REQUIREMENTS TO PARTICIPATE
INSTRUCTIONS
Cristinel is a Senior Product Manager for Adobe Target, focused on machine learning personalization in Adobe Target, Analytics for Target integration, and the product user interface. Before his current Adobe role, Cristinel held product management positions on various content management and digital marketing products focused on consumers.
Curious about what an Adobe Target Community Q&A Coffee Break looks like? Be sure to check out the thread from our latest 10/26/22 Adobe Target Coffee Break with Adobe Target Expert Drew Burns aka @Drburns27.
Topics help categorize Community content and increase your ability to discover relevant content.
@cristinel is there a document with out of the box profile scripts?
@Studley2021 - thank you for your question. The profile scripts page on Experience League includes some examples of Profile Scripts usage:
Is there a particular use case you are trying to solve?
Hi @cristinel ! Thanks for joining to answer Community Qs today, and thanks @Studley2021 for kicking off the chat!!
This question was posted by mharper5:
"I am looking for a log that can tell me the last time a feed was successfully loaded. I have one that has been stuck on Importing Items for a while."
Original Question: Recommendations Feed Log?
Views
Replies
Total Likes
Unfortunately Target does not have a log for showing when a feed import has failed. However, you can subscribe to a notification feed which can send UI, push or email messages when a feed import has failed. See this Experience League document for more details: https://experienceleague.adobe.com/docs/target/using/release-notes/system-status-updates.html?lang=e...
@cristinel , this Question was posted by KMarchewa:
"In their documentation, Adobe suggests the following guideline for determining sufficient traffic when a a Conversion metric is used for Auto-Target
"1,000 visits and at least 50 conversions per day per experience, and in addition the activity must have at least 7,000 visits and 350 conversions.:
My question is, in general, if these requirements are met, how long should it take the models to build? More generally, there is a calculator for Auto-Personalization Activities - can one use this to estimate a sufficient duration for Auto-Target or is there an alternative calculator that will work? Thanks"
Original Question: Auto-Target - Model Building and Activity Duration
If the traffic and conversion thresholds are met, first models are built within 24 hours and will keep learning and adapt to new traffic moving forward.
Automated Personalization and Auto Target are pretty similar, with the the note that AP usually requires more traffic given that it builds experiences based on the offers specified in the activity.
Hi @cristinel , this Question was posted by niocolasmeriel
"I wonder if there is a minimum of traffic or conversion needed for Recommendations to work well?
For Recommendations to work effectively/develop its algorithm is there any guideline or documentation specifically looking at the sales/conversion volumes required for the machine learning to work?
Thanks,
Nicolas "
Original Question: Is there a minimum of traffic/conversion needed for Recommendations?
Views
Replies
Total Likes
Recommendation minimum traffic is hard to defined as it can be influenced by the a number of factors such as: algorithm, filtering and exclusion rules, number of items in catalog. Some algorithms (like popularity based ones) require a low volume of traffic in order to start generating recommendations. Others, like user based and cart based require some traffic to start learning visitor behavior and be able to give recommendations. You can find more information on Adobe Target recommendation algorithms on this page: https://experienceleague.adobe.com/docs/target/using/recommendations/criteria/create-new-algorithm.h...
Hi @cristinel this Question was posted by mysticDeveloper:
"I want to create a "most popular in your favourite brand" recommendation, which with the new update it should be through the "Popularity-based" recs.
What does the field "Profile Attribute to Match" do on the new "Popularity based" recommendations?
Not sure why Adobe released an update without also making a proper documentation at the same time. Currently the documentation says "(Info coming soon)" for Top Sellers by Item Attribute and Top Sellers by Item Attribute and Most Viewed by Item Attribute. https://experienceleague.adobe.com/docs/target/using/recommendations/criteria/base-the-recommendatio..."
Original Question: Popularity based recommendations. What is "Profile Attribute to Match"?
Views
Replies
Total Likes
Thank you for raising this. Similar to the "Most viewed by item attribute" algorithm, the Top sellers by Item attribute let you select which item attribute you want the recommendation to be based on. For example, you can specify which profile attribute stored in the visitor profile to match.
We will update the documentation for Top seller items as well.
@cristinel How can I gain insights as to how Adobe AI-Driven Personalization & Recommendations features & capabilities stack-up to key competitors in the market? Is there any comparison documentation that can be referenced?
Adobe Target is a testing and personalization tool recognized as a leader in by various industry reports. Here is some more information on how Target can contribute to your experimentation and personalization programs:
Thanks for taking the time to answer some questions today. If you don't mind, I have some questions unrelated to the AI-driven personalization aspect of Adobe Target. If not, no worries.
Our org has been looking at using on device decisioning. We're excited by the simplicity and performance that's suggested in its documentation. However, most (if not all) of our use of Target is for AB tests w/ mutually exclusive test groups, and on-device decisioning doesn't (yet?) support Visitor Profile audiences. Is there any possibility that it ever will? If not, are there any suggestions on how we could achieve conducting A/B tests across mutually exclusive groups with on-device decisioning?
Unrelated, we are also seeing odd behaviors with our analytics reports. KPIs and other metrics continue to shift for groups in a test we've *after* deactivated tests, sometimes days after. We're also seeing events attributed to users in mbox assignments where it should be impossible for them to see these events (e.g., a user clicked a button that wasn't shown for the experience that Analytics claims they were given). Any thoughts on how this could happen or we could troubleshoot these issues?
Again, I hope these are not too off-topic for this venue and thank you for your time in responding to these questions.
@seeplusplus - thank you for your questions.
Unfortunately we do not have any plans to add support for visitor profile audiences in On-Device decisioning, but I would like to learn more about how you are differentiate your user groups.
As for the unrelated question, there might be multiple reasons for that. Some of them could lie in the difference on how Target and Analytics attribution work, with Analytics having longer attribution times. It would also depend on the activity type as some activities are optimizing for visitor while other per visit.
Thanks for your reply. As for how we differentiate our user groups, we are using a setup similar to this guide:
Re: Activity types. All of our activities are A/B tests w/ form based config. (Not sure if that answers your question). Are there any resources where I could read more about Target/Analytics attribution? I'm fairly fresh in the process of looking into all of this, and any further reading would be great!
Thanks again!
That's great, thanks!
Is there a way to export all the audience segments from Adobe Target? Also, will it be possible to see the Target activities in which the audience segments are used?
Please guide me to the reference documentation or how-to videos, if there's a procedure to achieve it. In case it is possible through APIs, that would be helpful too!
Views
Likes
Replies
Views
Likes
Replies
Views
Likes
Replies
Views
Likes
Replies
Views
Likes
Replies