Insynctive × Resonate Labs · Live engagement
12× more visible in six weeks, with every win traced to a fix we shipped.
A B2B HRIS platform went from effectively invisible across ChatGPT, Claude, Gemini, and Perplexity to surfacing on the buyer queries that matter, in six weeks. Here is exactly what moved, and why.
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Resonate Labs audited Insynctive, a B2B HRIS platform that was effectively invisible in AI answers, surfacing in just 2 of 150 buyer queries. We fixed a rendering problem and shipped 38 fresh pages against a prioritized plan. Visibility rose 6x by the four-week re-audit and 12x by week six, on the same matched query set, every gain traceable to a fix we shipped.
Updated June 2026
By the numbers
Six weeks from an invisible baseline to a 12x lift, all on the same matched 150-query set.
Insynctive
38
Pages shipped
Net-new server-rendered GEO pages, the core of the build most of the lift traces back to.
19 → 39
Google-indexed pages
Indexed pages more than doubled as the new content shipped.
6×
More visible by week four
Buyer queries surfacing Insynctive went from 2 to 12 of 150. 8.0% visibility, up from 1.3%.
12×
More visible by week six
Queries surfacing went from 2 to 24 of 150, on the same matched set.
Every figure is scored on the same 150-query set, so the multipliers hold because the denominators are identical: 6x at the four-week re-audit, 12x two weeks later. Crawler traffic moved first, and citation visibility followed. We claim attribution, not latency.
Crawler traffic moved first; citation visibility followed. The crawl spike showed up inside the sprint, and visibility kept climbing past the four-week re-audit.
The Insynctive trajectory
Crawl spikes first, visibility follows.
Leading indicator · GPTBot crawl volume, +504% over baseline
Lagging indicator · visibility on the 150-query set
X-axis is time-proportional; the baseline is near zero by design. Measured on a fixed 150-query set across ChatGPT, Claude, Gemini, and Perplexity. Resonate Labs · Insynctive engagement
The starting point: invisible to the engines buyers use.
At the April baseline, Insynctive surfaced in 2 of 150 buyer-research queries, a 1.3% visibility rate. The site ranked on Google and the content was good. The engines had almost nothing to surface.
[Diagnosis] The platform was built on a client-side-rendered framework. Most AI crawlers do not run JavaScript, so they requested each page and received an empty HTML shell. For the full mechanism, and how to check your own site, see why AI can't see your site.
The six-week arc
From an invisible baseline to a measured, attributable lift, in the first weeks of an ongoing program.
Baseline to re-audit
Day 0 · Baseline
Effectively invisible
2 of 150 queries surfacing. 19 indexed pages. The diagnosis: a client-side-rendered site serving empty HTML to AI crawlers.
Days 2 to 28 · The build
Fixes live, authority compounds
15 items shipped in the first 48 hours, including the rendering fix that unblocked everything else. Then 230+ internal links across three layers compounded topical authority as the new pages went live.
Week 4 · Re-audit
6× more visible
12 of 150 queries surfacing. 8.0% visibility, up from 1.3%. Every new win traceable to a fix we shipped.
Week 6 · Check-in
12× the baseline
16% visibility on the same matched 150-query set, 12× the baseline and still rising two weeks after the formal re-audit.
Every new win traces back to a fix we shipped.
Audit insight, to a fix we shipped, to a query surfacing at re-audit. For the new pages, the loop closes all the way to the citation: the query returns Insynctive and cites the exact page we built for it. Most agencies cannot produce this. It is the single most defensible argument for the methodology.
Step 01
Audit identifies the query
The 150-query set is tagged by buyer-journey cluster and intent, surfacing the exact questions where Insynctive was absent.
Step 02
Brief written
Each gap becomes a content brief, structured to the cluster, the persona's language, and a citable claim shape.
Step 03
Page shipped to the main domain
Server-rendered HTML, 8 to 14 internal links, submitted to the engines. Live on the client's own domain.
Step 04
Query surfaces and cites it
At re-audit, the query returns Insynctive, citing the exact page we shipped for it.
[One closed loop] Take a validation-stage question a CFO would ask: the limitations of the platform worth knowing about. At baseline it surfaced no one, because the relevant pages returned empty HTML to the crawlers. In the first 48 hours we shipped two server-rendered hub pages built for that evaluation question. At the week-four re-audit, the query surfaced Insynctive, citing the exact pages we shipped. Audit to citation, start to finish.
The largest gains landed on the queries closest to purchase.
Requirements building, shortlisting, and validation are where AI tools shape final-mile buying decisions. All three moved from a standing start, and requirements building saw the largest single jump, from 6.2% to 25%.
The top individual gains came on capability queries: compliance management moved from 0 to 28.6%, and document automation from 0 to 20.0%. These are the questions buyers ask when they are close to a decision, and Insynctive was absent from all of them at baseline.
Existing vendors said the CMS could not be fixed. We engineered around it.
The hardest part was one technical change: making the pages readable to AI crawlers without re-platforming the site.
Before · Invisible to AI
Crawlers read an empty page.
A crawler requested each page and the server returned a JavaScript framework shell. AI crawlers do not execute JavaScript, so they read an empty page. Nothing to index, nothing to cite.
After · Readable and citable
Crawlers read the real content.
The same crawlers now receive identical server-rendered HTML, the same content a person sees, with no re-platform required. This is server-side rendering, not cloaking: bots and humans get the same page.
Once a page can be read, citation tends to follow quickly. The full mechanism, and how to check your own site, is in why AI can't see your site.
The constraint Insynctive hit is common. Any site that renders its content with JavaScript on the client, without server-side rendering, can be invisible to AI for the same reason, and the fix is portable.
One engine doesn't fit that mechanism. Google renders JavaScript when it crawls, and Gemini grounds on Google's index, so Gemini could read the pages the other three couldn't. Gemini was invisible for a different reason: the site had very few pages indexed, and what was indexed had gone stale, so there was little current content to surface. The rebuild closed both gaps at once. Server-rendering opened the pages to the three blind crawlers, and the 38 fresh, internally-linked pages gave Google current content to index, which is what Gemini needed. Two reasons for invisibility, one rebuild that cleared both.
How we work: audit, plan, ship, re-audit.
The plan is structured in three layers and re-prioritized on each re-audit. 15 items shipped in the first 48 hours, the fast start. The 38 net-new pages shipped over the four weeks that followed, alongside the technical and existing-page work.
L1
Technical foundation
Crawler access, server-side rendering, sitemap structure, schema, and canonicals. The prerequisites that gate everything else. 5 fixes shipped.
L2
Existing-page deepening
Restructuring pages that already rank: comparison framing, competitive positioning, and citable claim structures, each one prioritized from the audit.
L3
New content
New pages for query clusters with zero coverage, each brief built to a buyer-journey stage and the persona's language. 107 opportunities surfaced.
Audit, plan, ship, re-audit. The re-audit proves what moved and resets the priorities for the next round. It is the same audit any company can start with.
Frequently asked questions
What people ask most often about this engagement.
What did Resonate Labs do for Insynctive?
Resonate Labs ran a 150-query Visibility Audit, found the site was invisible to AI crawlers because it rendered with JavaScript, served identical server-rendered HTML so the engines could read it, and shipped 38 pages against a prioritized plan. Visibility rose 12x in six weeks, on the same matched query set.
How is the 12× lift measured?
The same 150-query set was scored at baseline and at re-audit. By the six-week re-audit, queries surfacing Insynctive went from 2 to 24 of 150, which is 1.3% to 16% visibility, a 12x lift. At the formal four-week re-audit it was already 6x (2 to 12). The denominators are identical every time, so the multipliers hold.
How long did it take to see results?
The first items shipped within 48 hours of audit delivery. Visibility was measurable at the four-week re-audit (8.0%, up from 1.3%) and reached 16% by the six-week re-audit, all on the same matched 150-query set. The full engagement runs as a quarterly program with a monthly re-audit.
Which AI engines did this audit cover?
The audit scored visibility across the four engines buyers use to research vendors: ChatGPT, Claude, Gemini, and Perplexity. The methodology is documented in How We Measure GEO.
Your turn
See where you stand in AI. Then fix it.
Insynctive started with one audit. Start with yours: 150 buyer queries across ChatGPT, Claude, Gemini, and Perplexity, scored for where you appear, win, and get cited, with a prioritized plan to close the gaps.
- Where you appear, win, and get cited across the four engines
- The exact queries where you are invisible, and who wins them
- A prioritized plan to close the gaps