Influencer marketing has been around for decades even before the dawn of digital marketing. You may recognize its other names: celebrity endorsements, thought leaders, journalists, newspapers, magazines, activists…and the list goes on. 

For years, the industry tried to term influencers based on their reach. While gauging influence by looking at ones reach can be used as a measuring stick, the true form of influence comes from relevance and engagement. Ever wondered why on some popular Instagram accounts you see tonnes of engagement but when they slip a product (obviously sponsored), the engagement numbers for that post plummets down like rock falling from the skies? That’s relevance and the outcome is engagement. 

Let’s get back to why you clicked and read this article – on leveraging data analytics to help manage your influencer campaigns better. 

You can’t improve what you can’t measure
Digital marketing enables you and I to do one thing that traditional marketing just won’t allow – measure outcomes and be data-driven. 

While traditional marketing uses proxies on what is the value of your marketing efforts, going digital means you could, one way or another, measure the data that relevant to your marketing spending. 

It enables optimization through rapid trial and error, shift budget to what works, find out why some assets don’t perform as well, and best of all…helping you justify your marketing dollar to the dime. 

Why immediate sales are not always the best way to measure influencer marketing
While the easiest way to measure outcome of any marketing effort is sales, this metric is lacks information on the other gains that are not directly correlated to immediate sales. 

Let’s break it down to how you and I consume media relevant to our purchase behaviours. Depending on what you are selling/promoting, there are 4 types of consumer products or services (convenience, shopping, specialty, and unsought). A quick Google and you will learn what each products are and how to market them. 

And these types of products would leads us to 4 types of purchasing behaviours: impulse purchase, routine purchase, limited decision purchase, and extensive decision purchase. 

So what do I measure then?
Remember I spoke about relevance and engagement earlier? These metrics coupled with other things like brand-love, mindshare, or whatever you call the “emotional” component of consumer towards products and services are soft-metrics that leads to your ultimate goal of sales. 

Different online channels have their own ways to showcase relevance and engagement. 

Let’s have a crash course on some of it: 
Facebook – Reactions, comment, shares, impressions, where people click on the Facebook posts. 
Instagram – Like, Comment, Video views. Websites/blogs – Time on page, bounce, returning visitors, new visitors. 
Youtube – Average percentage of video viewed, number of views, comments, likes, dislikes. 

Don’t worry if all these sound bit too technical to you now. I’ll be preparing future posts for you to understand each and everyone of it. 

How does knowing these data help me to better manage my campaigns?
Data is meaningless unless you and I are able to make sense of it. Right? 

Let’s go with one example, Facebook posts. 

By measuring how Facebook posts perform overtime for your campaign, you would be able to decide if you need to increase the frequency of postings from influencers. Observation on how campaign content perform over a period of time enables you to pin-point what happened when one of the posts have spikes in engagement. Allowing you to ask questions such as: 
1. What did the influencer do differently compared to previous posts that caused this? 
2. What are the elements that the influencer can replicate from this post into your future posts to improve its engagement numbers? 
3. What are the events that happened during the time of posting that contributed to the engagement outcome? Is it the hashtag trending? Is there media boost performed by any party? 

Am I overspending?
By knowing how each influencer is contributing – in terms of number of content and engagement they contributed to your campaign, you are able to derive average cost per engagement (price paid to influencers over total engagement generated by the influencers who are paid). If the influencer campaign is in-kind, then the value of in-kind can be used as total amount spent on influencers. 

To demonstrate how this is calculated, let's assume you spent USD1,000 on 10 influencers. And they created 10 content in total for you. The 10 content generated 10,000 engagement. 

Average cost per engagement 
= (total money paid out to influencers) / (total number of engagement for all contents generated)
= (USD1,000) / (10,000 engagements)
= USD 00.10 per engagement

You would then compare the average cost per engagement with the cost per engagement of each influencer to see the variance between average CPE and the influencer’s CPE. 

Continuing for the example about, assume you paid each of the influencers USD100. And the engagement generated is 1,000.

Cost per engagement of particular influencer
= (total money paid out to influencers) / (total number of engagement for all contents generated)
= (USD1,00) / (10,00 engagements)
= USD 00.10 per engagement

If you are paying the influencers differently and they generate different numbers of engagement, you would be able to compare it with your Average Cost Per Engagment to check if there are influencers that are have cost per engagement that you could not tolerate. 

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