Tuula vs Gary Pepper: who wins?
Which Australian fashion influencers have the highest engagement rates among their followers? Ragtrader asks BrandData to calculate a top ten ranking.
1. Tuula
2. Natasha Oakley
3. Gary Pepper Girl
4. Sarah Ellen
5. Sydney Fashion Blogger
6. Mimi Elashiry
7. Oracle Fox
8. A Bikini A Day
9. Micah Gianneli
10. Rachel Tyler
BrandData currently tracks over 135 ‘Fashion Influencers’, and Tuula is consistently in the top ten most engaging across social media.
The average daily engagement percentage for Tuula across all channels over the last week is 3.74% while the average daily engagement percentage for all brands in fashion influencers is 2.68%.
Instagram has the highest average engagement percentage over a seven day period in the fashion influencers category at 2.8%.
Instagram also registers the highest engagement percentage and has the largest audience for Tuula.
The Facebook channel has approximately 74,804 fans from Australia. Over a seven day period 9,246 activities were tracked, giving an average daily engagement percentage of 1.77% for this channel.
The Instagram channel @tuulavintage has approximately 2,210,089 followers. Over a seven day period 598,937 activities were tracked, giving an average daily engagement percentage of 3.87%for this channel.
The Twitter channel @tuulavintage has approximately 38,455 followers.
Over a seven day period 106 activities were tracked, giving an average daily engagement percentage of 0.04% for this channel. Tuula does not appear to have an active YouTube channel despite 29.41% of brands in fashion influencers having YouTube presence.
Pick up Ragtrader's April edition, where we put Kelly Smythe head to head with Romy Frydman.
BrandData – 6,400 brands, 230 categories, 5 channels, 1 rank daily. The BrandData rank is calculated based on 41 different engagement events taken from direct feeds from any social channel that accounts for more than 2.5% of the worlds traffic every day and then compared against the real data from all the other brands in that category or custom list. That data is then weighted according to channel significance within that category (real floating weighted average channel activity). This generates a rank for each brand.