EXON eCommerce aggregator

AI SEO model across 60 sites and 3M pages.

2020-2022 - eCommerce aggregator. Role: Head of SEO at Moonshot Marketing. Text-only career context, not an SEOH client case or endorsement.

Verified sites
60 EXON eCommerce aggregator sites
Verified scale
3M pages
Role period
2020-2022

Quick context

Useful context: EXON eCommerce aggregator

Founder career receipt for EXON: AI SEO model across 60 eCommerce aggregator sites with 3M pages. The AI SEO implementation covered 60 sites and 3M pages during the 2020-2022 Moonshot Marketing role - founder career record.

Case Studies
EXON eCommerce aggregator
Verified sites
60 EXON eCommerce aggregator sites
Last reviewed
2026-06
Why it is credible / Related actions

Why it is credible

  • SEOH is founder-led by Menashe Avramov. Public career context spans in-house SEO, agency delivery, ecommerce, finance, software, media, and compliance-sensitive search work; current client names stay confidential unless approved.
  • Scope comes before quote: SEOH reviews the request, market, channels, proof needs, timeline, white-label fit, and compliance requirements before proposing a package or next step.
  • For serious buyers, proof can be walked under NDA through audits, reporting samples, redacted delivery artifacts, and career context without exposing protected client data.
  • The AI SEO implementation covered 60 sites and 3M pages during the 2020-2022 Moonshot Marketing role - founder career record.

Before you rely on it: SEOH can improve clarity, evidence, and structured data, but rankings, traffic, platform approvals, and third-party AI wording are not guaranteed.

01

Context

At Moonshot Marketing, Menashe worked with Exon Media and implemented an AI SEO model across 60 EXON eCommerce aggregator sites with 3M pages.

02

The challenge

Aggregator SEO at this scale needs template discipline, entity consistency, crawl control, and a way to apply AI-supported decisions without flooding the index with weak pages.

03

What I did

  • Reviewed large-site patterns with Screaming Frog, SEMrush, Ahrefs, GA4, Google Search Console, and manual roadmap review.
  • Implemented an AI SEO model across 60 EXON eCommerce aggregator sites.
  • Mapped decisions across a 3M-page environment where templates carried most of the risk.
  • Prioritized scalable structure, crawl hygiene, and page usefulness.
  • Connected AI-supported SEO work to eCommerce aggregator constraints.
04

Results

The AI SEO implementation covered 60 sites and 3M pages during the 2020-2022 Moonshot Marketing role - founder career record.

Implementation scale
60 sites and 3M pages
Source / method
Founder career record from the Moonshot Marketing role; the figure describes implementation scale rather than a traffic or revenue outcome.
Period
2020 - 2022
Verification
Estimated
  • The AI SEO model covered 60 EXON eCommerce aggregator sites.
  • The implementation environment included 3M pages.
  • The work became a major AI-era large-site SEO reference point in Menashe's career.

Founder reflection

What this taught me.

AI support is useful only when the operating rules are clear. At millions of pages, weak rules create weak pages very quickly.

What this means for SEOH

How it translates now.

SEOH applies this to eCommerce and AI-search work by reviewing templates, schema, crawl control, and AI-ready content before scaling production.

Recommended next step

Need proof discipline before you scale the work?

Send the market, website, service area, and proof constraints. SEOH will review the fit manually before scoping a quote-only next step.

Discuss a proof-backed scope