Three Ways to Make Your Influencer Selection Process Simpler
Influencer marketing is hardly new, but marketers continue to make relatively uninformed decisions when identifying influencers to represent their brand. They often rely too heavily on surface-level, publicly available metrics like follower count and engagement rate, or only on the directly attributable actions an influencer elicits from their audience—like site traffic, social media follows or downstream purchases. For many years, the discrepancies between what we can visibly see and the often-different story data tells us have been accepted as part of the trade-off when enlisting actual consumers to tell your brand’s story.
Here are three reasons why the influencer selection process is inefficient, and how to fix it:
No. 1: Not having the right toolset
While several variables impact the success of an influencer activation, it’s important to first
understand many marketers are attempting to discover creators for their brand using the most basic tools—or, in many cases—no tools at all. The recipe for underperformance begins with flying blind, continues with impulsive decisions and ends with more questions than answers.
One recent study shows 76% of responding marketers use no tools when selecting influencers, relying on internal teams and manual, painstaking research as their identification process. Yet, we also know 71% of marketers polled in another survey indicate they struggle to find the right influencer. Seeing the correlation between these two revelations, a solid first step for many of these participants would be to identify tools that not only provide them with a deeper data set but also help them organize, plan and execute their activations.
No. 2: Not evaluating the right data to determine success
Ultimately, the reliance on unreliable data is most often the cause of inefficient spending on influencers. Many studies show marketers today are focusing more specifically on engagement rate, content quality and outbound traffic driven from content because the consistent message in the market is that influencers are exhibiting fraudulent behavior to gain followers.
Fraudulent activity, however, is not always a reflection of decisions an influencer makes to inflate their status to brands. As influencers with public accounts cannot control who follows them, we often see scenarios where bot accounts will follow influencers to make their own accounts look more legitimate. This can happen without the influencer taking specific actions to accelerate short-term growth, and results in many brands activating influencers whose message will inevitably be displayed to irrelevant audiences, or not consumed altogether.
No. 3: Focusing too narrowly on directly attributable metrics
Many advertisers today only value an influencer and their historical work based on the amount of traffic they drive through provided links. This, then, severs as the deciding factor when determining whether or not an influencer should be re-activated. While eliciting clicks is a reasonable performance indicator and often a primary goal of influencer campaigns, it must be acknowledged that “influence” is not always represented in the form of immediate, trackable actions taken by an influencer’s audience.
The modern consumer moves unpredictably around the web, from one device to another, app to browser and so on. It’s completely conceivable that a viewer sees an influencer promoting your product on Instagram, and instead of swiping up to visit your site, they first visit retail sites to read customer reviews or compare prices before ultimately deciding to make a purchase. While that influencer’s content elicited a purchase, their work won’t be admired or rewarded in a model that values an influencer based solely on the number of clicks they drove.
Luckily today’s tools have finally caught up to yesterday’s problems, and new usages of existing technologies can enhance the decision-making process when identifying which influencers to activate. Proper collection and analysis of data, paired with well-constructed algorithms—like machine learning and natural language processing—provide marketers with the instruments needed to make better, more informed decisions than ever before.
For more information about how data and technology can enhance your influencer selection process, download our white paper here.