Level 2

Question

Offer decisioning limitation - any workaround ?

Forum|Forum|1 year ago
August 7, 2024
2 replies
1319 views

Hi All,

Currently I'm looking into one use cases which is simply lets call it event based offers but while reading Adobe docs noticed that is not supported [1] due to offer decisioning limitation :(.Yea, I know that due to fact that events are not stored on Edge therefore events based offers cannot be done, so all these rules should be profile based ... and this is exactly the problem.

Example use case:

User is trying to add XYZ product to get free delivery or adding multiple products (XYZ + ZYX + YYY) to have discount, all these need to be executed between step 1 and step 2 of basket/transaction closing but we can not freeze/pause any of the steps or processing esp. if takes too long ...etc.

In this case please advise if there is any way to workaround for such limitation of Offer Decisioning to accomplish such scenario?

[1] - https://experienceleague.adobe.com/en/docs/journey-optimizer/using/decisioning/offer-decisioning/create-components/creating-decision-rules#video

Many thanks!

Tom

Journey Optimizer

SatheeskannaK

Community Advisor

@toml78 Have a look at the edge segmentation that can be setup to meet such a use case.

https://experienceleague.adobe.com/en/docs/experience-platform/segmentation/ui/edge-segmentation

Thanks, Sathees

T

Toml78Author

Level 2

Hi @satheeskannak

Yes, I was checking this but I have feeling that is not going to work for my case due to limited Edge segmentation query types as this is not covering any recalculation options etc because honestly I cannot just simplify default case to add into cart (including count of items with time or not time window) but i have to recalculate/update in such way segments as per event data in realtime e.g. SUM $$ amount of products if such order is eligible to get free delivery, voucher ...etc.

Also looking for alternative options (e.g. computed attributes) but if you have any other idea please let me know.

Thanks

Tom

T

Toml78Author

Level 2

Edge Segmentation has limitations as well, so unfortunately my use case is not supported currently. Thx Tom

M

mdonke

Level 4

Hello @toml78

a bit unrelated... I stumbled upon this sentence:

due to fact that events are not stored on Edge

Do you have any Adobe source for this finding?

Edge segmentation supports for instance "Multiple incoming hits within a time profile of 24 hours" [1].

I'd say this can only work if events are stored on Edge. At least for 24h.

Regarding your use case: Would it be an option to help ODE by calculating a bit more on the frontend and hand in some "context data" [2]?

[1] https://experienceleague.adobe.com/en/docs/experience-platform/segmentation/ui/edge-segmentation

[2] https://experienceleague.adobe.com/en/docs/journey-optimizer/using/decisioning/offer-decisioning/api-reference/offer-delivery-api/start-offer-delivery-apis

T

Toml78Author

Level 2

Hi @mdonke

Sorry I should be much more precise 🙂 in my origin message, i was referring to fact that Edge Decisioning API does not store events on edge profile [1] therefore events based offers cannot be done. All these rules should be profile based.

Yes, exactly current idea about workaround is to calculate & put some piece of logic on frontend, based on context data (this is not super nice but all what can be done right now from my PoV as well) but I hope to see that in Offer Decisioning in near future to support to unlock potential of really sophisticated event based rules. If not mistaken Pega support such thing.

Good point reg. link from your post [2], but we cannot reuse such data immediately or as part of API call - lets hope that ODE will be improved soon for such capabilities.

[1] https://experienceleague.adobe.com/en/docs/journey-optimizer/using/decisioning/offer-decisioning/create-components/creating-decision-rules#video

[2] https://experienceleague.adobe.com/en/docs/journey-optimizer/using/decisioning/offer-decisioning/api-reference/offer-delivery-api/start-offer-delivery-apis

Thanks

Tom