how does customer loyalty work?

[kr8tive]

hi i tried to categorize customers with the segment called 'customer loyalty'

but i find it very confusing and need clarification.

i used the segment that is like below 

hit bucket

visit container page = A

and

hit container order exists

then i tried to filtered it with customer loyalty with orders on top

when i broke it down with visit number, most of new customers had visit number 1 and none of return customers and loyal customers were included.

return customers and loyal customers had figures starting from visit number 2

this is so far understandable. but when i looked into visitor id that is under visit number 1, 

a person who made 4 purchases was included as new customers and the same visitor id was also included in loyal customers with 20 purchases at the same day.

i thought if a person makes more than 3 orders he or she should be included in loyal customers and not both (new and loyal) and that person even had 4 purchases and categorized as new customers. i even looked into the hit depth of a person who made 25 orders in visit number 1 and it seems the person really has made 25 purchases after or before visiting page A.

my question is why visitors with more than 1 purchases are included in new customers. some of them even had more than 20 purchases in visit number 1 and still were categorized as new customers. Also shouldn't those with more than 1 purchases move to loyal customers and not included in new customers? these cases can be considered as duplicates.

i thought it is the # of purchases that differentiate the types of customers and not visit number but the figures in workspace don't make sense to me

thanks in advance

[Jennifer_Dungan · Accepted solution]

While I don't use this dimension much myself (we have a subscription based site... users can't purchase more than once, subscriptions are often renewed automatically and not where they can be tracked, etc)....

But I suspect that this dimension (because it's a dimension and not a segment - https://experienceleague.adobe.com/docs/analytics/components/dimensions/customer-loyalty.html?lang=e...) works similarly to the Return Frequency dimension... 

In that case, the same user will show in multiple buckets (within the reporting period a user may have returned in the same day, then later returned after 2 days, then again after 8 days, then again after 16 days, etc) which would then place this user in "Less than 1 Day" AND in "1-3 Days" AND in "7-14 Days" AND in "14 days to 1 month".

Also, how I read the documentation, these don't indicate exclusivity...

Dimension items include the following:

• Not a customer: At the time of the hit, the visitor has never made a purchase before.
• New customers: At the time of the hit, the visitor made a single purchase before.
• Return customers: At the time of the hit, the visitor made two purchases before.
• Loyal customers: At the time of the hit, the visitor made three or more purchases before.

---

These are all based at HIT level.

A user could in one month appear in all 4 buckets...

They come to the site, never having made a purchase... therefore "Not a Customer", then they make their first Purchase and become a "New Customer"... the record that was previously recorded as "Not a Customer" wouldn't be removed... that user wasn't a customer at that time, on whatever pages they visited or actions they performed.

Similar, if the user makes multiple purchases, either in the same visit, or within your reporting period, they could easily be flagged as a "Return Customer" and subsequently a "Loyal Customer" if they make enough purchases...

If you want to see exclusive behaviour, I think you will have to make your own Segments with proper exclude rules.

This should be similar to how I created non-overlapping New and Return Visitor segments in a presentation I did at Summit (then an encore for Skill Exchange) https://experienceleague.adobe.com/docs/events/the-skill-exchange-recordings/analytics/may2023/rocks... 

You should be able to create a similar "exclusion" logic based on Orders..

[kr8tive]

wow, thanks. especially the link to the presentation helped me a lot.

[Jennifer_Dungan]

You're very welcome