If you’re collecting customer testimonials but not actually using them to make sharper go-to-market (GTM) decisions, you’re leaving easy wins on the table. This guide is for marketers, founders, and product folks who want to do more than just slap quotes on a landing page. We’ll go step-by-step through how to dig real insights out of testimonial data in Senja, what’s actually worth reporting, and how to avoid drowning in noise.
Why Testimonial Data Matters (and Where Most People Go Wrong)
Testimonials are gold for understanding who loves your product, what they value, and what language actually resonates. The problem? Most teams treat testimonials as decoration, not data. They grab the shiniest quotes and move on.
If you want to make smarter GTM calls—like which segments to double down on, which features to highlight, or how to fine-tune your messaging—you need to start treating testimonials as a dataset, not just a scrapbook.
Step 1: Get Your Testimonial Data Organized in Senja
Let’s not overcomplicate this. Before you can analyze anything, your data needs to be clean and accessible. Senja’s core job is to collect, store, and tag testimonials. Here’s how to make sure you’re not starting from a mess:
- Tag everything. Use tags to mark the product, use case, customer segment, or theme for each testimonial. Don’t overthink the taxonomy—start simple and refine later.
- Add context. Include info like customer name, company, role, date, and any other fields you have. The more context, the richer the analysis.
- Remove junk. If you have duplicates, spam, or vague one-liners (“Great product!”), archive them. They won’t help you learn anything.
Pro tip: Don’t wait for “perfect” data. Even a batch of 20-30 tagged testimonials is enough to spot trends.
Step 2: Decide What Questions You Actually Want to Answer
Don’t just start slicing and dicing for fun. Decide which questions matter for your GTM strategy. Some examples worth caring about:
- Which customer segments are happiest? (By role, industry, company size, etc.)
- What features do people rave about? Are there sleeper hits you’re overlooking?
- Which pain points does your product solve best?
- What language do customers use to describe value? (This is gold for copywriting.)
Ignore vanity questions like “Which testimonial sounds the most impressive?” unless you’re prepping for a pitch deck.
Step 3: Slice the Data—How to Actually Analyze Testimonials in Senja
Senja isn’t a full-blown analytics tool, but you can still do a lot with its built-in features and a bit of manual work. Here’s what works:
- Filter by Tag: Want to know what founders vs. marketers love? Filter by those tags. Same goes for features or industries.
- Search for Keywords: Use Senja’s search to see how often certain words pop up (“easy,” “fast,” “support”).
- Export to CSV: For deeper analysis, export your testimonials. You can slice and dice in Excel, Google Sheets, or even import into a basic text analysis tool.
- Group by Themes: Read through a batch and group similar sentiments. Don’t over-engineer—just jot down the top 3-5 themes you’re seeing.
What’s Not Worth Doing
- Don’t try to quantify everything. Counting the number of times “easy” appears doesn’t mean much without context.
- Avoid sentiment analysis software. Most of these tools are built for massive datasets and often miss nuance in short, enthusiastic testimonials.
- Don’t chase perfection. You’ll never have a ‘statistically significant’ sample. Look for patterns and outliers, not gospel truth.
Step 4: Turn Insights Into Actionable Reports
All the tagging and filtering in the world is useless if you don’t turn it into something your team can actually use. Here’s how to report your findings:
- Keep it visual—when it helps. Pie charts showing which features get the most love? Useful. Endless spreadsheets? Not so much.
- Use real quotes. Pull out the best lines that represent each theme or segment. Don’t just summarize—let customers speak for themselves.
- Highlight surprises and contradictions. Did a feature you thought was secondary come up a lot? Is there a pain point you’re not addressing?
- Make recommendations. Based on what you see, suggest specific GTM actions—like updating messaging, focusing on a different segment, or featuring a certain benefit more prominently.
Example simple report:
- Segment: Early-stage SaaS founders
- What they value: Integration with X, responsive support, fair pricing
- Representative quotes:
- “Integration with X saved us hours every week.”
- “Support actually responds—rare these days.”
- Action: Highlight integrations and support in founder-focused campaigns
Step 5: Share Findings—And Use Them for GTM Decisions
Don’t let your analysis live in a slide deck, never to be seen again. Get findings in front of the people making decisions. That could mean:
- Sharing a one-pager in your next GTM meeting.
- Updating your website copy with customer language (not marketing-speak).
- Prioritizing roadmap items based on what real users actually care about.
- Pitching a new campaign idea based on an unexpected testimonial trend.
Pro tip: Circle back in a month or two. Did the changes you made move the needle? Are new testimonials showing different themes? Treat this as an ongoing feedback loop, not a one-off project.
What Works (And What Doesn’t)
What Works
- Simple, consistent tagging.
- Going beyond the “best” testimonials. Sometimes the most useful feedback is buried in a quote you’d never put on your homepage.
- Sharing real customer language with your team. It beats any copy a marketer could write from scratch.
What Doesn’t
- Overanalyzing tiny datasets. Sometimes, you just don’t have enough data. Don’t pretend you do.
- Treating testimonials as sacred truth. People exaggerate. Some will gush, some will nitpick. Look for patterns, not absolutes.
- Relying only on testimonials. They’re one input—pair them with usage data, sales calls, and support tickets for a fuller picture.
Pro Tips for Avoiding Common Pitfalls
- Don’t let tagging get out of control. Too many tags = analysis paralysis.
- Archive the fluff. If a testimonial doesn’t add insight or isn’t usable as a quote, don’t count it in your analysis.
- Keep your process repeatable. If it takes hours every time, you’ll never do it again.
Keep It Simple—And Iterate
You don’t need a PhD in data science (or even a fancy analytics stack) to get value from Senja testimonial data. Focus on what’s clear, actionable, and repeatable. Start with basic tags, look for patterns, and make small adjustments. Then check back to see if your changes actually helped. That’s how you turn testimonials from window dressing into a real GTM advantage.