“Influencer marketing” is a buzz phrase we’ve been hearing in the marketing world for quite some time, but does it actually work, and to what end?
Devon Wijesinghe, CEO of InsightPool, would respond with an emphatic “YES”…provided you actually know what you’re doing with the data you receive.
Five years ago, it was common for brands or agencies to dip their toes into the influencer marketing space by asking for influencers in large pools: “We want mommy bloggers.” The problem with this old approach, Wijesinghe argued, is that it’s too broad–not all mommy bloggers are the same, much like no two mothers are the same or, if he is to be believed, no to women are the same.
“Don’t get me wrong,” said Wijesinghe, “the ‘Mom Mafia’ is important, but the old model completely misunderstands the way we target.” The former methods used to find influencers for a brand typically boiled down to age, demographics, and life stage. But audiences are complicated, he argued, and not all of an influencer’s followers will be interested in each and every thing they say.
The question in the new model, to continue using mommy bloggers as an example, is not who are the mommy bloggers, but how are they influential, and in what spaces? Are these bloggers focused on the day-to-day activities of child-rearing, or on cooking food children will eat, or on the brands they use in their house, or even on having a glass of wine at the end of the day and remembering that no one is perfect? When marketers get more granular in terms of the audience they want to attract, that’s when influencer marketing really starts to work its magic.
In becoming more laser-focused on a specific audience (mommy bloggers who have multiple children, are the primary caregiver, and prefer Cabernet to Chardonnay when they’re attempting to relax), marketers can begin to pull together data that will start to flesh itself out into a very specific taxonomy. Mommy bloggers who blog about being a mom in a rural or religious community versus mommy bloggers who blog about being a mom in a major city. When taxonomies become clear and specific, marketers can start seeing where the audiences get segmented based on the data: this audience only engages this mommy blogger when she talks about lipstick, while this audience engages her when she talks about making food for her kids. Clearly segmented audiences provide opportunities for highly targeted advertising with more focused voices: all keys to increasing awareness, conversions, and ultimately, ROI.
But what else can we use this kind of social data for in lieu of advertising? Wijesinghe stressed the importance of understanding the entire story before advertising even begins–a brand can think their audience desires one thing when, in fact, the data will tell a different story completely. He told a story of an automotive parts client who assumed that their audience of likely buyers would be men who liked NASCAR. When the data was actually collected and reviewed, however, it was found that their most likely buyers actually ended up being women who liked Formula One racing–talk about being off-base. Once the brand was updated on and embraced the data presented, they were able to switch gears, as it were, and advertising voices to cater to this new audience, which resulted in a 10X conversion rate.
When looking for influencers, Wijesinghe urges marketers to “go organic” whenever possible. Networks of influencers sound tempting: it’s easy for marketers to feel they’ve hit a gold mine of verified influencers interested in being paid for their endorsements of specific products. The problem with this, however, is the potential lack of true loyalty investment on the part of the influencer. For instance, if an influencer is endorsing a Mazda, but driving a Mercedes in their personal lives and is caught in the act, all trust and credibility is gone…and you can’t get that back. “Earned [influencers are] going to deliver what you really need in the end,” said Wijesinghe. “That way, [the endorsements] are just based upon the data as opposed to being based upon how much someone wants to get paid to talk to an audience about something they have no freaking clue about.”
“We have a tendency to make sweeping generalizations on race and gender when we really can’t,” he said. It seems, then, that the general theme of this year’s conference is emerging, and it’s simple: we can attempt to start with data, but we really need to start with a specific hypothesis of what we think is happening in our audience. Once we have a hypothesis, only then we can test it–the data that emerges will either confirm or deny what we thought to begin with.