Use case · Pipeline from search

Book more demos and trials from search.

Your traffic chart is green and your demo count is flat. We rebuild the keyword and prompt map around the queries that end in a vendor decision, rewrite the pages those buyers land on, and get graded on demos booked and trials started.

Forecast set before kickoffDemos and trials, not sessionsFounder-led
Real client results. Want results like these?

Demos booked · 90 days · CRM-verified

Day 0Day 30Day 60Day 90
Conservative forecast scenario10 demos
Demos booked by day 9059 demos booked
Trial starts from solution-aware pages3.1× lift

Why teams pick this use case

The dashboard is green. Sales feels nothing.

This is the most common reason a marketing leader books the call. Not "we want more content". One of these three is happening right now, and someone above you has noticed.

01

"Traffic is up. Demos aren't."

Sessions and impressions climb every month, the demo count doesn't move, and every QBR becomes a defense of the channel. The terms winning are not the terms buyers use when they are ready to buy.

What it costs: a channel your CFO reads as a cost center
02

"The wrong people are signing up."

Signups arrive, but they are students, job hunters, or curiosity traffic from the wrong region. Sales stops working the inbound queue, which makes the channel look even worse than it is.

What it costs: sales trust in every lead marketing sends
03

"We rank for the category, not the purchase."

You own the broad head term and lose every "best tool for [use case]" and "[competitor] alternatives" query. Those are the pages buyers read in the last week before they pick a vendor.

What it costs: deals decided before you enter the room
All three are the same problem, and it is not a volume problem

The diagnosis

Most programs optimize the query. We optimize the decision.

Before we chase a keyword or a prompt, it goes through the kill test: after ChatGPT or Google answers this, does the buyer still need a vendor? If the answer is no, winning it produces a visit and nothing else. That single filter is why traffic and demos come apart, and why cutting queries usually raises pipeline.

"what is customer success software"Killed · no vendor needed
"how to reduce churn"Killed · answered in full
"best customer success software for SaaS under 50 customers"Chase · books demos
"[competitor] alternatives for mid-market teams"Chase · switcher intent

On the reference engagement we tested 412 prompts and keywords and kept 37. The program that booked 59 demos chased 9% of the map its predecessor was chasing.

Prompts and keywords tested412
Kept after the kill test37
Demos booked in 90 days59 · forecast said 10

What we actually ship

Everything that has to change for demos to move.

Not a content calendar. A rebuilt map, rebuilt pages, and a rebuilt path from page to booked call, run by one senior team against one number.

01 · The map

Rebuild the query and prompt map

Every keyword and prompt runs through the kill test before a word is written, so the map only holds queries that end in a vendor decision.

  • Full query and prompt inventory
  • Kill test on every entry
  • Paid search terms read for demo evidence
  • Killed list published, not buried

Moves: Share of buying queries

02 · The pages

Build the pages buyers decide on

Solution-aware BOFU pages, hand-researched, SME-reviewed, and written for someone who arrives already educated.

  • Solution-aware landing pages
  • Use-case and segment pages
  • Senior editing on every piece
  • Proof modules inside the page

Moves: Demo-intent traffic

03 · The shortlist

Take the comparison surface

Comparisons, alternatives, and best-of pages are the last thing a buyer reads. We take the ones you can own and the ones third parties control.

  • Versus and alternatives pages
  • Best-of and roundup inclusion
  • Review-site presence
  • Competitor claim checks

Moves: Shortlist inclusion

04 · The path

Rebuild the path to the demo

Ranking is half the job. The other half is what the page asks for and how hard it is to say yes.

  • Offer and CTA placement
  • Form length and friction cuts
  • Trial path for self-serve motions
  • Internal links from proof into the path

Moves: Page to booked call rate

05 · The filter

Stop counting the wrong signups

Wrong-fit signups are a targeting artifact. We narrow the queries and tighten the pages so sales trusts the queue again.

  • ICP and geo qualification
  • Intake questions that segment
  • Wrong-fit sources pruned
  • Lead quality reported separately

Moves: Lead quality sales will work

06 · The scoreboard

Grade it against the forecast

The forecast is set before kickoff on your funnel data, then we grade ourselves against it in writing every month.

  • CRM and GA4 wiring in week one
  • Demo and trial source captured
  • Monthly actuals versus forecast
  • What we are changing next, named

Moves: Budget you can defend

How the 90 days run

Diagnosis first, then waves, measured throughout.

Same engine as every other use case. What changes is the order of operations and what we grade first.

01

Week 1 · Diagnose

CRM and analytics wiring, technical audit, then the kill test across the full query and prompt set. You get the map, the killed list, and the forecast before anything ships.

Artifact: prompt map, kill list, 3-scenario forecast
02

Weeks 2 to 12 · Build the waves

Wave one recovers the pages closest to a purchase. Wave two takes comparison and alternatives. Wave three widens into the use cases and segments that convert, refreshing wave one as data lands.

Artifact: shipped pages, every one tied to a query that survived
03

Always on · Grade it

Demos, trials, and source recorded every week. Monthly report compares actuals to the forecast and names what we are changing next, including what did not work.

Artifact: monthly scoreboard versus forecast

The scoreboard

What we grade ourselves on.

Set before kickoff on your funnel data, graded monthly in writing. If the model cannot clear a 4× return, we tell you before you spend a dollar.

Metric 01 · Primary
Demos booked

Counted in your CRM, not in analytics. Split by source so the channel stands on its own.

Graded monthly vs. forecast

Metric 02 · Self-serve
Trial starts

For self-serve and sales-assist motions, tracked separately from demos so neither hides the other.

Graded monthly vs. forecast

Metric 03 · Quality
Demo to MQL rate

Whether the demos are workable. Protects against a volume win that sales quietly ignores.

Reported with the raw count

Metric 04 · Finance
Attributed pipeline

Pipeline traced to a source under the Two-Witness Rule, with raw always shown next to corrected.

Reported to your board

Results · From the monthly reports

Real case studies, not screenshots.

Demos booked, trials started, and pipeline your CFO can trace back to a source.

Case study 01 · Rasa

Open-source conversational AI · $40M+ raised

ML engineers and platform teams at large enterprises build assistants and voicebots on Rasa. Attribution recovery plus the full program: both channels compounded, AI search the steepest.

+237%
AI-search influenced pipeline · Mar+Apr vs Jan+Feb
+106%
Google-influenced pipeline over the same window
2.3×
Daily lead pace vs the prior window
Read the case study ↗
Case study 02 · Waitwell

Queue-management SaaS · Enterprise, 60-120d cycle

Virtual queues for universities, banks, hospitals and government. Six-month forensic audit: real lift after stripping out B2B holiday seasonality.

+124%
Google-influenced pipeline · Last 3 mo vs prior 3
89%
Of AI-search buyers reached MQL or beyond, ~2× baseline
+102%
Intake-form completion, outpacing raw inbound
Read the case study ↗
Case study 03 · Lendbuzz6-week window

AI auto financing · $2.1B raised, pre-IPO

Approving thin-credit and no-credit buyers through dealerships. Zero to majority AI visibility in six weeks, outranking Capital One and Bank of America on the buying prompt.

0→60%
AI visibility across 7 tracked LLMs · 6 weeks
#28→#1
Google rank for "no credit auto loans"
7 / 7
LLM sources surfacing, +4 new buying prompts won
Read the case study ↗

In their words

The people who signed off on it.

"The partnership with Rock The Rankings contributed to clear improvements in organic performance across Canada and Australia, particularly for MoonPay's high-value transactional keywords and pages."

LB
Luc Bouvier
Head of SEO at MoonPay

"Rock The Rankings have really gone above and beyond, in terms of exceeding our expectations in both their communications and their strategies around marketing. They're very specific at what they do. They've been able to help us get to positions 1 and 2 for our most valuable keywords."

EU
Eric Unterberger
Digital Marketing Manager at Webconnex

"Justin and his team have been phenomenal from Day 0, and the consistency in quality and the measurable results they have delivered have been a true transformation to our business. We are extremely happy and we have already recommended them to our friends."

GM
George Makkoulis
Co-Founder at Keragon

Hover to pause and read

Straight answers

Asked on every call.

If yours isn't here, bring it to the call. Same unpolished answer either way.

01How fast do demos actually move?+

Pages ship from week two, citations move in weeks, and demos usually move inside the 90 days. The reference engagement booked 59 against a 10-demo forecast. Slower categories with 120-day cycles see the leading indicators first: demo requests from named accounts, then closed pipeline a quarter later.

02Our traffic is already low. Does this still apply?+

Yes, and it is usually easier. When there is little traffic to protect, we can rebuild the map around purchase queries without unwinding a decade of content decisions. The forecast will be built on your funnel maths, not on a traffic multiple.

03Do you touch paid search?+

We do not run your paid budget. We do read it, because your search terms report is the cheapest evidence available of which queries convert to demos. If a term buys demos on paid, it earns a page.

04What if the problem is our ICP, not our traffic?+

Then we will say so in the first two weeks, and the fix is the map, not more pages. Wrong-fit signups are usually a targeting artifact: broad head terms plus an ungated trial. We narrow the queries, tighten the pages, and quality moves before volume does.

05Who is this wrong for?+

If you need leads next week, have no working sales motion, or cannot give a channel 90 days, don't hire us. This use case rewards teams selling considered B2B SaaS deals who want a durable channel, not a spike.

Next step

Your GEO plan, built on your numbers.

Give us your domain and your pipeline goal. We map the prompts your buyers are asking, build your GEO marketing plan against them, and forecast the pipeline the next 90 days can realistically produce.

Your plan · Walked through live
Founder-built
Justin Berg
Founder · Rock the Rankings

What we walk through

01Your prompt map: the buying prompts and queries that land you on a vendor shortlist.
02Where you show up today vs. your three closest competitors and where the gaps exist.
03The 90-day sequence: what we would ship, in what order.
04The 3-scenario ROI forecast, run on your actual numbers.
No SDRs · ONLY SENIOR OPERATORS · 300+ B2B SAAS ENGAGEMENTS