Guest Post by: Rick Burgess
Gilad’s R&D team spend a huge amount of time looking at data provided by the Twitter firehose and the bit.ly stream, using this information they are able to gain valuable insight into how Twitter users interact, and so predict the potential virality of certain content.
The team at SocialFlow applied this analysis to their own tweets. The results were interesting, as some tweets generated a large number of clicks but a low number of retweets, and vice versa. Using this information and by determining the characteristics of each “type” of tweet, SocialFlow were then in the position where they could target amplification (retweets) or engagement (clicks).
If you take this approach to your own tweets, you can work out when your users are paying attention and when they are likely to respond to your communications. You can also understand what topics are most interesting to your users. Once you have these two pieces of information you can start to ensure your brand is writing content, across your platforms, that will engage with your audience.
The focus of Gilad’s talk was on understanding audiences. One example below shows what topics the audiences of four major news networks are talking about:
When looking at this information Gilad noticed that users clustered together into groups, further analysis showed that these clusters in some cases were geographic but in others they were groups around a single topic or even a single core influencer.
They key take away from talk was that data can help you know your audience, understand what’s important to them, and when they are paying attention. Analysing this data into insight allows you to make every tweet count.
While this information is definitely useful, and a great starting point, the way that we would apply such insight is to go one step further and link it into existing business KPIs, such as measuring conversions from engagement into sales opportunities.
