Michael McBride
Founder & CEO, Atelier Commerce
Michael McBride
Founder & CEO, Atelier Commerce
UTV Source plays in one of the toughest categories on the internet, where the buyer is spending real money to get a part right and the competition is one click away. You do not win that on price alone. You win it on trust. Our job was to build the reviews and rewards system that captures that trust at scale: thousands of verified reviews so the next rider sees a hundred people who already bought the part, a rewards program that gives them a reason to come back, and NPS so we hear it straight. When the rewards program went live in 2024, review collection jumped 80 percent in a year. That is what being in the mud with your customers looks like, and it is the thing that makes every paid dollar work harder.
UTV Source plays in one of the toughest categories on the internet, where the buyer is spending real money to get a part right and the competition is one click away. You do not win that on price alone. You win it on trust. Our job was to build the reviews and rewards system that captures that trust at scale: thousands of verified reviews so the next rider sees a hundred people who already bought the part, a rewards program that gives them a reason to come back, and NPS so we hear it straight. When the rewards program went live in 2024, review collection jumped 80 percent in a year. That is what being in the mud with your customers looks like, and it is the thing that makes every paid dollar work harder.
The Challenge
UTV Source had the demand, the catalog, and a base of riders who were genuinely happy with their parts. The challenge was that it competes in one of the most punishing categories in e-commerce, and trust was not yet built as a system.
It is a brutally competitive category. UTV Source wins by competing for expensive attention against a wall of other parts sellers. In that environment, the storefront has to convert hard-won traffic, and the single most powerful conversion asset for a high-consideration part is another real rider saying "this fit, this worked." The buyer does real homework. A part on a side-by-side is a considered, often big-ticket purchase, and getting it wrong is costly. The shopper researches before committing. Reviews are not a nice-to-have here. They are the deciding factor, and they matter more the higher the price and consideration. Trust was not captured as a system. Plenty of riders were satisfied, but there was no instrumented engine prompting them at the right moment to leave the verified review the next buyer reads, no rewards program rewarding the behavior, and no NPS loop to hear it straight. Loyalty had no architecture. The category rewards frequency and referrals, and peers all run points programs. UTV Source needed a rewards layer that recognized repeat riders and gave a reason to come back. The brief: build a reviews and rewards program fit for a competitive aftermarket category, launch a rewards program that pays riders to share and to return, and turn customer trust into a scaled, compounding conversion and retention asset.
The Challenge
UTV Source had the demand, the catalog, and a base of riders who were genuinely happy with their parts. The challenge was that it competes in one of the most punishing categories in e-commerce, and trust was not yet built as a system.
It is a brutally competitive category. UTV Source wins by competing for expensive attention against a wall of other parts sellers. In that environment, the storefront has to convert hard-won traffic, and the single most powerful conversion asset for a high-consideration part is another real rider saying "this fit, this worked." The buyer does real homework. A part on a side-by-side is a considered, often big-ticket purchase, and getting it wrong is costly. The shopper researches before committing. Reviews are not a nice-to-have here. They are the deciding factor, and they matter more the higher the price and consideration. Trust was not captured as a system. Plenty of riders were satisfied, but there was no instrumented engine prompting them at the right moment to leave the verified review the next buyer reads, no rewards program rewarding the behavior, and no NPS loop to hear it straight. Loyalty had no architecture. The category rewards frequency and referrals, and peers all run points programs. UTV Source needed a rewards layer that recognized repeat riders and gave a reason to come back. The brief: build a reviews and rewards program fit for a competitive aftermarket category, launch a rewards program that pays riders to share and to return, and turn customer trust into a scaled, compounding conversion and retention asset.
The System
We treated reviews, rewards, and feedback as one connected program, built for a category where trust is the most and the buyer is doing homework.
A reviews engine built for a high-consideration category. A review here is worth more than at impulse price points, because the buyer is spending real money to get a fitment right and is researching before they commit. We made verified reviews and NPS an instrumented part of the program, so satisfied riders leave the proof that converts the next one. The result is a wall of proof: more than 3,500 published product reviews at a perfect 5.0 of 5 average, more than 4,000 total reviews, and over 8,000 total responses including NPS, all verified buyer and current. A rewards program that took off in 2024. The category rewards frequency and referrals, so we built the loyalty layer to lean into it. The points-based rewards program launched in 2024, and the effect on review collection was immediate and dramatic: published reviews jumped from 417 in 2023 to 750 in 2024, an 80 percent surge, as points-for-reviews put the collection engine into a higher gear. The program is live and well-trafficked, drawing thousands of sessions a year from the brand's own customers. Multi-platform proof, on purpose. Trust in this category is not built on a single curated widget. UTV Source collects on-site, runs NPS, and also shows up on independent third-party platforms. The independent aggregate sits at a credible 4.3 across more than 4,000 reviews, with real one-star volume in the mix. We treat that candor as a feature, not a flaw: thousands of real reviews and a strong third-party score read as authentic in a way a too-perfect number never could.
The System
We treated reviews, rewards, and feedback as one connected program, built for a category where trust is the most and the buyer is doing homework.
A reviews engine built for a high-consideration category. A review here is worth more than at impulse price points, because the buyer is spending real money to get a fitment right and is researching before they commit. We made verified reviews and NPS an instrumented part of the program, so satisfied riders leave the proof that converts the next one. The result is a wall of proof: more than 3,500 published product reviews at a perfect 5.0 of 5 average, more than 4,000 total reviews, and over 8,000 total responses including NPS, all verified buyer and current. A rewards program that took off in 2024. The category rewards frequency and referrals, so we built the loyalty layer to lean into it. The points-based rewards program launched in 2024, and the effect on review collection was immediate and dramatic: published reviews jumped from 417 in 2023 to 750 in 2024, an 80 percent surge, as points-for-reviews put the collection engine into a higher gear. The program is live and well-trafficked, drawing thousands of sessions a year from the brand's own customers. Multi-platform proof, on purpose. Trust in this category is not built on a single curated widget. UTV Source collects on-site, runs NPS, and also shows up on independent third-party platforms. The independent aggregate sits at a credible 4.3 across more than 4,000 reviews, with real one-star volume in the mix. We treat that candor as a feature, not a flaw: thousands of real reviews and a strong third-party score read as authentic in a way a too-perfect number never could.
Latest projects
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
Latest projects
Social Media Marketing
Alicia Adams Alpaca: Where nine in ten organic social visitors are meeting the brand for the very first time
Alicia Adams Alpaca runs organic social as top-of-funnel discovery, not bottom-funnel conversion. Nearly 90% of visitors it sends are first-timers, the brand's highest new-visitor rate of any channel, arriving curious after seeing a styled throw or editorial content, ready to look closer.
Moonglow Jewelry: SEO & AEO, One Data Layer, Three Surfaces
We cleaned up a sprawling Shopify Plus catalog and enriched the product data behind it, structured for search engines and answer engines alike. The result: the blue link, the star-rating rich result, a seat in the AI Overview. Same data. Built to be found. Built to be cited.
