NBOUND RESEARCH
Research Methodology
This page explains how NBound Research evaluates software, constructs comparisons, and publishes reviews. It covers what our scores mean, what our limitations are, and how to use our research to make better software decisions.
Last updated: June 2026
What we research
NBound Research covers fast-moving software categories being reshaped by AI, search, automation, and modern work. Our current categories are GEO and AI visibility software, AI app builders and vibe coding tools, marketing and growth software, workplace and HR software, and workflow and automation software.
We prioritise categories where buyers face genuine complexity: too many options, poor pricing transparency, rapid product change, or a lack of independent, evidence-based coverage.
OUR FRAMEWORK
The six evaluation factors
Every review and comparison is built using the same six-factor framework applied consistently across all categories.
1. Pricing
We check published pricing directly on vendor websites and note the date. We document base plans, seat or usage-based scaling, annual vs monthly differences, and where pricing requires a sales call.
2. Feature depth
We assess features on depth, not breadth. A long feature list means less than an accurate account of whether core features work well. Features requiring workarounds are noted separately from native capabilities.
3. Ease of use
We consider the onboarding experience, interface quality, and the time a typical buyer would need to get value. Tools requiring extensive setup or technical expertise to use are flagged.
4. Integrations
We document which tools each platform connects with natively and how those integrations work. We note whether integrations are direct, Zapier-dependent, or limited to higher pricing tiers.
5. Use-case fit
We identify who each tool is built for and note where it is a strong or weak fit for specific team types, company sizes, and workflows. One tool rarely fits all buyers.
6. Hands-on testing
Where possible, we test platforms directly. Our GEO software research used a standardised prompt protocol: 25 brand prompts run across ChatGPT, Perplexity, Gemini, and Google AI Overviews on each platform reviewed.
Review metadata
Every review published by NBound Research includes:
Written by — the person or team who produced the research
Last updated — the date the review was last substantively revised
Pricing checked — the date we last verified pricing data
Testing method — how we evaluated the platform
Disclosure — any commercial relationship with the vendor
Our limitations
We are a small research team. We cannot test every tool in every configuration, and we cannot always access enterprise pricing or advanced features that require an active contract.
Where our knowledge has a gap, we say so. We do not estimate figures we cannot verify. Vendor contact does not affect scores or rankings.
Update policy
We review each published piece at least once every six months. Where we become aware of significant product or pricing changes, we update sooner. The last updated date on each page reflects when we last made a substantive change.
Related pages
Editorial policy — commercial relationships
Research disclosures — vendor relationship log
NBound Research — all categories
Contact
Factual corrections, product updates, or methodology questions: hello@nboundmarketing.com