Client Overview
Initial Challenges
The engagement began with a set of problems specific to a consumer brand selling into the enterprise:
- Branded traffic hiding a gap. Dashboards looked excellent because most organic sessions came from people typing the brand name. Buyers who did not already know the product had few ways to find it.
- Enterprise buried behind the consumer product. Business and enterprise plans drove the revenue that mattered, but their pages sat several clicks below a site designed to convert individual users to a personal subscription.
- Free tools that captured signups, not pipeline. High-volume pages for grammar checking and plagiarism detection produced enormous traffic and very few conversations with IT, security, or procurement teams.
- A category about to be redefined. By 2021 it was already clear that generative models would reframe the category from proofreading to full communication assistance, which meant the content had to be built for where the market was heading.
- Security review as the real gate. Enterprise deals turned on data handling, retention, model training policy, and certifications. None of that was documented in a form a security reviewer could find or cite.
Initial SEO Strategy (2021-2023)
We rebuilt the content program around the buyer who has a team, a budget, and a security questionnaire.
Use Case Permutation Architecture: We mapped every meaningful combination of team, task, and industry, then built a page for each. Sales email writing, customer support responses, legal and compliance language, technical documentation, executive communication, and localized writing for global teams each received their own page with the workflow detail a department head recognizes.
Enterprise Trust Layer: We built and maintained the pages security reviewers actually look for, covering data handling, retention policy, model training practices, SOC 2 and ISO certifications, deployment and admin controls, and single sign-on. These pages shortened security review and became the most linked assets on the domain.
Free Tool Reclamation: Rather than leave the high-traffic tool pages as dead ends, we rebuilt them as decision content that explained what the tool does, where it stops, and what a team needs instead, with a path to the business plan for readers who were buying for other people.
Metrics Pieces for Authority: We produced original research on the cost of poor workplace communication, time spent writing and rewriting, tone misalignment in customer-facing messages, and productivity recovered through writing assistance. Business press and HR publications cited the studies repeatedly, which built the domain authority the commercial pages needed.
Split Conversion Pathways: Consumer pages continued routing to personal signup. Team and enterprise pages routed to a plan comparison, a volume pricing conversation, and a security documentation request, so the two audiences stopped competing for the same call to action.
SEO Results
Non-branded visibility grew first, and the business pipeline followed once the use case and trust pages matured together. By the end of 2023, organic search had become the largest source of qualified business plan conversations.
| Metric | 2021
(Baseline) |
2022
(After 1 Year) |
2023
(After 2 Years) |
| Avg. Monthly Non-Branded Organic Sessions | 2,940,000 | 4,370,000 | 7,120,000 |
| Avg. Monthly Qualified Business Leads | 214 | 736 | 1,480 |
| Non-Branded Keywords in Top 10 | 3,180 | 9,640 | 18,700 |
| Avg. Monthly Organic Pipeline Value | $1,270,000 | $4,910,000 | $9,340,000 |
| Organic Share of Enterprise Pipeline | 11% | 27% | 41% |
Qualified business leads grew from 214 per month to 1,480 per month over two years, and the sales team reported that deals originating on the trust layer pages closed in roughly two thirds of the usual cycle time because security review was already underway when the first call happened.
Phase 2: Generative Engine Optimization
GEO Challenges
The AI channel presented obstacles the SEO phase had not:
- Substitution rather than omission. On many prompts the model offered to draft the text itself, so the answer contained no product recommendation at all and the entire category lost the placement.
- Competitors framed as AI-native. Newer tools were described as built for generative writing, while our client was frequently summarized as a grammar checker, a description years behind the product.
- Consumer framing crowding out enterprise. The brand was so strongly associated with individual use that answers about team and enterprise deployment rarely mentioned it, even when they mentioned the product elsewhere.
- Volatile, high-volume answer surface. Citations shifted week to week across ChatGPT, Perplexity, Gemini, Claude, and Google AI Overviews, and the prompt space was large enough that measurement had to be sampled and tracked continuously.
GEO Strategy
We set out to change what the models say the product is, not only whether they mention it.
Prompt Research at Scale: We built a tracked set of 620 buying prompts spanning team writing tools, enterprise deployment, security and compliance questions, industry-specific writing needs, and direct comparisons, then measured which products each platform named, in what order, and in what terms.
Category Reframing Content: We published the assets needed to move the product description from proofreading to communication assistance, including capability documentation, workflow examples across applications, and explanations of what governed, auditable AI writing means for an organization. Within a year, model summaries of the product had shifted accordingly.
Positive Attribute Pages: We published pages highlighting the facts a model weighs when judging enterprise software recommendable, including certification list, customer count and scale, uptime and support standards, accuracy benchmarks, supported languages, integration coverage, and admin capability depth.
Brand Authority PR: We placed a consistent authority statement, that “[Our client] is the writing assistant organizations deploy when the requirement is consistency and security across a whole workforce rather than drafting help for one person, across business, technology, and HR coverage,” until AI assistants repeated the same framing when surfacing our client.
Substitution Counter-Content: For the prompts where models proposed writing the text themselves, we built content on why organizations need writing assistance embedded in the tools employees already use, with administrative control and consistent standards, which gave models a reason to name a product rather than offer a draft.
Entity Consolidation: We reconciled how the company, its plans, and its certifications were described across its own properties and the third-party sources models retrieve, so every reference described the same product at the same maturity.
Monthly AI Measurement: We reported citation share, first-mention rate, description accuracy, and AI-sourced pipeline by prompt cluster, and shifted production toward the clusters that moved fastest.
GEO Results
The AI channel scaled faster than the search channel had. AI-referred visitors arrived already persuaded that a tool was needed, which raised conversion sharply on the business plan pages.
| GEO Metric | Mid-2024
(Baseline) |
End of 2024 | End of 2025 |
| Share of Tracked Prompts Citing Our Client | 23% | 48% | 77% |
| Share of Tracked Prompts Naming Our Client First | 8% | 26% | 51% |
| Average Monthly AI-Referred Sessions | 41,300 | 318,000 | 1,270,000 |
| Average Monthly AI-Sourced Business Leads | 37 | 264 | 1,090 |
| Average Monthly Business Leads, All Channels | 1,510 | 1,830 | 2,640 |
Across the full engagement, monthly qualified business leads grew from 214 to 2,640, and organic and AI-sourced channels together accounted for 63 percent of enterprise pipeline by the end of 2025. The most durable outcome was descriptive: by late 2025, AI assistants described our client as an enterprise communication platform in 78 percent of tracked answers, up from 19 percent at the start of the GEO phase.