The success of an orchestrated journey can be seen through its results: delight through customer experience.
But, to derive the real picture of what went well and what didn’t, where the drop-outs happened, what are the hotspots, the popular route of choice, common routes behind successful closures, you need to dissect the journeys step-by-step.
Journey Builder in CommandCenter comes with a built-in reporting facility. After publishing your journeys, you can view reports specific to those journeys by accessing the journey-based reports.
What are the analyses you can see in these reports?
Journey Builder comes with three analytical components:
- Stage-wise segregation provides a split of record concentration for each stage in that journey, for the specified duration.
- Average time taken in each stage shows the average time records spend in each stage
- Overall record count shows how many records were there in each stage for the chosen duration. It also shows the number of records that passed through a transition giving insights on the progression.
Let’s look at a use case to understand how these analyses can help your business:
Zylker is a consumer electronic retail chain that is best known for flexible orders, delivery, and returns across different purchase channels. They are able to deliver this kind of consistent CX across all of their touchpoints because they connected them with the end-to-end process, managing them from one tracking system, and correcting the course by observing convergence at each stage.
Here’s the process they have created in Journey Builder:
From exploration to sale closure, Zylker can respond with the right actions to customers based on their choices. Now, to monitor the drop-outs, returns, cart abandonment, Zylker can keep a close eye on the turn of events by monitoring records movements across the stages.
Stage-wise segregation
X-axis: Stages; Y-axis: Record count
This component lets you understand in which stage your prospects and customers are stationed at, for the selected duration. By segregating them based on their stages, you can observe the popular preferred stage, see the parity of distribution, and more.
This is a progressive path with each step as stages.
By seeing the number of records in each stage, you can compare between
- Online vs store visits
- Successful transactions and abandoned cart
- Customers’ convenience in waiting for product delivery or pickup at the store.
- Number of returns versus replacements
and more.
Average time taken in each stage
X-axis: Stages; Y-axis: Average time taken
This is another chart to understand how long all of your prospects and customers stay in a particular stage on an average. This will give you the amount of time each spends on being on a stage.
Say, for example, if your prospects station on Added to cart for a long time, then it indicates they are contemplating their choice. Zylker can nudge the customer using push notifications or remind them about the item in cart.
This is a CX hotspot and identifying them at the right time, will enhance the possibility of conversion.
For another, let’s say, you identify your fulfilled package often remains in the delivery partner assigned stage for long. In which case, you can change your delivery partner or raise a conflict.
This chart to analyze the average time records spent on each stage will help you compare the average progression time and identify latency if any.
Overall record count
This chart gives you how your prospects and customers trickled down through the journey for the selected duration. Based on how they progressed, you can identify the major drop-spots, observe how their choices branched through the journey, understand preferred routes, and see how many completed their journey.
Let’s say by the number of customers opted for store pickup can mean they either feel pickup is easier, or delivery is costly or is often taking time. Likewise, you can also see the ratio of customers end up raising support requests for returns/replacements.