Semrush: A Straight Bet on Reverse-Engineering AI Answers
Ticker: SEMR Sector: Martech / SaaS Theme: Transition, Existential Risk, AI Optimization
Key Thesis
Semrush is attempting a full pivot away from consumer SEO tools—which are eroding under zero-click AI search—to enterprise AI optimization services. This is essentially a bet that you can influence AI-generated answers in the same way brands once manipulated Google’s public algorithm.
However, AI Answer Engines (LLMs) are proprietary, context-driven, and probabilistic. Unlike SEO, there is no stable, transparent set of ranking rules to reverse-engineer—making “AI optimization” a fundamentally unstable strategy.
The Setup
- Consumer SEO Collapse: Google’s SGE, ChatGPT, and similar AI tools deliver direct answers, bypassing traditional web results and rendering SEO tooling obsolete.
- Enterprise Pivot: Semrush’s enterprise contracts now represent over 40% of revenue growth, but face entrenched competition (BrightEdge, Conductor) and lengthy sales cycles.
- Product Launch: Enterprise AIO & AEO launched mid-2024 to help brands “optimize” for AI answers, accompanied by a major leadership change.
- Market Sentiment: Stock down ~78% from all-time high, indicating investor skepticism about both consumer and enterprise futures.
What’s Actually New?
- AIO Toolkit: Analytics for tracking brand mentions in AI outputs, content structuring guides, and “AI answer audits.”
- Enterprise Services: Premium professional services (custom integrations, SLAs) driving 25% higher average contract size.
- Leadership Shift: Founder → CTO; new CEO (Bill Wagner) with enterprise sales background, signaling “readiness for sale.”
- Cash Accumulation: €235M cash on hand provides runway, but also underscores lack of immediate growth opportunities.
The Problems With the Bet
- LLMs ≠ SERPs: AI models deliver narrative answers, not ranked lists—no equivalent to PageRank to decode.
- Frequent Model Updates: AI providers iterate rapidly; optimization guidance will lag and become obsolete.
- Neutrality Mandates: AI platforms aim for unbiased outputs—aggressive optimization may trigger de-prioritization.
- Monetization Gap: Even if cited by AI, users may not click or convert; AI answers diminish website traffic.
- Clone Risk: Any robust AIO features can be replicated by larger enterprise martech vendors with deeper pockets.
Where Does This Go? (2025–2027)
- Best Case: Blue-chip enterprise deals sustained; Semrush becomes an AI answers analytics provider and is acquired at a premium.
- Base Case: Modest enterprise growth offset by continuing consumer decline; AIO services generate single-digit growth.
- Worst Case: AI platforms lock down outputs; enterprise clients shift to full-stack martech providers; Semrush sells assets at a steep discount.
Bottom Line
Semrush’s AI optimization strategy is a high-risk, high-uncertainty bet, not a natural evolution of SEO. Without a stable, transparent mechanism to game, their core revenue engine faces disruption from both AI platforms and enterprise competitors. Durable success requires proving real influence over AI answers—a capability that remains unproven and likely transient.