AstroColossal Blog

2016-09-13

Relevant customer journey data used includes drip click throughs, content A/B tests, actual user testing, e.g. watching the users using your product. Financial data helps build a balanced scorecard: lifetime value, upsell, churn, etc. Data from support and engagement interactions is also important.

But, looking at the data often leads to a single question, “Why?” Why did customer A visit your site and buy, when customer B didn’t. Agile use of surveys help answer these questions and iterate and make decisions based on these results.

Oh, I can help you solve your user’s mysteries.

2016-09-13

Most Customer Success frameworks are built on customer journeys: the idea of following your users through single or multiple paths of using your application, and identifying areas causing friction. But what is a Customer Journey?

Think of Agile Project Management, where you have stories and epics. A story is a short goal: A user I want to successfully create an account. An epic is a collection of stories: I want to go on vacation using your service (create an account, select a flight, purchase a flight, be allowed onto the plane, have the hotel expect my arrival, have a great vacation).

Make sure you are thinking from the perspective of the customer. Their objectives are probably different than your sales, marketing or product vision.

2016-09-13

Tracking user journeys requires your company to data efficiently, since you can’t watch over all your user's shoulders. The more data sources you can integrate, the more informed you are. This often means making decisions early on in the design process to make sure your APIs are able to easily capture and serve this data. The more you can build the product in a way that makes it easy to track user date, even if using an external service, Mixpanel, etc. is less work later on, when you invariably discover you need it.

Also having a defined goal allows you to use real statistical analysis to see if your data is in any way correlated. It's super easy to get focused on a data point, spend months improving it, only to realize it doesn't move any needles. That's an awesome thing to have to explain to your boss.