Great Question Organic Growth Opportunities

Create a massive directory of landing pages targeting specific professional and demographic audiences that researchers need to recruit. Each page provides screener suggestions, recruitment channels, and operational guidance for finding that specific cohort.

Example Keywords

• "recruit product managers for user interviews"
• "find nurses for research participants"
• "software engineer participant recruitment"
• "recruit small business owners for usability testing"
• "how to find niche research participants for [industry]"

Rationale

Researchers often search for the 'who' before the 'how.' By capturing intent at the audience level, Great Question can position its participant management and recruitment features as the immediate solution for these specific needs.

Topical Authority

The domain already features content on research recruitment and participant management. Expanding into specific audience segments leverages this existing topical seed to dominate long-tail recruitment queries.

Internal Data Sources

Use existing candidate attribute documentation, study setup guides, and anonymized audience criteria from the platform's help center to provide realistic recruitment parameters.

Estimated Number of Pages

5,000+ (Covering hundreds of job titles, industries, and demographic segments)

Develop a programmatic encyclopedia of participant incentive benchmarks tailored by country, research method, and session length. These pages answer the critical budgeting question every research team asks during the planning phase.

Example Keywords

• "participant incentive for 30 minute interview in United States"
• "how much to pay research participants in United Kingdom"
• "user interview incentive rates 2025"
• "B2B research incentive benchmarks by country"
• "standard survey incentive for [industry] participants"

Rationale

Incentive budgeting is a high-friction part of research operations. Providing localized, data-backed benchmarks attracts users at the exact moment they need a system to fulfill and track these payments.

Topical Authority

Great Question already ranks for 'customer research incentives' and has a dedicated feature for incentive fulfillment. This play expands that authority into thousands of localized long-tail variants.

Internal Data Sources

Leverage internal documentation on incentive fulfillment mechanics, supported payout types, and anonymized platform payout data to provide authoritative benchmarks.

Estimated Number of Pages

3,000+ (Mapping 50+ countries across various methods and durations)

Generate a comprehensive library of AI-moderator prompt templates and discussion guides tailored to specific personas and research topics. This positions the brand as the leader in the emerging AI-moderated research space.

Example Keywords

• "AI interview script for customer onboarding"
• "AI moderator questions for B2B pricing research"
• "automated qualitative interview guide for [persona]"
• "prompt template for customer discovery interviews"
• "AI research assistant prompts for [industry]"

Rationale

As AI moderation becomes a standard tool, researchers are searching for how to prompt these models effectively. Providing these assets drives users toward Great Question’s native AI features.

Topical Authority

The domain already has a footprint in AI research guides and features. Creating a prompt library establishes the brand as a technical authority in AI-driven qualitative research.

Internal Data Sources

Use existing AI feature documentation, Great Question AI help articles, and internal prompt engineering best practices to ensure high-quality, functional outputs.

Estimated Number of Pages

5,000+ (Covering diverse personas, industries, and research goals)

Build a jurisdiction-aware library of participant operations policies, including consent forms, NDAs, and disclosure templates. This targets the operational and legal hurdles that enterprise teams must clear before starting research.

Example Keywords

• "research participant consent form template [jurisdiction]"
• "recording disclosure language for user interviews"
• "participant NDA template for research"
• "GDPR compliant research consent form"
• "participant no-show policy template"

Rationale

Compliance is a major entry barrier for enterprise research. Providing these templates attracts Research Ops and Legal stakeholders who are standardizing their organization's research infrastructure.

Topical Authority

The domain's existing Trust Center and security/compliance feature pages provide the necessary signals to rank for high-trust legal and operational templates.

Internal Data Sources

Utilize Trust Center artifacts, existing privacy policies, and support documentation regarding participant communications and data handling.

Estimated Number of Pages

3,000+ (Covering multiple jurisdictions and various policy types)

Create programmatic landing pages for every tool in the modern research stack, detailing how Great Question integrates with them to streamline workflows. These pages focus on data syncing, highlight exports, and repository automation.

Example Keywords

• "[tool] integration for user research repository"
• "sync research insights to [tool]"
• "export interview highlights to [tool]"
• "[tool] + Great Question workflow"
• "automate research participant tracking in [tool]"

Rationale

Stack compatibility is a primary filter in the software procurement process. These pages capture high-intent buyers looking to ensure a new tool will fit into their existing ecosystem.

Topical Authority

The sitemap already contains specific integration pages (Snowflake, Okta, etc.) and a developer API reference, providing a strong foundation for technical integration authority.

Internal Data Sources

Use the Developer API reference, existing Help Center integration articles, and product feature specs to generate accurate technical content.

Estimated Number of Pages

1,500+ (Covering a wide range of CRM, Analytics, Collaboration, and Project Management tools)

Improvements Summary

Update the UX/customer research method guides that rank in “striking distance” by rewriting above-the-fold sections for intent match (short definition, when to use/not use, jump-link TOC) and adding concrete process content (steps, templates, examples, comparisons, FAQs + schema). Create a UX Research Methods hub and strengthen internal linking (including intent-led links between /ux-research guides and /features pages) to address cannibalization and concentrate authority across the cluster.

Improvements Details

Map each page to a primary keyword and expand with secondary/PAA terms, such as “card sorting ux,” “how to conduct a focus group,” “research operations,” “ux research repository,” and “screener survey,” then add snippet-ready blocks (numbered steps, compact tables, FAQs with FAQ/HowTo schema). Publish 6–10 spoke articles (e.g., open vs closed card sorting, focus group moderator script, repository taxonomy/governance) that link back to the main guides and include contextual CTAs to recruiting, scheduling, incentives, and repository features. Tighten internal links from a central methods hub, add “Related methods” modules on each guide, and separate informational vs product intent for card sorting (/ux-research/card-sorting vs /features/card-sorting) with reciprocal links and a single strong CTA.

Improvements Rationale

The target pages sit on keywords with meaningful volume and relatively low competition signals but have low traffic share, which suggests page-2 rankings driven by thin on-page coverage and weak SERP formatting. Adding definitions, step sequences, examples, and FAQ/schema increases featured-snippet eligibility and long-tail coverage, while a hub-and-spoke internal linking plan consolidates topical authority. Clear intent mapping between guides and feature pages reduces cannibalization and helps both informational and product-intent queries rank more consistently.