Another post via the FACE company blog – see the story in full here: Mapping the Brand Graph: a study of the O2 audience on Twitter (FACE and O2 @ Warc #Datacentric 2011, London).
This has been some of the most interesting research I’ve done all year and certainly the most technically challenging, so I wanted to share it here too.
In short, FACE and O2 presented at the WARC Datacentric conference in December 2011. To quote Fran’s write-up:
The objective of the O2 Brand Graph pilot was to mine social media data in a way that would allow us to connect it to audience studies. What follows is an initial exploration of how we can you use social media to augment a segmentation model with real-time data.
Whilst tracking social media by keywords allows us to get an understanding of how a specific topic is discussed online, tracking social media by users allows us to build a map of an audience, its hubs, its behaviours and its interests.
We called it the Brand Graph: the conjunction of the Social Graph (defined here as the network of people who are within 2 degrees of separation from the brand through social media channels) and the Interest Graph (the network of interests, topics, activities and behaviours associated with the nodes of the social graph).
What can you do with it?
- Dynamically understand who your audience is and how is it changing, in real-time;
- Dynamically understand what your audience is about, what makes an interesting topic and how broader cultural conversations affect it;
- Segment your audience in clusters based on topics of interest, passions, life stages, professions, online behaviours etc.;
- Plan and fine tune the content of your social media strategy;
- Engage with your audience in the right way (channels, mechanics, times of the day, tone of voice etc.);
- Assess the impact of your strategies in real-time.
- Going forward, we see the brand graph becoming one of the key tools to build a seamless connection between your brand and its audience
So, how did we go about building the O2 Brand Graph?
Sample: We defined our sample as the entire audience of O2 on Twitter, i.e. 58.339+ Twitter users who were following @O2 (as of November 2011).
Methodologies: Statistical analysis, Semantic analysis, Network analysis, Netnography and Content analysis.
We then analysed the static data of 58,339 profiles on Twitter gathering insights around 10 key dimensions:
- To get this information we had to map 58,339 users following @O2 and who was following each of the 58.339 users.
- We ended up plotting a graph of 1 million nodes, 1 million primary connections and 574,278 horizontal connections within the graph.
- We then analysed the static data of 58,339 profiles on Twitter gathering insights around 10 key dimensions.
- Finally, we analysed 3,120,371 public tweets, 122,220 tweets/day (avg), generated by the @O2 followers over one month (November 2011).
Here’s the conference presentation: