Identifying Micro-Influencers In Scraawl

Identifying Micro-Influencers In Scraawl

micro-influencer-girlIn a recent blog post, Adel de Meyer explored some key strategies and corresponding rationale for crafting a micro-influencer network you can leverage in your social media campaigns. While she made an excellent case for the benefits of using micro-influencers, we wanted to dig a little deeper to examine a few strategies as they apply to the utilization of Scraawl. Specifically, we will explore aspects of identifying and scrubbing potential key influencers. Subsequently, we will look at ways of managing your key influencers to make sure they stay engaged with your brand and avoid controversy.

The Initial Query 

Scraawl is an excellent tool for identifying and vetting potential micro-influencers. While there have been a number of in-depth articles on how to identify communities and key influencers, it seemed worthwhile to construct a brief workflow to tie them together as they apply to this specific purpose. Of course, it’s paramount to identify those individuals who share the most common interests associated with your brand or the campaign you will be promoting. To that end, a top-line keyword search is a good first step. For instance, let’s assume you’re a US travel agency looking to promote Ecotourism in South America.

 

image-1

As you can see above, we searched for posts including the word “travel” along with either the terms “South America” or “Eco” or “Ecotourism.” Looks like we got some good data. It’s here where the power of Scraawl can really be leveraged using analytics as a filter.

 

Scrubbing The Data 

Of course, there is naturally going to be some noise within the data set. I would therefore dive into Scraawl’s advanced analytics and first run Bot Detection, filtering out bots to try to eliminate some of that noise right off the bat.

bot-detection

 

Now that we’ve filtered out all those pesky bots, we can move on to identifying the most relevant communities within our data set using Scraawl’s Advanced Analytic Community Detection.

 

 

Of course, there is naturally going to be some lingering noise within the data. It’s important to click into each of these communities and look at the raw data to see what each one is discussing. As a perfect example, the top ranked community in this data set had nothing to do with ecotourism, and was about the eco-friendly nature of using the metro as promoted by the Union Minister of Urban Development of New Delhi. However, it looks like we did have some excellent communities relevant to our campaign. As you can see from the screen below, we can very easily click in to the raw data tab, and using simple operators exclude the data from communities not relevant to our campaign.

 

raw-data-exclude-ecotourism-updated

 

Identifying the Influencers 

The next step is to run Scraawl’s Influence Detection analytic solely on the relevant communities, a clean data set. This will help us quickly identify the top influential users as they pertain to this specific and highly relevant query.

 

We can then do a deeper dive to further explore the networks, thereby identifying potential ancillary micro-influencers.

 

Finally, we can also click over to the Basic Statistics, and look at top users sorted by total lifetime followers if we want to further expand our network.

 

Making the Connection

Let’s assume you’ve used the above methodology and come up with a list of 10 potential micro-influencers you’d like to reach out to. For a micro-influencer strategy to work, it is especially important to understand the personalities, behaviors, and preferences of each micro-influencer so that when we reach out, we do so in a way that seems organic and shows added-value.  To that end, perhaps the next best step is to utilize Scraawl’s Brand Monitoring search to do a deeper dive into each of these users’ posting behavior. As you can see below, we can include up to 10 individual user handles concurrently and monitor each simultaneously in one report.

 

 

We can then look at the Social Metrics under Advanced Analytics. This is a great tool to really verify the reach and engagement of each user. As is evident in the screen below, while this user looked good in our initial query, they don’t seem to have the engagement necessary for this type of campaign.

 

 

We can also scroll down and look at the top posts from each micro-influencer to help gauge our strategy of reaching out, and further verify that their topics align with our brand or campaign’s goals.

 

Next Steps

So we’ve identified potential micro-influencers, vetted them, and reached out. Now that they’re actively engaged with our brand, it’s important that we monitor their activity in order to minimize any negative or controversial posts we might not want associated with our brand. Once again, Scraawl provides an excellent tool for this purpose. For each user, we can set up a streaming report that will alert us any time the user mentions specific keywords such as our brand or campaign hashtag. This was, you can gauge not only how actively engaged each micro-influencer is with your brand, but also how exactly they are engaging.

Hopefully this post has illustrated the methodology of Scraawl as it applies to identifying micro-infleuncers, vetting them, and finally monitoring them. As always, please feel free to reach out to me if you have any questions or would like to see a live demo of this methodology in action. Keep on Scraawling!

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