Do you know who’s using your product?
Do you know who’s signing in every day and telling their friends?
Do you know who’s never been back since they first signed up, because they ran into an error on their first session?
If you’re anything like us, you’ve got about 10 different tools with different pieces of data on each of your users.
Your billing system, like Stripe, has the information about whether a user is paying you money, and how much.
Your transactional email system, like Mandrill or Sendgrid, has all the info on which emails a user has been sent, and which ones they’ve actually read.
Your email marketing system, like MailChimp, has info on whether the user is on your mailing list, and when they signed up for it.
Your support desk software, like Zendesk or Desk or Groove, has a treasure trove of info on what problems a user has had, and how long those problems took to be resolved.
Your analytics tools, if you’re lucky, have a bunch of data on what features a user has been interacting with and how often.
Your internal user database has the record-of-truth data on a user’s name, email address, and when they originally signed up.
You already have all the data and information to understand your users.
But it’s scattered all over the place.
Because it’s scattered and separate, you are missing the bigger picture. You’re only understanding a tiny part of the profile of each user.
That’s why we built People Analytics.
All the information on your users, all together, in one place. Instantly searchable and immediately available to everyone on your team.
When everyone on the team has access to a definitive view of each and every user, magical things can happen.
Customer support teams can get back to customers in a fraction of the time because they don’t need to dig through swathes of information spread across different tools.
Sales teams can be smarter about the leads they reach out to, reaching out faster and giving a more personalised message at the right time.
Product teams can focus their efforts on the right features by seeing who’s using what in the product, and looking at how different people at different times use the parts of the product.
Change your understanding of your users.