Results · Biotech and life sciences
ingenious targeting laboratory
From page two of Google to 6.5x the inbound leads within eight months
Mouse model CRO with more than 14,000 catalog products
Today this lab's sales team opens a full inbox every morning. Organic search brings in roughly seven of every ten form fills, the catalog ranks on page one for the product searches researchers actually type, and month eight was the best organic month on record. A year ago none of that existed.
6.5x
Inbound form fills
Months five through eight against the six months before start
3.7x
Organic search clicks
16 to 10
Average Google position
Page two to page one
70%
Of form fills now come from organic search
Current share; prior tracking was broken
Month 8
Best organic month on record
Still climbing
First eight months of engagement. Multiples against the client's own prior six month baseline. Method and sources below.
The situation
The company had spent two decades building one of the largest catalogs in its category, more than 14,000 mouse models, each with real specifications, real publications behind it, and real buyers looking for it. Almost none of it was indexed. Google saw a handful of service pages and a search box.
Inbound leads had sat flat at the same monthly average for over a year. Marketing attribution had been broken for months, so nobody could say where the leads that did arrive came from. Paid search covered the gap at a cost that grew every quarter.
What we ran
01 Build
Every product became a page
We rebuilt the catalog as a searchable repository: one server rendered page per model, generated from the company's own data, with full schema markup and a request form on every page. Over 14,000 pages shipped through strict release gates so nothing thin or duplicated went live. Every inquiry routes into the CRM tagged by catalog prefix, and the tracking that had been dead for a year was repaired so every lead has a source.
02 Rank
Ranking for what researchers actually search
Scientists search by gene, by modification type, by catalog number. The page structure matched those queries exactly, so within weeks the site appeared for thousands of product searches it had never ranked for. Average position moved from 16 to 10. Around the catalog we run a technical content system, a monthly editorial series featuring published researchers who used the models, and articles answering the questions labs post in forums.
03 Run
Paid search pointed at the page that converts
With the catalog indexed, paid search stopped sending researchers to a generic landing page and started sending them to the exact model they searched for, ad group matched to page. Campaigns are managed to a cost per inquiry, not a cost per click, and the search term report is read weekly by a person.
04 Buy
Not in this engagement.
05 Book
Outreach to the labs already citing the work
Each researcher spotlight comes with an outreach sequence to the featured lab and its institution, and a separate sequence targets venture backed biotech companies building programs that need custom models. Warm inbound and targeted outbound feed the same calendar.
06 Educate
Not in this engagement.
Why it worked
Most companies with a large catalog treat it as a database. Google treats a database as one page. The shift is to treat every item as its own entity with its own page, its own schema, and its own reason to be indexed. We call this the Searchable Repository Method and it applies to any business with hundreds or thousands of discrete things a buyer might search for.
The second factor is that leads grew faster than clicks. Clicks rose 3.7x, form fills rose 6.5x. Traffic that arrives at the exact product it searched for converts at a higher rate than traffic that lands on a homepage and has to find its way.
Timeline
Month 1
Catalog audit, data model, page architecture, and release gates defined
Month 2
First programmatic pages live, tracking repaired, CRM routing built
Month 3
Most of the catalog indexed, impressions 3x the prior baseline
Month 4
Full catalog indexed, impressions 4x the prior baseline
Month 5
Form fills cross 6x the prior monthly average and hold
Month 8
Best organic month on record. Editorial series and outreach running on schedule
Who this fits
- ·Life sciences suppliers, CROs, and reagent companies with a large product catalog
- ·Healthcare and medtech brands with many distinct services, conditions, or locations
- ·Any B2B company where buyers search for a specific item and the site only shows categories
- ·Teams currently paying for search traffic to pages that do not match the query
How we report these numbers
Every case study on this site covers the first eight months of an engagement and nothing after. We chose a fixed window so studies are comparable to each other and so a strong later month cannot inflate the story.
Each result is the average of months five through eight of the engagement divided by the client's own average over the six months before our start date. Same window for every stat and every brand, so no study can pick a flattering baseline. Where a client's tracking was broken before we arrived, we say so and report current share rather than growth.
Clients are named with their permission. Raw exports behind any figure, including search console and CRM data, are available on request under NDA.
Across the other brands we run, first eight month results have landed within a few points of the studies shown here. Each is added as it passes month eight.
This study
Baseline for every stat is the six months before engagement start. Search stats use five of those six months because the sixth has ten days of console data. Lead source tracking was broken before our start, so the organic share figure is current share, not growth.
- ·Google Search Console monthly and daily exports
- ·HubSpot contact and form submission exports by first conversion date
The division of labor
Your only job is to close.