In September 2017 we launched Babios, an affordable online luxury furniture store specialising in furniture for kids. We had the opportunity of working with fantastic mummy/parenting bloggers in the UK with mixed results.
Finding the most appropriate influencer mummy bloggers to work with was a challenge. There are dozens of professional blogger/influencer marketing platforms. They have their own algorithms and use some sort of a method evaluating and matching influencers with brands in real time.
These platforms are incredibly expensive and out of reach for most small businesses and in most cases not very helpful apart from showing key performance metrics, such as the number of Twitter, Facebook, Instagram followers, average retweet ratios, number of likes, average number of comments, and the list goes on. These are useful statistics, but which one of these metrics should you be focusing on? Relying on a single measure or even a combination of measures can be misleading.
Also, some bloggers prefer Instagram more than any other platform, whereas others may heavily utilise Twitter, Facebook, Pinterest, BlogLovin, and/or a combination of these mediums (offline and online).
There are also many websites providing a list of top 10, top 50 or top 100 mummy bloggers in the UK, Vueolio and tots100 been the most popular. In the majority of instances bloggers are ranked according to the number of Twitter, FB, Pinterest and/or Instagram followers. It sounds like a number game. The more the better. Is it really?
This is a big mistake. What about efficiency, effectiveness, and productivity? For example, what if a blogger is able to produce much higher output (e.g. high engagement rate on Twitter and Instagram) with a small number of inputs (e.g. publish fewer but high quality blogs)? This is a typical example of been an efficient blogger.
What’s more frustrating is the fact that each platform or ranking says something different, so who do you trust? And it’s a bit of a mystery how bloggers (influencers) are ranked (i.e. the methodology used behind the scenes). For instance, almost every mummy/parenting blogger has a banner on their homepage, for example, Tots100 Ranked #30 or Vuelio Top 10 Blog. Have you ever wondered how these rankings are established and the key factors driving these rankings?
So, after a 12 months of frustration, I wanted to put my wife (the managing director of Babios) out of misery and come into the playing field with my academic hat on. I am Professor of Statistics and Operational Research at the University of Hertfordshire. One of my area of expertise is the development of statistical and mathematical models that rank institutions and organisations, such as the National Health Service hospitals in the UK.
In this context, bloggers are no different, they are an entity just like organisations with clear inputs, sharing and promoting blogs within their community, working with brands, which then leads to outputs, such as authority, value added to brands and community, and level of engagement on social media platforms.
The objective of this comprehensive study is not just to benchmark bloggers, but to deep dive and analyse wide range of key performance metrics (explained below). The study involves you and your data collected over a 6 month period (almost 480 hours of work), thanks to three research assistants collating all the relevant data using wide range of sources.
Note that the data is publicly available, but the trick is identifying all the key metrics of importance, and been able to collect each and every single one of them for 1000’s of mummy and daddy bloggers in the UK. It’s not an easy task.
The objective of this study and the article are as follows:
There are numerous benefits of this study for both to businesses and mummy/parenting bloggers, and to name a few:
Over a period of six months, relevant data was extracted using various websites, some publicly available and others through paid platforms. Key information related to a total of 1,188 mummy/parenting bloggers was collected. This is a very large sample size thus the analysis can be deemed to be nationally representative, reliable and accurate.
According to Table 1, a mummy/parenting blogger on average has 10,299 Twitter followers with a maximum of 119,800. The average retweet and reply ratio is approximately 21% (max 97%) and 22% (max 76%), respectively.
The youngest mummy blogger in the UK is 0.044 years (i.e. 16 days old) and the eldest is 10.54 years. The average Twitter social authority is around 48 (out of 100), where 75% of bloggers have a score less than 56 (with a maximum of 76).
A mummy blogger on average publishes 126 blogs per year (max 2,111), generating around 42 engagements per blog (approximately 6,899 engagements in a year and as high as 651,556). Engagement includes Facebook, Twitter, Pinterest, Reddit, and Instagram.
Instagram engagement rate (ER) and authority score is an important metric. The average Instagram ER is around 3% (27% been the highest who has less than 2000 followers). Smaller close knit community of followers tends to have higher ER. The average number of likes per post on Instagram is around 294.
Note that a fair number of mummy bloggers rely on Instagram with very little activity or no use of other platforms. As a result, they accumulate larger number of followers over time, thus more likes. In this context, the average is skewed and may not be a reliable measure. The 50th percentile of 84 is more accurate, meaning that 50% of mummy bloggers attracts 84 or fewer likes per post, with around 14 comments.
2.2. Correlation Analysis
Correlation is an important statistical measure used to determine how strongly pairs of variables are related. For example, highest level of qualification (e.g. PhD) can be related to high salary, or to be within context, mummy bloggers social authority score can be linked to retweet ratio, e.g., high social authority score on Twitter could be an indication of high retweet ratio.
Correlation statistic ranges from -1 to +1. The closer it is to +1 or -1, the more closely the two pairs of variables are related. If correlation is close to 0, it means there is no relationship between the variables. If correlation is positive, it means that as one variable gets larger the other gets larger. If it is negative it means that as one gets larger, the other gets smaller (often called an "inverse" correlation). See Table 2 for correlations of all the data variables.
The number of Twitter followers are correlated with Instagram metrics. For instance, there is a 53% correlation between the number of Twitter followers and the average number of Instagram likes (and 46% with the number of Instagram comments). In plain English, this basically means that the higher the number of Twitter followers’, the higher the number of Instagram likes and comments. A careful visual inspection of Figure 1 confirms this.
From Table 2, a surprising finding is that Twitter account years (i.e. the number of years a blogger has been on Twitter) is negatively and weakly correlated with Twitter social authority score. One would assume that Twitter authority scores should increase as the account ages, but it’s the opposite. As the account ages the authority score seems to be decreasing. I wonder why, does anyone have an explanation to this phenomenon?
As expected, increasing Twitter account years is positively correlated with domain authority (DA) and page authority (PA). Clearly Google likes and prefers aged and active domains, which is also evident from the positive correlation between the numbers of articles published (in the last 12 months) and DA & PA (0.34 and 0.30, respectively).
The number of Facebook followers and Total Blog Engagements (last 12 months) has a correlation of 0.97 (almost 1, i.e., 100%). Despite the decreasing popularity of FB amongst many bloggers in the UK (and worldwide), this finding suggests that FB remains to be the dominant player, where the vast majority of blog engagements takes place (i.e. likes, shares, and comments).
This does not mean that there are no engagements on other platforms, including mummy bloggers own website, but there seems to be high level of engagement on FB. However, we notice a weak but positive correlation (0.17) between the average number of blog engagements (in the last 12 months) and Instagram authority score.
The finding that struck me the most is the connection between the number of Instagram followers and Instagram engagement rate, which is almost 0% (i.e. -0.04). Increasing number of Instagram followers is absolutely nothing got to do with engagement rate.
Clearly this is an evidence indicating that blogging is not necessarily a number game. It’s all about the quality of the posted material and more importantly bloggers community on Instagram. Some mummy and parenting bloggers have fascinating levels of Instagram engagement (between 10-15%) with 5-10K followers, which can be considered to be a large community.
We will post and share our findings in stages over the next few months. The first stage of the study (i.e. this article) is to raise awareness amongst mummy/parenting bloggers showcasing that such exercise has been carried out, and provide an exhaustive analysis of the data.
The second stage of the study (possibly January 2019) will introduce the mathematical model (in plain English) and benchmark bloggers accordingly.
A technical report will be published but the mathematics can only be understood by those who have a sound knowledge of Operational Research (a branch of Mathematics).
The third stage will publish top 50 or top 100 mummy bloggers from our sample. Note that we are only able to carry out the study on the sample of bloggers we have collected, thus if a particular blogger is missing then a benchmark cannot be provided.
Over time our sample size (with new data variables) will grow which will enable us to provide more accurate rankings.
After an exhaustive review of the literature and online materials, we confirm that such analysis at this scale has never been carried out before. The development of mathematical models for benchmarking bloggers and influencers is in its infancy.
There are still plenty of work to do, including the testing of novel methods/approaches with new data variables. As a result, our findings may change and where appropriate shared as and when new set of results are obtained.
These models will be published in top academic journals, which will be reviewed by esteemed academics and practitioners specialising in Influencer Marketing.
Transparency in terms of methods, results and findings are crucial. The study will be submitted to the “Journal of the Academy of Marketing Science”, internationally recognised as the world’s leading Journal in Marketing. If the article is accepted for publication, it will be the first of its kind within the field of Influencer Marketing.