Launched in 2018, Zevo was an unknown startup brand in the home pest control category. A category dominated by the same brand for decades with >50% US market share.
Zevo’s promise? An effective nature-inspired bug killing product that you can feel good about using around your home and loved ones. A difficult challenge in a category where product efficacy and safety were diametrically opposed in the mind of users.
To succeed, we had to drive both awareness and believability. We needed to create demand and push consumers to retail, but we had little awareness and limited distribution. How would we disrupt the category and secure our position as the preferred brand during peak bug season?
We decided to invest and connect with customers where our competitors weren’t. We knew our target consumer was discovering new brands on Instagram so we decided to own it with a massive influencer network, making Zevo appear big and popular at select retail stores. But we knew that approach alone wouldn’t be enough. The challenge with traditional influencer approaches is that they often measure without meaning. So, we sought a new approach that focused on measurement and relentless optimization. And it worked.
Our influencer approach was built with four key principles:
Speed & Agility: Real time learning and adjustments
Scale: All-in approach enabled
Design: Distinct waves allowed focused learning and enabled sales performance tracking
Mentality: Hands-on, attention to detail, diligent tracking and relentless analytics
Our 2019 results speak for themselves. More than 170 influencers shared highly-engaging custom content encouraging consumers to purchase at Target and The Home Depot, resulting in 20pt and 5pt boosts in weekly sales indices at those respective retailers during our active influencer waves.
Then, in partnership with our client, we started to drill down to understand what specific components of the content are driving action at retail. If we could quantify post content and tie its performance to sales, then we could use that model to optimize future content and campaign design. So we took inspiration from sabermetrics and developed a proprietary influencer scoring and measurement system. We took the insights from our 2019 campaign to inform and build our 2020 campaign.
When we say relentless, we mean it. In 2020, we expanded our team to 250+ influencers, all of whom were predicted to perform well by our model, and they delivered as predicted - driving content engagement rates and total branded engagements >30% higher than our previous year.
With this influencer model – called “Marketing Moneyball,” as it’s based on the 2003 Michael Lewis novel about the Oakland A’s analytical approach to building a competitive MLB team with a small budget -- we had a framework with which to build an even more impactful 2020 program, with high confidence. Applying a performance based, statistical approach to quantifying influencer content and correlating it with sales performance takes the guesswork out campaign building. Simply put … we engineered the 2020 program to be successful and drive our business by finding the right influencers and briefing-in the elements we knew would score highly in the model.
THE RESULTS:
2019 INFLUENCER
Impressions: 26,539,039
Placements: 935
Average Engagement Rate: 6.85%
2020 INFLUENCER
Impressions: 44,719,703
Placements: 1,223
Average Engagement Rate: 9.39%
SALES
Sales results are up significantly in brick-and-mortar retailers at over 2x our initial 2020 forecast. (specific sales numbers are confidential)
“Marketing Moneyball” takes influencer marketing to the next level – just like the Oakland A’s General Management did with their 2002 roster. They won as many games (103) as the NY Yankees with 1/3 of the payroll because they efficiently built the team based on delivering on the offensive statistics that most closely correlated with wins. Our approach to valuing elements of influencer content performance that most closely correlate with sales is very similar to the A’s approach to finding players who get on-base effectively and produce runs. This work has fundamentally changed the way we build future influencer campaigns.
