Did you know that influencer marketing is the fastest growing method to acquire new customers online?
This is not surprising considering the numerous lucrative benefits influencer marketing offers in terms of boosting brand awareness. It is also extremely effective at impacting purchase decisions and winning the trust of your potential customers.
Social network analysis has been used in various industries to examine the connections between people, organizations, and other related entities.
It uses network and graph theory to investigate social structure by mapping and measuring these relationships. The principles of network analysis can also be applied to influencer marketing.
Image via Influencer Marketing Hub
Before we explore how you can utilize influencer network analysis, let’s first take a look at the challenges of influencer marketing.
The road to influencer marketing isn’t filled with sunshine and unicorns. It isn’t just about partnering with someone who has a large number of social media followers. It requires meticulous research and planning.
One of the most crucial factors that decides the success of any influencer marketing campaign is the influencer you collaborate with.
However, identifying the right influencers for your campaign isn’t as straightforward as it seems. In fact, 73% of marketers describe it as the biggest challenge of working with influencers.
Finding the right influencer takes more than just a quick Google search. There are a lot of aspects such as reach, engagement, and public persona that you should consider before selecting an influencer.
Collaborating with an influencer with millions of followers won’t yield any results if their audience doesn’t engage with your brand. It is here that influencer network analysis can be of great help.
Influencer network analysis can help you identify people who have the real power to influence your target audience.
It doesn’t consider reach or follower count as the only indicators of a person’s influence in their network. Instead, network analysis uses a person’s position in the network to determine how influential they are.
If you are unfamiliar with the concept of network and graph theory, social network analysis may seem quite overwhelming. In simple terms, it is just the process of evaluating the relationships shared by individual entities in a network.
It can be used to obtain both a visual and a mathematical analysis of different social structures.
The entities (people, organizations, and computers) are represented by nodes in the network. The links or edges represent the relationships between various nodes.
The position of a node in the network determines whether they are the connectors, leaders, or bridges. It can be applied to social networking platforms to determine the real influential power of a person in the network.
Consider the example of the “Kite Network” developed by David Krackhardt, a pioneer in the field of social network analysis. In this network, two nodes are connected to each other if they interact through some means. Take a look at the screenshot below:
Image via Orgnet
The degree centrality of a node is determined by the number of direct connections it has. It is evident that Diane possesses the highest degree in this network.
In other words, hers is the most active node and she functions as a connector or hub. However, it is important to understand where these connections lead to. Diane only connects those who are already connected.
On the other hand, Heather has only three direct connections. However, she is located in a very important position in the network. Such a node is said to have a high betweenness centrality in the network.
In a way, Heather acts as the bridge or gatekeeper between two important constituencies in the network.
Without her, Ike and Jane would be completely cut off from information that is circulating in Diane’s cluster. It is evident that a node with high betweenness can have a significant impact on what flows or doesn’t flow in the network.
Now, let’s take a look at how social network analysis can be applied to influencer marketing.
The example of the “Kite Network” illustrates that reach isn’t the only measure of a person’s influence. In other words, when looking for influencers, you can’t judge them based on their number of followers.
Instead, you should also consider the quality of their connections and the people they are connected to.
Let’s say, on one hand, you have an Instagram user with 2 million Instagram followers. However, most of these followers are regular users who, in turn, don’t have big audiences of their own.
On the other hand, you have another user with a few thousand followers, many of whom are well-connected in other networks. Working with an influencer who belongs to the second category might be more rewarding in terms of reach and engagement.
In addition, influencer network analysis allows you to identify those users who are connected to many parts of the network.
In other words, these users possess a high value of betweenness centrality and act as brokers or innovators. They have the power to start conversations, offer alternate perspectives, and transfer ideas between groups.
Let’s say you want to promote a brand of sunscreen using influencer marketing. The most obvious choice for such a campaign would be to collaborate with lifestyle, fashion, and beauty influencers
However, you can also market the product to people who travel frequently or are planning to travel soon. An effective way of connecting with such people on social media is through travel bloggers and influencers.
Influencer network analysis enables you to take a closer look at the positions of different users in a social networking site. It uses algorithms such as degree centrality and betweenness centrality to indicate the influence each user has in the network.
In addition, it often uses another algorithm called PageRank (originally developed by Larry Page to optimize Google search results).
PageRank determines the position of a webpage in Google search results depending on the number of websites linking to it.
In influencer network analysis, the algorithm measures the number of interactions (mentions, shares, and hashtags) linking to a particular user. In other words, PageRank is an indication of the level and quality of engagement an influencer generates.
A high PageRank value indicates that the user is perceived as a trusted source of information.
In addition, such users are likely to share a strong rapport with their audiences owing to a large number of interactions. They actively participate in discussions and are regarded as authority figures in their niche.
Influencer network analysis can help you identify the social network users in the most powerful positions. However, you might be torn between an influencer with a high betweenness and another one with a high PageRank.
The only way to resolve this dilemma is to have a clear idea about your objectives and target audience. If you want to expand your reach and establish brand trust, you should prioritize PageRank over the other factors.
Likewise, if you want to target new demographics, select an influencer who is well connected to different user segments.
Influencer network analysis can revolutionize the way marketers perceive influence and reach. It can help you identify users who are most likely to help you meet your end goals.
Sometimes, you can even reach the right audience by collaborating with an influencer who has a few thousand followers. It is high time you start utilizing influencer network analysis to select the right influencers for your marketing campaigns.
Have you collaborated with any influencers using social network analysis? Share your experience in the comments section below.
Learn more about influencer marketing: Influencer Marketing 101
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