Owned portfolio / SaaS / search intelligence
LemRank: getting seen was only the beginning
Our SaaS product appeared in Google almost twice as often in one month. That sounds like a win—until you see how few people clicked. Here’s what the numbers taught us about turning visibility into buyer interest.
By Deepak Shukla, founder of Pearl Lemon Group / SEO consultant · Published · GSC run:
Part 01 / SaaS / search intelligence
A search product trying to reach the agencies that need it
LemRank’s public positioning is built around rank intelligence for SEO agencies. Rank tracking, AI explanations, LLM visibility and reporting sit alongside agency use cases. That creates several ways into the product, but it also creates several different conversations. A buyer comparing reporting tools is not looking for the same answer as someone trying to understand visibility in AI search.
For an agency, the stakes are practical. Can this tool help the team make better decisions, explain performance to clients and reduce the work involved in reporting? Those are the questions I would use to assess the existing pages. Repeating feature names cannot carry the whole argument. A prospective buyer needs to understand what changes in their working day and what they should evaluate before committing.
The rank-tracking feature, agency-use-case and pricing pages give us concrete places to start. They already exist; the task is to make sure each earns its place in the buying journey. A feature page should clarify the capability. A use-case page should connect it to an agency’s needs. Pricing should help someone judge the next step. That is a more useful brief than simply asking for more SaaS content.
Part 02 / SaaS / search intelligence
The visibility grew. The real challenge became getting chosen
The headline was difficult to ignore: LemRank appeared in Google 143,881 times in 28 days, against 75,609 the month before. Clicks rose from 25 to 62. If we were interested only in percentages, we could have called it a remarkable month and moved on. But those 62 clicks meant that virtually everyone who saw a result kept scrolling. For a product designed to help agencies understand search performance, that gap demanded more attention than the growth headline.
I like this example because it is our own business. We do not have to dress up the numbers for a client presentation. We can ask the harder question: if so many searches are surfacing LemRank, which of those people are actually choosing it—and why? Search exposure has value only if it reaches the people who might need the product. The immediate opportunity is not another celebratory chart; it is learning where the journey breaks down.
Yet those 62 clicks represent a click-through rate of approximately 0.043%: roughly four clicks for every 10,000 appearances. That is the real starting point. The site was gaining exposure much faster than it was becoming a dependable route into the product. My reading is not that the growth should be dismissed. It is that the growth has made the next decision clearer.
Part 03 / SaaS / search intelligence
How the product's buying journey was developed
There is documented work behind the current evaluation journey. A page-level editorial ledger dated 7 October records changes across feature, comparison, pricing, alternative and help pages. It includes clarifying the public rank-checker’s access promise, correcting comparison and pricing facts, strengthening agency-buyer criteria and linking evaluation pages to a suitable signup destination.
Those decisions are small enough to overlook in a glossy case study. They are also exactly the kind of decisions that make a software website more credible. If a comparison misstates a product fact, a buyer has a reason to doubt the rest. If a free tool’s access conditions are unclear, the first interaction can feel like a bait-and-switch. Clear promises and accurate detail belong at the centre of the sales journey.
The ledger also records an older ranking tutorial being consolidated into the maintained guide at /how-to/track-keyword-rankings. Pricing research, direct comparisons and alternatives were treated as different needs rather than interchangeable keyword targets. That gives this story substance: the recorded work was about helping people evaluate the product. Its effect on the search totals cannot be isolated from the available timeline; the documented work and the measured movement remain separate parts of the story.
Part 04 / SaaS / search intelligence
What the stronger visibility actually revealed
Growth Intelligence’s commercial weighted impression indicator reached 39,493, up 244%. Alongside that, top-10 impression share moved only from 15% to 16%. The contrast matters. LemRank was appearing across a much bigger commercially classified footprint, without a comparable change in the proportion of exposure associated with the strongest result positions.
I would take that as a reason to narrow the next phase of work, not broaden it automatically. If useful feature and comparison pages are already appearing for relevant searches, improving a few of those pages could be more worthwhile than launching another large batch. First we need the page-and-query breakdown: which buyers are seeing us, what position are they seeing us in, and which page is Google choosing?
The latest week adds urgency. From 3–9 October, LemRank recorded 63,672 impressions and 22 clicks, up 97% and 47% respectively on the preceding week. Exposure was still moving faster than clicks. A bigger footprint is valuable when it reveals a reachable opportunity; it becomes a distraction when the team treats every new appearance as equally important.
Part 05 / SaaS / search intelligence
Where several pages competed for the same attention
The same run flagged 55 potentially cannibalised queries. That is a manageable investigation, not an instruction to delete 55 pages. With feature pages, comparisons, use cases and tutorials, some overlap is natural. Two pages can appear for a broad phrase while serving very different readers.
My first step would be to put the competing URLs beside the actual searches. Where a buyer is comparing tools, the comparison should be the obvious destination. Where someone wants to learn how to track rankings, the guide may be the better answer. The problem worth fixing is not overlap in the abstract; it is a buyer repeatedly landing on a page that does not help them make their decision.
From there, the response can be proportionate. Sharpen a page’s purpose, improve the links pointing to it, or consolidate genuinely repetitive content. Preserve useful URLs and existing links before making structural changes. A good recommendation explains why one page should lead and what the other contributes. It does not hide behind a technical label.
Part 06 / SaaS / search intelligence
Why more pages would not automatically solve the problem
This is also why I would be careful with programmatic SEO at this stage. The available record does not establish a completed programmatic rollout. What it does show is a business with expanding exposure, weak click capture and several related page families. That combination calls for a quality threshold before expansion.
A comparison page needs a real comparison. An agency page needs something specific to an agency’s workflow. A tutorial needs to solve the practical problem it promises to solve. Swapping a product name or keyword into an otherwise identical page would multiply the surface area without necessarily giving anyone a better answer.
I would choose a small family of existing pages, agree what each must help the reader decide, and improve those first. Then compare their relevant searches and clicks over consistent periods. If the approach earns better discovery and useful visits, there is a stronger basis for expanding it. If it does not, the team has learned something before committing to a much larger content programme.
Part 07 / SaaS / search intelligence
From search exposure towards product enquiries
Imagine an agency owner comparing rank trackers. They want to know whether reporting will make client conversations easier, what AI visibility adds to their workflow and what it will cost. A generic pitch about search intelligence will not settle those questions. The strongest next move is to examine the queries already sending impressions to feature, comparison and pricing pages, then rewrite the pages where buyer expectations and our answers fail to meet.
That means prioritising pages by the commercial decision they support—not publishing another hundred interchangeable pages. The work can be measured: do relevant queries find the intended landing page, do more of those impressions become clicks and do those visitors show product interest? Those last outcomes need separate tracking; the Search Console report alone cannot answer them. For a SaaS founder, this is the difference between being discovered and being considered.
If this sounds familiar, the consulting conversation should begin with your existing opportunity, not an arbitrary publishing target. I can help you decide which pages deserve attention, which overlaps matter and what the team should do first. Pearl Lemon can take that agreed direction into execution. LemRank’s lesson is straightforward: once Google starts showing you more often, the commercial question becomes why a buyer should choose you.
SaaS search growth
Getting found is only the first decision.
LemRank's search impressions rose 90.3%, but just 62 clicks came from 143,881 appearances. The next challenge was attracting tool buyers rather than collecting exposure.
- 01
Discovery
Google showed the product more often.
- 02
The friction
Most appearances still did not become visits.
- 03
The next move
Make product evaluation pages more useful to agency buyers.
Search performance
More appearances. A small number of visits.
28 days: 12 September–9 October 2026 compared with 15 August–11 September 2026.
Both bars use the same zero-based scale. Exact figures appear above and in the comparison table.
Both bars use the same zero-based scale. Exact figures appear above and in the comparison table.
Scale: 0–100%. Exact figures appear above and in the comparison table.
Calculated click-through rate • 28 days
0.033% → 0.043%
Clicks ÷ impressions × 100. The proportion of search appearances that earned a click.
The search figures in full
Main window: 12 Sep–9 Oct 2026. Previous: 15 Aug–11 Sep 2026. Seven-day and flag rows use their separately stated basis.
| Metric / basis | Previous | Current | Change |
|---|---|---|---|
| Google search impressions28-day comparison | 75,609 | 143,881 | +90.3% |
| Google search clicks28-day comparison | 25 | 62 | +148% |
| Top-10 impression share28-day comparison | 15% | 16% | +1 percentage point |
| Commercial weighted impressions28-day comparison | Not supplied | 39,493 | +244% |
| Impressions • seven-day snapshot7 days: 3–9 October 2026 compared with 26 September–2 October 2026 | Not supplied | 63,672 | +97% WoW |
| Clicks • seven-day snapshot7 days: 3–9 October 2026 compared with 26 September–2 October 2026 | Not supplied | 22 | +47% WoW |
| Cannibalised queries flaggedRun-level flag; window and detection rules not supplied | Not supplied | 55 | Not supplied |
Changes are reproduced at the source’s stated precision. “Not supplied” is not zero. Weighted commercial impressions and overlap flags are source-model indicators, not native GSC metrics.
Methodology and ownership
Owned and operated by Pearl Lemon Group: first-party GSC observations
Sources, dates and measurement notes
Search figures come from Pearl Lemon Growth Intelligence’s complete, settled Google Search Console run of 12 October 2026. The main comparison is 12 September–9 October against 15 August–11 September 2026. The weekly comparison is 3–9 October against 26 September–2 October 2026; both weeks fall within the current 28-day period. The public websites and available work records were reviewed on 14 October. The supplied totals were not independently rebuilt from raw exports.
Impressions count appearances in Google search; clicks count visits from results, not unique people, enquiries or sales. CTR is clicks ÷ impressions × 100; percentage change is (current − previous) ÷ previous × 100. Top-10 impression share is the Growth Intelligence measure of exposure associated with top-10 positions, not a count of keywords on page one. Share changes are expressed in percentage points. Commercial weighted impressions and cannibalised-query flags are analytical indicators: their underlying classifications, weights and detection rules were not supplied. Missing earlier totals remain “Not supplied” rather than being reconstructed from rounded percentages.
These comparisons describe change, not its cause. Query mix, device, country, seasonality, competitors and Google updates can influence the totals. Available work records do not establish a complete release-and-recrawl timeline. Enquiry examples come from the owner’s private correspondence review, are anonymised and were not independently re-read; they sit outside the search window and have no verified organic attribution or revenue outcome.
Explore the business and supporting sources
Visit the service pages discussed in the story, or read the measurement guidance behind the figures.
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