Many ecommerce analyses, including many in Repeat Customer Insights look at your customer and order data as it stands today.
The Order Sequencing Analysis is different. It rewinds the ordering data and plays it back from the past to the present.
Past behavior and performance
This gives it a unique view of different customer segments. Instead of looking at customers who are part of one segment right now, it looks at how customers behaved in the past when they placed a specific order.
Each row in the analysis analyzes the nth order for all customers. The first row analyzes all customer's first orders, the second row analyzes all customer's second orders, etc. If a customer doesn't have a order for that row, they fall out of the analysis.
Inside each row, the Repeat Purchase Rate, Average Order Value, and Latency is calculated from the orders in that row.
Repeat Purchase Rate measures the rate of customers who placed an order on the prior row, placing a repeat order.
Average Order Value is what you'd expect, it's how much customers spend on average.
Latency or the longer: Customer Purchase Latency, measures the delay between customer actions. In this case, it's how long it took the customer on the previous row to order again.
Insights from the metrics
These metrics can give you a lot of insights that are normally difficult to find:
If you use paid acquisition and your Average Order Value for the first order is high, you can use that for your acquisition payback. Showing a "profit" on paid acquisition in your first order means that any repeat orders end up being extra profit.
Combining the Repeat Purchase Rate and Latency, you can guess how many customers will be reordering in what time-frame.
Insights and advice
Additionally, each row is analyzed against the Insights database in the app to benchmark your metrics against the industry and your store itself. Those come with recommendations and advice which can help you focus on troublesome issues.
Further filtering and refinement
The analysis can also be refined by the Period so only orders and customer behavior within that period is analyzed. It can also be filtered by the Acquisition Source so only customers who came from that specific source are counted in the analysis.