How EdisonOS turned organic search into the engine behind 100% of their pipeline with Scale Theory

About

EdisonOS is a test prep platform for SAT and ACT tutors to conduct practice tests in a near SAT/ACT test environment, assess student performance and exam analytics, set custom scores and so on.

• Industry: EdTech / Test Prep SaaS
• ICP: Independent tutors and tutoring institutions (SAT/ACT/SHSAT/AP prep)
• Geography: United States (Primary)

Problem statement

In December 2024, EdisonOS pivoted their product from an LMS for online course creators to focus specifically on SAT/ACT tutors and schools.

However, EdisonOS faced a unique challenge. 5 things were working against them:

• Most of the keywords that could have been right for EdisonOS had mixed intent, meaning, both students and tutors searched for these keywords
• Mixed-intent keywords were dominated by high-traffic, high-competition sites like Khan Academy and Magoosh
• No way to determine what share of that traffic was actually tutors (their target audience)
• No competitors existed in the organic scene making it difficult to or reverse-engineer keyword strategies
• Tutor-specific keywords, where intent was clear, had virtually no search volume

SEO, in its traditional sense, didn’t work. 

Additionally, they had zero topical and domain authority in this space. The brand was quite new as well.

Goal 

EdisonOS needed a structured content strategy to generate qualified meetings and not vanity traffic. 

The strategy had to capture high-intent queries from tutors actively looking for information to grow their business, fix student performance, and to evaluate test prep platforms, build topical authority in the tutoring tools space.

Solution 

Rather than chasing high-volume keywords, we used the jobs-to-be-done framework to find topics focusing on real difficulties that a tutor will have in accomplishing their jobs. 

We also built product-aligned clusters (e.g., mock tests, SAT/ACT prep workflows) and expanded into adjacent exams like PSAT and SHSAT as the product evolved.

Here’s what the execution looked like:

• Consistent tracking and re-optimization of 20–25 money keywords
• Publishing ~10 new content pieces per month
• Re-optimizing ~5 existing pieces per month
• Continuous tracking and defense of high-value (“money”) keywords
• High-quality, SME-driven content with strict editorial standards
• Strategic internal linking to strengthen key pages
• Rapid response to ranking drops (recovering keywords back to top positions)

Results 

SEO went from a supporting channel to the only channel that matters.

Every result below was achieved from August 2024 onwards.

Traffic & Visibility

• Organic clicks grew from 3,475 in December 2024 to a peak of 6,707 in March 2025 — nearly doubling within four months
• Total monthly impressions scaled from 586,000 to a peak of 1,739,038 by August 2025 — a 3x jump in under a year
• Core money keywords consistently ranked in the top 3

LLM & AI Visibility

• EdisonOS went from zero to 500+ monthly LLM sessions consistently, appearing in the exact searches their ICP runs when evaluating test prep tools

MQL Pipeline: The Real Story

When Scale Theory started working with EdisonOS in August 2024, SEO was responsible for 5 out of 14 meetings booked that month — 36%. Cold calls, email outreach, and other channels were still doing most of the work. 

What followed was a steady  takeover:

• August 2025: Volume peak — 22 meetings in a single month, 71% of all pipeline
• October 2025: 10 of 12 meetings from SEO — 83%
• November 2025: 13 of 17 meetings from SEO — 76%
• January 2026: 18 of 19 meetings from SEO — 95%
• February 2026: 13 meetings booked. 13 from SEO. 100%.

Year-over-year, SEO-sourced meetings in January–February grew from 8 to 31 — nearly a 4x increase. Every incremental gain in the pipeline over the past year has come from SEO.

Results summary