Our Methodology: How We Evaluate AI Tools for Social Media
This page explains how we choose which tools to cover, what we look at when we assess them, and how we handle the limits of what we can know. If a review on this site does not meet these standards, tell us at [email protected], and we will correct it.
What we review
We cover software that uses AI to help with social media work: planning and scheduling, writing, image and video creation, repurposing content, analytics and reporting, social listening and community management. We choose tools based on reader interest, relevance to real workflows and market presence, not on who is willing to pay.
What we look at
Every tool is assessed against the same questions, so reviews can be compared fairly.
| Area | What we ask |
|---|---|
| Output quality | Is the AI output usable as a first draft, or does it need to be rewritten? Does it keep a consistent brand voice? |
| Workflow fit | Does it fit how teams plan, approve and publish content? Does it save steps or add them? |
| Platform coverage | Which networks and formats are supported, and how deeply (native publishing, previews, format limits)? |
| Pricing and limits | What do plans cost, and what is capped: credits, seats, connected accounts, scheduled posts, exports? |
| Data and privacy | What does the vendor say about how your content and account data are used, including model training? |
| Reliability and support | How stable is the product, and what help is available when something breaks? |
| Learning curve | How long does it take a new user to get a useful result? |
| Alternatives | How does it compare with direct competitors for the same job? |
How we gather evidence
We label the basis for what we say, so you can judge how much weight to give it.
- Hands-on testing. Where we use a tool directly, we run it on realistic social media tasks and describe what happened.
- Vendor documentation. Features, limits, pricing, and policies are checked against the vendor’s own pages, help center, and terms.
- Independent sources. Where we cite studies, platform announcements, or third-party data, we link to the original source and attribute it correctly.
- User-reported experience. We treat anecdotes and reviews as signals, not as proof, and say so.
When a point rests only on vendor claims, we say it is a vendor claim. When we could not verify something, we say that too.
Pricing and “last verified” dates
Prices, plan limits and features change often. Each review carries a date showing when its key facts were last checked. We re-check pricing and major features periodically and whenever we learn of a significant change. Always confirm current details on the vendor’s site before you buy.
What we do not do
- We do not publish invented statistics, quotes, case studies or user testimonials.
- We do not accept payment, free access or commissions in exchange for a favorable review or a higher ranking.
- We do not present marketing copy as findings.
- We do not claim to have tested features we have not used.
How rankings and recommendations work
When we recommend a tool as “best for” a given job, the recommendation reflects the criteria above for that job. We state the reasoning and the trade-offs. A tool can be the right choice for a solo creator and the wrong choice for an agency, and our write-ups say which is which.
Limits of our testing
AI tools are updated frequently, outputs vary from run to run, and plans differ by region and account. Our findings describe what we observed at the time. Your results may differ. We encourage using free trials where they exist.
Updates and corrections
If a tool changes in a way that affects a review, we update the article and note the change. If you spot an error, see our corrections process in the Editorial Policy.