Become the answer AI engines cite.
SkuLift orchestrates your algorithmic authority across ChatGPT, Claude, Perplexity and Gemini through a closed agentic loop: measure, analyze, recommend, execute, re-measure.
of searches end without a click when AI answers
LLM adoption growth in 12 months
of consumers query an AI assistant weekly
traffic drop observed on some B2B sites
What does SkuLift do?
SkuLift pilots your answers in ChatGPT, Claude, Gemini and Perplexity. We measure your share of voice, win the citations that matter, and keep your brand the default source AI recommends.
Search no longer ends on a results page. It ends inside an answer — and if your brand is not in that answer, you are invisible at the exact moment of decision.
Our model is operated, not self-serve: AEO and GEO specialists measure where you stand, diagnose why an engine cites a competitor, execute the fix under human validation, and re-measure to prove the lift. That closed loop runs continuously, because a position won in March can erode by June if nobody is watching.
The market has already shifted to answer engines.
When an engine answers directly, most searches end without a click — and a majority of B2B buyers now build their shortlist with AI. The contest has moved from the results page to the inside of the answer.
The traffic that does arrive from AI converts better, because the engine has already vouched for you. And none of this is confined to one sector — wherever a purchase begins with a question, the answer engine is increasingly what answers it first.
The search shift to AI answers
- 60%
- Zero-click searches
- Answered without a site visit
- ~1B
- AI assistant users
- ChatGPT, Gemini, Perplexity
- +10×
- AI answer queries
- Year-over-year growth
A closed loop, operated around the clock.
Measure, analyze, recommend, execute, re-measure. A supervised agent keeps the loop turning around the clock and never publishes on its own.
- 1. Measure
- Probe ChatGPT, Claude, Gemini and Perplexity at scale to capture where your brand stands today across hundreds of strategic prompts.
- 2. Analyze
- Decompose every answer to see which sources earned the citation, how prominent your mention was, and where competitors displaced you.
- 3. Recommend
- Draft concrete, answer-first recommendations and brand-controlled assets ready for review, never speculative filler.
- 4. Execute
- Approved work is produced and applied, from on-site answer blocks to off-site authority signals and structured data.
- 5. Re-measure
- We re-probe the same engines to prove the lift, attribute it to the change, and feed the result back into the next cycle.
Four KPIs that make AI visibility measurable.
You cannot pilot what you cannot measure. SkuLift tracks four hard metrics — share of voice, citations, word-count share and a prominence score — per engine, per market, over time.
Every metric is computed the same way each cycle, against the same question set, so the numbers are comparable over time rather than a moving target. Where the engine supports it, each metric is split parametric versus web-grounded — two different battles.
+34%
AI share of voice
×3
Citations earned
−21%
Time to first citation
24/7
Continuous optimization
Three starting points, one trajectory.
Most brands arrive absent, partially present, or visible but fragile. The trajectory out of each is the same disciplined climb from invisibility to a defended lead.
Absent brands have the clearest runway and often move fastest; partially present brands need their luck converted into a managed position; fragile brands need consolidation. The loop is identical — only the starting altitude differs.
Three maturity tiers, priced on request.
Foundation, Advanced and Premium describe capability, not cost. Every engagement is scoped to your catalogue and markets, so pricing is set on request.
Most brands begin at Foundation to establish a baseline, move to Advanced as the gaps become clear, and reach Premium when AI visibility is a defended, cross-market position. You never re-platform — you only widen the aperture.
Pilot vs. operated loop
Authority signals AI engines actually weigh.
Models cite sources that look corroborated, consistent and verifiable across the open web. SkuLift builds that authority footprint deliberately, signal by signal — never fabricated.
We resolve your brand into one consistent entity, align the reference profiles engines treat as corroboration, and earn verifiable third-party mentions. Authority compounds: each independent source that converges on your brand makes the next citation safer.
- Consistent entity — One coherent brand identity across owned properties, so engines resolve you to a single confident answer.
- Reference profiles — Presence on the marketplaces and directories that reviewers and engines treat as corroboration.
- Knowledge graph — Structured data and entity links that place your brand inside the graphs models lean on when sourcing.
- Third-party corroboration — Earned, verifiable mentions that make a citation of your brand feel safe to the model.
Authority signal stack
- Citations
- AI recommends the brand
- Authoritativeness
- Third-party references
- Expertise
- Author credentials
- Experience
- First-hand, dated proof
Start with a pilot, not a leap of faith.
A twelve-week pilot turns the abstract into a baseline you can see: where you stand in AI answers today, the gaps, and the first proven lift.