Twitter Bots & Brands – Fraud Wars

twittor-bots

There has been a lot of talk over the years about bots on Twitter. Since we invented instant transactions from a single social media action, with Chirpify itself being a bot on Twitter since 2011, I thought I’d share some thoughts on Twitter bots and brand campaigns. Today there are a LOT of bots on Twitter, and as this recent Adage article points out, brands are worried about it, and concerned about automation in general. Since automation of social media marketing is inevitable, as it was with email and other marketing channels, brands need to get comfortable with this fact.

As the article points out, marketers have seen their campaign metrics be skewed by bot accounts engaging with their campaigns.

The advertiser had asked Twitter if any of the activity was from bots, which Twitter denied. So the agency decided to scrutinize the campaign itself. It turned out that between 10% and 20% of Twitter activity on that particular campaign came from bots, according to the agency executive.

10% – 20% is a lot of “fake news” to handle as a marketer. It is especially frustrating when Twitter itself has provided no tools for marketers to avoid this. Since we’ve literally been a currency conversion between Twitter and financial and loyalty programs for 5 years, we’ve been forced to build tools specifically designed to avoid fraudulent bot activity. Our brand’s campaigns literally ignore bot accounts like they don’t even exist, not responding to or enabling them to transact or earn points, enter contests, get content, promo codes, or any other marketing outcome enabled by the platform. They do this utilizing the following features:

Automatic Bot Detection

Our rules engine can govern campaign engagement by several criteria, including geo-fencing, influence, and frequency. Using the influence filter brands can specify how many followers an account needs to participate in their campaign. They can also specify that their campaign ignore other bot identifiers like “eggheads” (accounts without profile photos), or accounts that have not tweeted much, or accounts that do not match other custom campaign or user criteria set by the brand.

Member Verification

Since Chirpify is integrated with membership databases, our platform can lookup customer details based on their social identity. So, if a brand doesn’t want any non-members to participate in a campaign, they can block them.

Frequency Limitations

Our rules engine can also limit participation in campaigns based on frequency, for example limiting contest entries to one Twitter account, or making accounts perform multiple actions to be rewarded, single use promo codes, and more.

Targeting

Brand campaigns often involve a call-to-action, instructing people to set off a social action like sharing a photo to be rewarded. When they do, our platform performs marketing automation, rules checking, automated smart responses and rewards. However, more brands are starting using our platform to mine social data for topics to surprise and delight consumers with a DM containing a reward or content. In this case, our dashboard enables brands to aggregate all posts and accounts containing the topic, and review all posts for quality before responding and rewarding. This gives marketers manual human control, while still saving them a lot of time by having responses and rewards preloaded into the system.

Blacklisting

If a bot account does pass the rules engine qualifiers brands have a fall-back – They can universally blacklist accounts, preventing them from participating in any future campaigns.

Conclusion

Enterprise brands have run millions of transactions through our platform, making our engine smarter along the way, eliminating fraud and bot activity. Our analytics dashboard provides the data metrics for brands to realize and confirm their campaign participant authenticity.

If you’re a brand concerned about false campaign activity from bots, you should consider utilizing tools built for the exact purpose of avoiding it. Contact us today to learn more.