Getting Your Brand Recommended by AI
When users ask AI assistants for recommendations, your goal is to be mentioned, and mentioned positively. This guide covers practical strategies to increase your chances of being recommended.
In this guide
- What triggers AI recommendations
- How to influence recommendation likelihood
- Building the signals AI trusts
- Common mistakes that hurt recommendations
Understanding AI Recommendations
When someone asks ChatGPT "What's the best CRM for small businesses?" or asks Perplexity "Which project management tools should I consider?", the AI synthesizes information from multiple sources to generate a response. Getting recommended means being part of that synthesized answer.
AI recommendations are influenced by:
- • Training data presence: How often and how positively your brand appeared in the data used to train the model
- • Real-time search results: What the AI finds when it searches the web (for models with search)
- • Authority signals: Reviews, mentions in trusted publications, expert endorsements
- • Category association: How clearly your brand is linked to the category being asked about
Strategy 1: Dominate Your Category Narrative
AI systems need to understand what category you belong to before they can recommend you. If you're a CRM, the AI needs to confidently know you're a CRM, not guess based on context.
Define your category explicitly
On your homepage and about page, clearly state: "[Brand] is a [category] that [primary function]." Don't make AI infer what you are.
Create category-defining content
Publish authoritative guides about your category. "What is [category]?" and "How to choose a [category]" content positions you as a category expert.
Appear in category lists
Get listed on comparison sites, industry roundups, and "best of" lists. These are frequently cited by AI when making recommendations.
Strategy 2: Build Review Momentum
Reviews are one of the strongest signals AI uses for recommendations. A brand with hundreds of positive reviews is far more likely to be recommended than one with few or no reviews.
High-Impact Review Platforms
- • G2, Capterra, TrustRadius (B2B software)
- • Google Business Profile (local)
- • Trustpilot (general)
- • Industry-specific platforms
Review Strategy
- • Ask at moments of success
- • Make it easy (direct links)
- • Respond to all reviews
- • Address negative feedback publicly
Strategy 3: Earn Third-Party Validation
AI systems weight information from authoritative third parties more heavily than self-promotional content. Getting mentioned by trusted sources significantly boosts recommendation likelihood.
Industry publications
Get featured in trade publications, industry blogs, and news sites relevant to your market. Even a mention in a roundup article helps.
Expert endorsements
When recognized experts in your field mention or recommend your product, AI notices. Build relationships with industry influencers and analysts.
Case studies and research
Publish original research that others cite. When your data appears across multiple sources, it reinforces your authority.
Strategy 4: Optimize for Comparison Queries
Many recommendation requests are comparative: "X vs Y" or "best alternatives to X." Position yourself to appear in these comparisons.
Comparison content to create:
- • "[Your Brand] vs [Competitor]" pages: Create honest, balanced comparisons
- • "[Your Brand] alternatives" page: Yes, create this yourself to control the narrative
- • "Best [category] tools" guide: Include yourself alongside competitors
- • Feature comparison tables: Make it easy to see how you stack up
Strategy 5: Maintain Consistent Information
AI systems cross-reference information from multiple sources. Inconsistencies create doubt and reduce recommendation confidence.
Inconsistencies to fix
- • Different pricing on different pages
- • Outdated feature lists
- • Conflicting company information
- • Old product names still appearing
Keep consistent
- • Pricing and plans
- • Feature descriptions
- • Company founding date, location
- • Product positioning
Common Mistakes That Hurt Recommendations
Being too niche in your positioning
If you position yourself as "the CRM for left-handed accountants in Ohio," AI won't recommend you for general CRM queries.
Ignoring negative sentiment
Unaddressed complaints and negative reviews get picked up by AI. Respond professionally and work to resolve issues publicly.
Relying only on your own website
AI weighs third-party sources heavily. A brand that only appears on its own site lacks the validation needed for confident recommendations.
Key Takeaway
Recommendations are earned, not gamed.
AI systems are designed to recommend what's genuinely best for users. The strategies that work long-term are those that make your brand genuinely recommendable: great product, happy customers, clear positioning, and consistent presence across trusted sources.
What's Next
Understanding how to get recommended is just the start. Next, learn how to monitor what competitors are doing in the AI space and identify opportunities they're missing.