Brand’s influencers on Twitter = Huge pay back
According to our recent research, influencer targeting on twitter pays back tremendously AND it’s probably wise to start with those who are organically connecting to a brand’s twitter account from within a brand target market or industry.
Here is why:
It’s a fact, people talk infrequently about brands in social media.
Moreover, we found that brands are mentioned much less frequently on Twitter than on Blogs. In the examples below, brand mentions are 10 to 30 times less on Twitter.
The good news is that we also found that:
- Industry influencers talk 100 times more often about brands that matter in their industry than the average Twitterers**; according to a Yahoo survey, half of all tweets consumed come from them.
- The pool of relevant influencers that are strongly connected to a brand through Twitter mention it 2 to 60 times more than other influencers within the same community.
=> Influencers from a brand’s industry who connect to a brand’s twitter account are 200 to 1200 more likely to mention it than the random Twitterers
Bottom line, from the standpoint of earned media and tweet consumption by a brand’s target audience, targeting, listening and connecting with relevant influencers to form strong and enduring relationships is critical.
And now, here are sample data in support of our findings:
First let’s compare brand’s share of voice between blogs and twitter in 2 large communities:
- Beauty Community (2500 influencers), we compare Lancome vs Clinique vs Sephora vs Mac vs Chanel
- 1 month history: 38k posts, 250k tweets -> # tweets = 7 x #posts
- Brand mentions:
- Biking Community (1280 influencers), we compare Specialized vs Trek vs Giant vs Cervelo vs Fuji.
- 1 month history : 13k posts, 127k tweets -> # tweets = 9 x #posts
- Brand mentions:
Next, lets look at the difference of SoV based on the level of separation between influencers and the brand twitter account (for the concept of level of separation, think about Linkedin levels of connection).
Below are pictures of the network of influencers connected to MAC’s twitter account at respectively 1, 2 and 3 level of separation (The node with a rectangle is MAC’s twitter account):
Mac’s twitter account is very connected thus their tweets are more likely to be amplified through the network.
And now the SoV data per level of connection to the brand’s twitter account. The data clearly shows that the SoV is much higher in the pool of influencers that are connected to the brand. Obviously those are organic connections from the influencers to the brands twitter account.
Group 1= Influencers who connects to the brand’s twitter account
Group 2=Influencers who are connected to an influencer from group 1
Group 3=All influencers
|# in group 1||35||99||9|
|SoV group 1||1.03%||0.66%||1.20%|
|# in group 2||166||195||156|
|SoV group 2||.88%||0.15%||0.11%|
|# in group 3||1165||1165||1165|
|SoV group 3||0.58%||0.10%||0.07%|
We see respectively a 2x, 6x and 18x ratio between the group of influencers which shows the impact of the degree of connectivity to the brand mentions.
** Comparison of brand mentions from Industry influencers vs others:
Based on our data, the volume of tweets from the beauty community mentioning a beauty brand is about 2% of the overall twitter activity on those brands. Considering the community is only 2500 people, which means 0.025% of Twitter’s overall ~100 millions active users, the volume of brand mention generated by the community of relevant influencers is 100 times what it is for the overall population.