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Revenue Spark

Use case

When your SaaS isn't in Claude's answer set yet.

Asking Claude or ChatGPT 'what is the best [your category]' returns competitors and not you. We rebuild the schema, anchor, and cluster cadence over six months so the answer engines start citing you.

The shape of the problem

A SaaS founder opens Claude. Asks the question their prospects ask: “What is the best [their category] for [their ICP]?” Claude names three competitors and a few legacy brands. Their company doesn’t appear.

That single test is what brings most engagements to RevenueSpark. The category exists. The product is competitive. The marketing site is fine on traffic. But the answer-engine layer has a blind spot — and the buyers’ research surface is shifting toward that layer fast enough that being invisible there is, increasingly, being invisible.

Why this happens

Three structural causes in the order we typically diagnose them.

Schema graph absent or unthreaded. Most SaaS marketing sites ship a single Organization JSON-LD block in the <head> and call schema “done”. That’s not schema. Answer engines need a threaded @graph — Organization, WebSite, Service, Offer, Person, FAQPage, Article, BreadcrumbList — with @id cross-references so the brand reads as one knowledge entity. Without it, the engines see fragmented signals and assign categorical placement to whoever shipped the cleaner graph.

Anchor language inconsistent. Your homepage describes the company one way; your LinkedIn bio describes it another way; your sales deck has a third version. Answer engines train on the corpus they encounter. A drifting anchor sentence trains them on noise; a locked anchor sentence trains them on signal. Consistency compounds.

Cluster authority low. A pillar page with eight loosely-related supporting posts doesn’t earn categorical placement. Twenty-six cluster pages threaded back to the pillar with component-aware anchor text does. The lift comes from architecture, not volume.

How we rebuild

The same 6-month engagement shape, applied to the answer-engine half.

Month 1 — Lock the anchor + ship the schema

Positioning sprint locks one canonical sentence + 8 components. Technical SEO ships the threaded @graph sitewide. By Day 30 you have the spine the next 5 months hang from.

Months 2–4 — Cluster cadence

Content engine ships pillar / cluster pages on a weekly rhythm. Each page contains all 8 anchor components in the first 200 words. Internal linking threads back to the pillar with component-aware anchor text. The agent fleet handles throughput; senior strategy handles voice.

Months 1–6 — Citation testing in flight

Measurement framework runs the 8-query citation test monthly. Per engine, per query, cited or not cited, what language they used to describe you, which competitor they cited instead. Month 6 verdict reports the delta vs Month 0.

What “in the answer set” looks like by Month 6

Realistic targets: 5 of 8 target queries surfacing your brand in at least one answer engine. At least 2 engines citing you on at least 4 queries. Half the gap to your primary named competitor’s citation share closed. The Month-6 verdict report ships board-ready 5 business days before the renewal call.

The signal we actually optimize for is third-party content adoption — independent reviewers, comparison articles, YouTube creators, forum discussions describing your brand using your component language. That’s the strongest single predictor of next-cycle citation share, and it’s the layer most agencies don’t track.

For the four-part recipe end to end, see LLM discoverability. For the methodology, see the Blueprint.

FAQ

Questions buyers ask.

How do I check if my SaaS is in Claude's answer set?

Open Claude (or ChatGPT, Perplexity, Gemini) and ask 'what is the best [your category] for [your ICP]?' If your brand is named in the answer, you're in the answer set for that engine on that query. If the engine names competitors and not you, you're in the blind spot. Test all four engines on at least eight category queries — the variance per engine is real.

Why is my brand invisible to LLMs?

Three structural reasons in the order we typically diagnose them. Schema graph absent or unthreaded — answer engines can't read your knowledge entity cleanly. Anchor language inconsistent — different on the homepage vs the LinkedIn bio vs the sales deck, so models train on noise. Cluster authority low — fewer than 20 internal pages reinforcing the pillar, so categorical placement collapses to a competitor with deeper coverage.

How fast can citations move?

Slower than Google rank, faster than people expect. Material structural changes — threaded schema graph deployment, locked anchor with consistent components, cluster cadence shipping — start showing in answer-engine citations 8–12 weeks after they ship. The Month-6 verdict typically reports a +3 to +5 cited-query delta against the 8-query baseline.

Is this just SEO with a new label?

No. The shared infrastructure (schema, content quality, internal linking) overlaps. The optimisation rules diverge: anchor language belongs in schema and body for GEO and decisively does NOT belong in meta titles for SEO. Citation lift compounds differently than rank lift. The Adalo Blueprint v2.0 is the methodology; SEO playbooks alone do not produce it.

Ready for a measurable Month-6 verdict?

Book a 30-minute discovery call. We'll run a live LLM citation test on your domain during the call.