← Back to case studies
Case study

79 interested replies for Hector AI's Amazon ads platform across three geographies

79
Interested replies
164K
Emails sent
37
Campaigns
Category
SaaS
Industry
Amazon ads platform
HQ
United States
Engagement
Mid-February 2026 to present

About Hector AI

Hector AI is an Amazon ad technology platform with two product lines: a self-serve Ad Optimization platform that reverse-calculates the ideal bid per keyword every thirty minutes from live ACoS and CPC, and a self-serve Amazon DSP that removes the traditional entry barriers to programmatic advertising.

Both are built on a native MCP integration layer that connects Amazon Ads data directly to ChatGPT or Claude. Ranked among Amazon's Top 15 Advanced Partners globally. Public reference library: Dalstrong (79% ROAS lift), Noise (3x revenue lift via AMC retargeting), Nua (97% order-volume lift), Campus Shoes (1593% revenue growth on a fresh account), and R for Rabbit (19% ROAS improvement).

The challenge

01
Two buyer conversations, one platform
Ad Optimization and DSP are different pains.
The challenge

The Ad Optimization angle lands with sellers mismanaged by an average-ACoS approach. The DSP angle lands with brands hitting the Sponsored Ads ceiling. Same platform, different pains, different vocabulary.

02
A wide geographic split
US, ROW, and India brands don't share a register.
The challenge

The US brand cares about Prime Video and AMC audience layering. The India brand cares about entry cost and no-minimum DSP access. One message could not carry all three geographies.

03
A flooded "optimize your ads" category
Every Amazon brand has seen that pitch.
The challenge

Cutting through meant naming a specific bid or retargeting pain in a performance marketer's vocabulary, not another generic optimization promise.

04
Replies had to route to the right owner
Three regional heads, three geographies.
The challenge

With three regional business heads owning different geographies, every positive reply had to route to the right owner automatically, without manual coordination.

The GTM engineering in works

GTM Play 01
Two product angles across one book
The observable picked the pain: bid drift or DSP ceiling.
~2x the winning angle over the otherreply attribution split by product pain
The play

Separate active recipes for Ad Optimization (bid recalibration every 30 minutes, ACoS drift on new SKUs) and DSP (AMC audience build, $100/mo, no minimums, live in four days).

A wide SKU portfolio with bid drift got Ad Optimization; a brand hitting the Sponsored Ads ceiling got DSP. Attribution split by angle showed which pain did the work per tier.

GTM Play 02
The DSP channel they weren't running
Sponsored Ads maxed out, no display retargeting yet.
+79% ROAS on the Dalstrong buildopened with a free 3-month self-serve DSP trial
The play

We flagged brands running Sponsored Ads with no visible DSP or display retargeting and taught the DSP-first, Sponsored-retarget path through AMC path-to-conversion. A whole channel was sitting unused.

The wedge was the free 3-month self-serve DSP trial: no upfront fee, no minimum spend, live in about four days. Dalstrong's build on the same play cut CPC 16%, lifted purchase rate 47%, and moved ROAS 79%.

GTM Play 03
Geographic recipe splits
US heard AMC; India heard $100/mo, no minimum.
The play

US and Rest of World ran one recipe track, India a separate one, each adapting the DSP economics: US brands heard Prime Video reach and AMC layering; India brands heard DSP starting at $100/mo with no upfront commitment.

Client-shared Amazon Advanced Partner data enriched the lists, so the audience was pre-qualified for scale before a single send.

GTM Play 04
Lookalikes of brands we'd already won
Matched each prospect to the nearest proven case.
~2x reply when the case shape matchedNua +97% orders, Noise 14x conversion as the peer
The play

We seeded lookalikes on the documented reference wins and matched each prospect on category, D2C model, and Amazon-heavy footprint, then led with the nearest case study: Nua's +97% orders for wellness challengers, Noise's 14x conversion for electronics, LeCalla's +54% UK sales for expanders.

"It worked for a brand shaped like yours" lowers the perceived risk before the first call. The closer the shape, the warmer the reply.

GTM Play 05
Conquesting the brand above them
Take share from the category incumbent on Amazon.
~2x reply on the challenger angleSponsored Display retargeting + conquesting keywords
The play

For challenger brands sitting directly under a category incumbent, we identified the leader they trailed and opened on the gap: Sponsored Display competitor retargeting plus conquesting keywords to take share from the brand above them.

The narrative generalized Nua's run at the legacy feminine-care giants, a funded challenger beating an entrenched incumbent on high-intent terms. Naming the specific competitor made the email impossible to ignore.

GTM Play 06
New-marketplace expansion readiness
Maxed the home market? Enter UK, DE, or UAE.
+54% UK sales on the LeCalla builda phased three-stage marketplace entry
The play

We flagged brands strong in one geo but showing saturation and opened on the ceiling: you've maxed your home market. The offer was a structured entry into a new Amazon marketplace, UK, Germany, or UAE, without the guesswork.

The play mirrored LeCalla's three-phase expansion, which lifted UK sales 54%, clicks 49%, and orders 54%. A concrete plan beats a generic "want to grow internationally?" every time.

GTM Play 07
The ad-leak teardown
Named 3-5 specific ad leaks on their number-one ASIN.
~2x reply on the teardown openbuilt from their public storefront and ASINs
The play

We scraped each brand's public storefront and hero ASINs, then opened by naming the specific leaks: thin keyword coverage, no Sponsored Brand video, no DSP retargeting, a weak branded-versus-generic split. Anchored on Hector's 34% average ACoS cut across 2,400+ campaigns.

A teardown of their own account proves we studied it, and that is why the open earned a reply instead of a delete.

GTM Play 08
Tentpole-event prep
A pre, peak, and post plan timed to the big sale event.
~2x reply in the pre-event windowtimed 6-8 weeks before the event
The play

Timed 6 to 8 weeks before Prime Day and the Great Indian Festival, we opened on the event itself and offered a phased pre, peak, and post budget plan, mirroring the playbook that took a hero brand to 3x event revenue and share-of-voice rank two to one.

The calendar built the urgency. The event was the reason to reply now, not next quarter.

Results

79
Interested replies across US, ROW, and India Amazon brands
164,086
Emails sent across 37 active campaign recipes
37
Active campaign recipes running in parallel across both product lines
Free test campaign

Want results like these on your ICP?

Apply below. If we're a fit, we run a real pilot on your ICP and show you the actual replies before you commit to anything.