Home Marketing Lessons Learned From a Twitter Bot

Marketing Lessons Learned From a Twitter Bot



Could you build a Twitter account completely from automated tools? Would anyone follow you? Or try to interact with you? Retweet you? Would you become an influencer, at least according to Klout?

Sadly, Andrew Hanelly found the answers to the above questions to be mostly yes. Over the course of several weeks earlier this summer, he took hundreds of Twitter accounts from various sources and constructed a new account, @contentasaurus. (Get it?)

He started with a list of more than 1700 influential accounts and manually followed them. That was tedious, but a one-time effort. Next, he then built a RSS feed to retweet bon mots from other influencers drawn from a series of digital media bloggers. He then sat back and watched the action. He deliberately didn’t respond to DMs or other requests from his own followers. “I let the conversation languish, because that’s what a robot would do.” (Many of you have a similar but perhaps inadvertent Twitter strategy by default. Or you might think this course of inaction is now a “strategy.”)

His bot-created account generated about 60 Tweets per day. That resulted in generating 443 click throughs, which in turn resulted in about 80 @mentions and 19 retweets. He then found out that his construct was popular, so popular that Klout gave it a score of 43.

Wow, a 43. It wasn’t all that long ago that I had a 43 Klout score, through the sweat of my own hands. That gives me, and hopefully you, some pause. Yes, Klout is an imperfect measurement and certainly people with scores lower than 43 might want to think about how to boost them and still be authentic to yourself and your brand. But it also shows that Klout really doesn’t measure anything meaningful either: there are people that I follow who have higher or lower scores, but that say something meaningful to me. Perhaps they don’t speak to your interests, or that you might find something else. That is what makes the Internet such an intriguing place.

We’ve covered the merits of auto-posting in earlier articles such as this one about how our community manager has gone to more manual methods on Facebook to nearly double the traffic formerly seen by the bots. But this experiment shows that you have to be careful about how you construct your social content, and how the proper mix of automated and manual methods could be a benefit. Tomorrow, we’ll post an article about avoiding bogus Twitter scams.

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