Check the acquisition promise
Read the store headline, screenshots and description. What problem is the app promising to solve?
Study the storefront ↗Taylor Sanson · iOS
Explore the ad evidence, study the storefront, and build your next acquisition hypothesis.
01 / Creative research
Read the store headline, screenshots and description. What problem is the app promising to solve?
Study the storefront ↗Explore apps with direct store-link matches. Compare their hooks and formats without assuming the same approach works here.
Browse observed advertisers ↗Store rankings and revenue estimates describe market context. They do not establish ad spend, conversions or ROAS.
Review the market context ↗02 / Storefront & product
Study the product story and store experience behind the acquisition funnel.
03 / Market context
Keep revenue, downloads and store rankings separate from advertising performance.
While the idea for the app is great, it doesn’t really work too well. I took a picture of what I thought was poison ivy several times and sometimes it said it was poison ivy, sometimes it said it was not. Same picture from the same location.
It’s a decent guide at best but do not depend on it. It identifies several plants as poison ivy that aren’t and vice versa. Be careful using this app and always use other sources to try to confirm
I do like the simplicity of the app and was very excited to use it. Unfortunately it had far too many false positives to make it trustworthy. I thought I had to clear out my entire woods as far too much was cited as poison ivy (chokecherry, ash, hickory, etc.) but other opinions proved otherwise. I truly hope this can be improved. *Update: Increased rating due to developer response. Would be worse if I was getting false negatives, which I have not yet. Will share images w/ dev per their suggestion. Would be great to see this app become more reliable.
Ivy is an app that uses machine learning to recognize poison ivy in images.