict as this flowchart implies so please do follow me as @sciencebase

Humorous. He’s actually probably quite liberal in who he follows back; he’s basically just checking for “genuineness” and “humanity”.

It turns out that this is a very good heuristic in general for an individual or a highly socially engaged business to follow, including the “maven, guru, entrepreneur, expert” and “lack of irony” accusations, when they want to vet new followers.

It also turns out that it’s really pretty easy to program a computer to determine which Twitter users are bots (automated) and which are human to 95% or better accuracy.  (Why most bots out there, many of them attached to services people are actually paying for, don’t make this distinction — and why it’s totally stupid and counterproductive that they don’t — will be the subject of a later post. –ed)

Much more difficult, as you might imagine, is determining “boringness” and making judgement calls on the “lameness” of an avatar.  Certainly the lack of an avatar can generally be deemed “lame”, but where do you go from there?  You start getting into the realms of computerized image recognition and computational linguistics, that’s where, and then it gets complicated and processing-intensive.  Not that we’re against that.  But for the purposes of this discussion, we’re going to stick with the low-hanging fruit.

Twitter provides quite a bit of low-hanging fruit to pick and process into some delicious heuristic jam.  Through the Web and through Twitter’s API, anyone can be provided with quite a few more indicators that help clue us in to our subject’s purpose in being on Twitter and their attitude toward engagement overall.

Tweets themselves qualify users in their personalities.  Here are some of the features of Tweets we use to model individuals on Twitter and evaluate their potential for interaction in your market:

  • @mention (reference to another individual on Twitter)
  • @reply (= @mention in the first part of the Tweet not shown to others who aren’t following the @mention’d party)
  • ~@reply (= @reply deliberately exposed to people not explicitly following the @mention’d party)
  • #hashtag (display of interest in an ongoing subject… OR an ironic gesture)
  • URL (full) (plus, whether the URL is accompanied by some other text or not)
  • URL (shortened — and type of shortener is important — see Brian Zarrella’s brilliant Science of Retweets report)
  • [blahblahblah]  (contains only a statement, none of the above features)
  • [...]  (nothing. lack of meaningful information is a significant feature)

Going to the trouble of marking off Twitter users in a more rich fashion goes a long way in producing meaningful quantitative data to inform your niche marketing efforts.  If your Twitter outreach results in 100 new followers who have mentioned “wine” in their bios, but who are 30% bots and %50 “social media gurus”, those 20 left over may well be worth your time — but how will you figure out how much time it will take to furrow out the false matches to the real customers?

AND, once you’ve gotten down to those 20, how do you feel about a conversion rate of, say, 5% bringing your total ROI on those 100 new followers to a mere 1 individual, if that?

If there were a tool to eliminate the need to spend the time and effort to investigate 100 leads just to acquire 1, would you try it?

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Inventing Your Market

The best business deal is one that has never been made before, and the healthiest businesses don’t necessarily compete, but rather innovate to pioneer and own a brand new niche.  Here is where technical innovation and creative market strategy intertwine: the best markets are the ones that haven’t yet been defined.

Just like that fanciful folk etymology about a certain Chinese character, inventing your market happens at the powerful Intersection of Crisis and Opportunity. 

If you have an awesome idea for a nifty widget, but you don’t know who would want it, you have a Crisis of having invested resources that marketing may or may not be able to solve.  And if you identify a novel group of people with unaddressed passion or pain, that’s the very definition of a market Opportunity, but one for which you may or may not be in a good position to innovate.

Your destiny as a potent force for Awesome starts with identifying this Intersection — the place where your expertise matches an audience that you can confidently interact with — and then choosing the Right Path leading to successful innovation — the place where your business stands uniquely apart from all others.  For a little while, at least.

So how do you invent a market, and what is the value in doing so?

Most businesses are competing for customers using very similar products or services, meaning that customers can only differentiate on a tangible like price or an intangible marketing asset such as brand loyalty.   Did you get into your business in order to become a supply chain optimizer and/or to spend 70% of your yearly budget on advertising to drill holes into viewers’ brains during the SuperBowl?  Those are the destinies for organizations that insist on direct competition.

How can there be new markets that haven’t yet been defined?

Simple: Most companies don’t quite get it, and are still competing for the ever-more-mythical "mass market consumer". 

The blanket Mass Marketing strategy worked well in an era of relatively low information, where consumers really could only differentiate products based on their labeling; but in the present era of high-information where people are generally so inundated that they use their social networks to filter information out for them, companies face not a homogenous national market, but a hyper-differentiated global market of markets that demand that their specific needs be addressed.  In other words, this is the era of micro-niches.

Do you suppose chocolate makers prior to this century ever imagined that there would be a market for unprocessed cacao beans — the stuff deemed so bitter and caustic as to absolutely require the addition of sugar and usually milk to make palatable — delivered as raw product straight to the consumer?  David Wolfe invented that market.

And the point is not that his company, Sunfood Nutrition, is making $X millions or giving Nestle a run for its money, which it certainly isn’t.  It’s that he managed to find the successful Intersection of his charisma-driven health-motivated marketing entrepreneurship and a certain customer audience of passionate health nuts to put his business in the category of Non-Competition, not to mention converting his own passion into a venture that funds many like-minded employees and keeps some possibly perplexed raw product suppliers very happy.

 

Finding the Right Path from that intersection towards your business goal does require some ingenuity, but floundering at this point is more likely a result of lack of organized information.  Very few keen innovators exist who simply operate in a realm of pure intuition, like some half-possessed twirling dancer in the music of market ideas, leading effortlessly time after time to brilliant business success.  Pure statisticians, on the other end of the spectrum, do very well at providing models of what has just happened, deriving patterns that make predictions about markets businesses are presently competing within, but aren’t particularly useful in predicting the market success of innovations that don’t exist, in markets that haven’t yet coalesced.

Rather, we see a movement towards honoring the power of the Intersection: those marketers who profess to half-scientist, half-artist mentality employ a clever combination of methodical research and creative interpretation.

So, no, your next awesome market strategy will not come from reading coolbusinessideas.com.  But the good news is that strategic market research that produces interesting results (that which you could act upon meaningfully) need not entail magical powers or a degree in statistics.

And the even better news is that picking a market exploration strategy based around Twitter has much to recommend it.  The short, obtuse explanation of Why: constrain the environment and you reduce your test load.

In blog posts ahead, we’ll be talking about how to sculpt your ideal market and court your ideal audience — focusing on Twitter, of course.  Stay tuned…!

Posted in theory | Tagged , , , , , , | 2 Comments

Openness and transparency

One thing Naomi and I have discussed a lot is openness and transparency.  We both feel that internal openness and transparency are key to running a sound ship, but we also like having  accountability and collaboration outside of our little bubble.  To that end, we’re working on an openness plan internally.  The first part of this is a commitment to Open Source wherever possible.

Both of us have spent a lot of time working on systems that are built on top of Open Source software: software that comes with its programming code, so you can tweak it as you need to.  follow logic is built on just that sort of software, and we’re keen on open sourcing components as we go.  Especially high priority is our infrastructure code, which isn’t all that much of a competitive advantage.  We’d love to share our twitter interface (it’s just a layer on top of an already-open library), the bit.ly code we use, and maybe some of our tricks for making everything run smoothly.

Subscribe to our RSS feed for more details on all this; we’ll have a proper announcements list set up once we do make a release, too.

Posted in FOSS | Leave a comment

Hello, World!

Hi folks, and welcome to the follow logic blog. My friend Naomi and I share a vision about making twitter a more effective tool for building communities. Her background is in marketing (and a bit of science journalism), while I’m more of a mathematics kind of guy. Between the two of us, we believe there are rational, logical, and socially conscientious ways to use twitter as a tool for community growth and getting your message out to people who would be interested.

We’ll use this blog to keep you apprised of what we discover as we run experiments, do market research, and build tools to find out what really works for twitter marketing and outreach. By following us here, you’ll learn what we know before anyone else, and can even help us define the cutting edge of twitter marketing by leaving your tricks in the comments.

We hope to be as entertaining as we are informative, but no promises. There’s only so many jokes that you can make with graphs (and, honestly, GraphJam has them all pretty well sewn up).

Posted in Uncategorized | Leave a comment
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