Natural language search is available on all plans.
Overview
Senja's natural language search lets you find testimonials by typing everyday phrases instead of clicking through filters.
Instead of searching for specific keywords, you can describe what you're looking for in conversational language, and the search feature uses AI to interpret your query and automatically find matching testimonials.
Example search queries
Here are real-world examples of natural language searches you can perform:
"Show me 5-star reviews mentioning speed"
"Find happy customer stories about our support team"
"Unapproved testimonials praising our pricing"
"Video testimonials from customers tagged well known"
"Recent testimonials from enterprise customers"
What you can search for
Natural language search understands several types of information about your testimonials:
Content: Keywords, phrases, and topics mentioned in the testimonial text
Type: Video, text or social shoutout
Context: Themes or topics like "pricing," "usability," or "support" (based on tags)
Dates: Time periods like "last quarter" or "from 2024"
Tags: Tags you've created to organize your testimonials
Status: Approved, unapproved, thanked and not thanked
How it works
1. Enter your search
Click the search bar and type what you're looking for in plain language. You can be conversational. No special syntax or operators required.
2. AI interprets your query
The search processes your natural language query and determines which filters match your request. It looks at your testimonial content and existing tags to find relevant results.
3. Instant results
As you type or after you hit Enter, matching testimonials appear immediately. If you refine your search, results update automatically.
What's next
Now that you understand how natural language search works, explore:
How to search or filter testimonials. Learn the step-by-step interface guide
What are tags? How do I add a tag?. Organize testimonials for better search results
How to search by tags with AND. Combine multiple tags for precise filtering