View The Work We Did For Cyclone Rake

The Brand

Cyclone Rake makes a category-defining lawn and leaf vacuum — a tow-behind collection system that mounts to a rider mower and handles leaves, grass, and yard debris at a scale ordinary baggers can’t. It is engineered, made in America, and built to last, with a loyal owner base and a price tag to match a serious piece of equipment.

That combination shapes everything about how it sells. The buyer is a homeowner or property owner who takes lawn care seriously, researches carefully, and treats the purchase as an investment. Demand is intensely seasonal, peaking with the leaves, and a large share of orders are placed not online but on the phone — after a customer has done their homework and wants to talk it through.

The Situation

SocialQ inherited an established but underperforming paid-media account and was asked to make it efficient — to grow revenue and the customer base across Google and Meta for a seasonal, high-consideration product.

Several frictions sat in the way. The account had drifted toward broad, upper-funnel spend that drove clicks but not sales, while costs in a competitive auction kept climbing. Meta was underdelivering. And the measurement picture was incomplete in a way that directly hurt performance: with roughly half of all revenue closing over the phone, much of the most valuable conversion signal never made it back to the ad platforms, so the algorithms were optimizing on a partial view of the truth. For a business this seasonal, with a purchase this considered, the job was to concentrate every dollar against genuine buying intent — and to give the platforms the full signal needed to find it.

The Solution

SocialQ began with a disciplined takeover: cleaning up brand exclusions, ad assets, and campaign structures, and refocusing the account on conversions, ROAS, and conversion value rather than raw traffic. From there the strategy was concentration over sprawl.

On Google, we rebuilt branded and product search around the highest-intent queries, scaled Shopping and Performance Max with tighter feed and bidding controls, and pulled back display, YouTube, and lead-focused campaigns that were absorbing budget without returning revenue — then judged each campaign against its actual objective instead of a single blended benchmark. A central thread was measurement: we surfaced that a large share of revenue closing by phone wasn’t being attributed to ads, and prioritized feeding that offline signal back to the platforms so bidding could optimize toward complete conversions.

On Meta, we rebuilt the account around conversion and retargeting with refreshed video and testimonial creative, steadily driving down cost per purchase. We layered in connected-TV with proper UTM tracking as an efficient mid-funnel support, and anchored reporting in year-over-year analysis suited to a seasonal business.