Why AI tools aren’t moving the profit needle and why the real leverage lives between them
For the last two years, the enterprise AI market has followed a familiar pattern. A new tool launches. It promises to automate a specific task—sales emails, support replies, invoice parsing, demand forecasts. Enterprises buy it. Pilots run. Dashboards light up. Usage grows.
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Growth: Reactivated users — A growth opportunity
Acquisition with habit oriented engagement and compelling retention strategy fuels true product growth.
Monetization: SaaS subscription pricing and packaging
Pricing is not set in stone, it is in motion — Keep iterating and identifying the changes. Run A/B test and keep incorporating the learning in the product, price, and packaging.
Monetization: Price is right — Monetization strategy (Part I)
Pricing should never be done in silos. It must align with the overall company goal and strategy
Monetization: Price is right — Monetization strategy (Part II)
Monetization strategy should be an enabler of growth by maximizing the value captured and using that to create more value for existing users or to create value for new users.
Monetization: Price is right — Monetization strategy (Part III)
Pricing is an iterative process. Best way to get it right is to keep doing qualitative research, quantitative analysis, and roll out A/B testing to confirm your hypothesis.
A/B Testing : How to calculate sample size before launching your test
“How long are we planning to run the test? Do we have a significance yet?”. This is not an unusual situation. In fact all product managers run into this issue.
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