When it comes to use a product based on analytics, how do you rely on it ?
Vikram Sahu ꩜
5 replies
I see some reporting tools which have been doing really great job in collecting data and crushing it out into valuable input that can be used for gaining profits. but sometimes I am not sure whether the inputs that I am using are really working for me or not! Are they correct? Are there any parameters that I should measure in order to make these stats clear?
looking for a suggestion here...
Replies
Scientists sometimes collect the data with no specific purpose and only after decades they have the tools which can use/decode that data into something useful. (E.g. enormous amount of work the group of women has done a century ago to map as many stars on the sky as possible in Harvard).
So, I would suggest to do the same - collect anything you can and, trust me, that data you collect now can be a great insight for future you one day.
Even if now you are not sure, if these inputs are correct, it doesn't harm to store them, right?
If you are specifically asking about the correctness and usability of the data you have right now, then just map the analytics results to your product growth for example. If there is no mapping, then you do not need that info to look at. Of course you can use not the product growth, but something else for mapping :)
* Please do not consider personal data collection as analytical data though, that's a completely different thing!
I think, any analytics tool will give you a wide range of metrics and reports because it isn't a one fits all solution. Different numbers may work wonders for different teams. Also metrics only matter the most when they are tied in with a business decision and tracked over time.
If you don't mind could you spare a few minutes to review http://analyticsverse.com/ that was built on this ideology ?
For me no tools are 100% perfect . I use Google analytics
No tool is complete - especially when it comes to measuring human behaviour on product usage. Analyzing data is important, but relying 100% on it is not good.
Remember, data just show you one side of the story - you need more signals to decide. In my case, I consider believing my gut, connecting multiple dots, research and real interaction with users (either physically or virtually using tools like hotjar screen recording).
There will always be more data points than you need. It's though up to you what you want to do with them. Personally would recommend, creating a hypothesis and try to answer questions using the data points rather than trying to look at data and figuring out what to do.
This is the broad analytical journey for a startup