Articles exploring b2b-saas through the lens of behavioral science and experimentation. Practical frameworks for growth leaders who measure in revenue, not vanity metrics.
20 articles
The AI wrapper era is over. Solo builders shipping hyper-specific vertical tools win — not another ChatGPT skin with a logo on it.
Early SaaS founders perfect architecture for products nobody uses. The fix: find the first value moment before you build anything else.
Before building Jobsolv's AI platform, Atticus Li validated the market by offering done-for-you resume services at $2,000-$3,000 per client, serving 26 clients with a 92.3% interview success rate, then scaling to 30K+ users and $80K+ revenue.
Use AI for pricing optimization to find your optimal price point. Data-driven pricing strategies that maximize revenue and retention.
A practical guide to building an AI chatbot for your SaaS product that actually helps users instead of frustrating them with generic responses.
When a buyer lands on your pricing page, the first number they see does more work than most teams admit. On B2B SaaS pricing pages, that first number shapes the rest of the choice. If I need higher ARPA, I usually test anchors before I touch list price.
If your pricing page gets more clicks but buyers keep choosing the cheapest plan, you don't have a traffic problem. You have a revenue problem.
If your pricing page gets traffic but revenue stays flat, I wouldn't start with button colors. I'd start with buyer confidence.
Most pricing pages miss the point. They chase more clicks, not better plan mix.
Your pricing page is where product value meets hard math. When I test decoy pricing saas pages, I don't ask whether the third plan looks clever. I ask whether it lifts revenue per visitor, keeps trust intact, and improves plan mix.
Your pricing page is where your nice story meets a credit card. Most teams spend their first cycles on surface edits. I don't. I start with tests that change how a buyer frames cost, risk, and fit, because that is where the money moves.
Low traffic doesn't give me permission to guess on pricing. It forces me to test fewer, sharper things.
More trials can hide a worse business.
Most advice on saas pricing page testing assumes I have traffic to spare. If I don't, that advice breaks fast.
Pricing pages rarely fail because the team lacks ideas. They fail because the test mixes too many changes, then celebrates the wrong number. When I test annual billing anchors, I'm not chasing a prettier click chart. I'm trying to change cash flow, payback, and the quality of the customer base.
The biggest pricing-page mistake I see isn't bad math. It's showing prices with no frame around them.
Your pricing page is not where buyers start thinking about price. It's where they compare.
Most pricing page tests die for a simple reason, they chase clicks instead of cash. When I work on saas pricing page testing, I care less about a prettier page and more about whether more visitors become paid users.
"Conversion rate" means completely different things for an ecommerce site vs. SaaS vs. media company. Here's the right metric hierarchy for each revenue model, with Optimizely setup instructions and worked examples.
Schwartz's paradox of choice reveals why adding more pricing tiers to your SaaS product actually reduces conversion rates, and how understanding maximizers vs satisficers can reshape your pricing strategy.