Customer Journey Analytics
Customer Journey Analytics tracks what people actually do across every touchpoint, from website to store to support call, so you see where the real friction sits instead of guessing from anecdotes.
Raw touchpoint data enters on the left and narrows step by step to one fixed friction point on the right.
Reach for this when…
- Sales are dropping at a point in the funnel and nobody can say exactly why.
- Marketing and support each have their own story about the customer and the stories don't match.
- You are about to redesign a process and want evidence, not opinion, about where it breaks.
How to run it
- Map every touchpoint where a customer interacts with you, online and offline.
- Instrument each one so you capture what actually happens, not what you assume happens.
- Stitch the data into a single view per customer across those touchpoints.
- Find the points where people drop off, stall, or contact support.
- Fix the worst friction point first, then re-measure before moving to the next.
A worked example
Situation. Fernanda Lopez ran Muebles Antigua, an online furniture retailer in Antigua, Guatemala, convinced her checkout page was losing customers.
Applied. She pulled journey data across browsing, cart, delivery-address entry and payment, and found the real drop happened one step earlier: shipping cost only appeared after address entry.
Result. She moved the shipping estimate onto the product page. Cart abandonment fell, and she stopped redesigning the checkout page that was never the actual problem.
The catch
The data shows what people did, not why, so you still have to ask or watch to understand motive. It also only sees the touchpoints you instrument, so a channel you didn't track, a phone call, a friend's recommendation, stays invisible and can mislead you into over-crediting the channels you can see.
If you cannot follow one customer across two channels, you don't have journey analytics, you have two separate reports.