☕[AT Community Q&A Coffee Break] 2/24/21, 9am PT: Rob Hornick, Senior Product Manager for Adobe Target☕

@kadcock-1 Here's a helpful link, it mentions all the limits in Adobe Target: https://experienceleague.adobe.com/docs/target/using/troubleshoot/target-limits.html?lang=en#orderid-parameter

Specifically the section:

Profile scripts

• Recommended limit of active profile scripts: 300

• Recommended limit of total profile scripts per account: 2,000

Hope that helps!

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@fdmamg wrote:

Hey, @rhornick any preference or best practices on using auto-allocate vs. sample size calculator for a/b testing?

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Hi @fdmamg ! Auto-Allocate can be used almost any time you would run an A/B test, but it can be especially good to use in the following circumstances:

• You have a limited amount of time for your test. This can be the case when a test is only relevant for a period of time (e.g. a promotion tied to President's Day Weekend or "The Big Game", or a landing page associated with an external email blast or a conference). Auto-Allocate begins shifting traffic to winners before the result is final and allows you to realize more lift in a shorter amount of time than traditional A/B tests.
• You want to test more than two experiences. Traditional A/B/N test methodologies require much more traffic when you add more experiences. Because Auto-Allocate reduces traffic to losing experiences, it's able to do a better job of finding differences between winning experiences.
• You don't want to worry about the statistical calculations. This one is self-explanatory!

You might want to run a classical A/B test under the following circumstances:

• You need a high degree of confidence about the magnitude of the difference between experiences. Because Auto-Allocate shifts traffic to winners, you may have a wider degree of uncertainty around the "true" conversion rate (or revenue, etc.) of a losing experience.
• When it's important to you to say that "there was no winner" within a fixed timeframe. Traditional fixed-horizon A/B testing has a defined end date for the test and at the end of that timeframe, you can say "We did not reject the null hypothesis; version B was not proven better than version A." Auto-Allocate doesn't have a fixed end date in mind, so you might be left with a less definite conclusion.

@toddweston  @rhornick Re: using custom attributes in Auto Personalization-- it seems like Target is pulling in custom analytics segments shared to the Experience Cloud, but no other Analytics data other than standard metrics. We are specifically interested in key custom events that have been set up to define success actions on the site.

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@pvanhelvoirt wrote:

@Rob_Hornick How do you keep everything manageable and maintainable when scaling up the number of A/B tests and setting up for personalisation at scale across multiple customer journeys? Any advice or best practices you can share?

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Hi @pvanhelvoirt ! This is a challenge to answer concisely within the scope of a forum post, but the best answer I can give is that you need to set up a testing/personalization organization and have a repeatable process that is followed for all tests/personalization activities. The Target Welcome Kit provides some general guidance on how you might do this. For specific and concrete examples, I would point you at the excellent customer sessions our customers have shared at Adobe Summits in the past. You can see a listing of all Target sessions from Adobe Summit 2020 here:

https://www.adobe.com/summit/2020/sessions.html?Products+%26+Services=Target

The upcoming Adobe Summit 2021 features 3 sessions that I think will address your question:

https://portal.adobe.com/widget/adobe/as21/catalogsum2021?search=910

https://portal.adobe.com/widget/adobe/as21/catalogsum2021?search=908

https://portal.adobe.com/widget/adobe/as21/catalogsum2021?search=907

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@amelia_waliany wrote:

Hi @rhornick , thanks for taking the time today! This questions was posted by yza085

geoffreyl854413: "In as few words as possible, what is the primary advantage of using Automated Personalization vs. Auto Target" 

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Hi @10815929 ! Auto-Target (AT) uses personalization to select the best experience for a visitor and builds a predictive model per experience, while Automated Personalization (AP) uses personalization to select the best combination of offers for a visitor and builds a predictive model per offer. That means:

Auto-Target is better when:

• You want to select the best experience per visitor.
• You have between 2 and 10 different experiences to choose between.
• You want to make changes across multiple pages (Auto-Target allows an experience to span multiple pages.)
• You want to consider interaction effects between offers (Automated Personalization builds a model per offer and does not consider interaction effects between them.)
• You want to use Adobe Analytics to analyze your activity or use an Adobe Analytics metric as your success metric for the activity. (Auto-Target supports Target's A4T integration.)

Automated Personalization is better when:

• You want to select the best combination of offers per visitor.
• You have dozens of possible offers resulting in hundreds or thousands of unique combinations. (Because AP builds models on a per-offer level, you can still get enough traffic to each offer to develop a prediction.)
• You want to use flexible rules to restrict combinations of offers or restrict offers to certain audiences (AP allows you to build exclusion groups and offer targeting rules) but don't mind ignoring interaction effects beyond this (AP does not consider interaction effects.)
• Avoid AP when you want to make structural or navigational changes, or changes across multiple pages -- Auto-Target is better for making non-offer-related changes.

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@amelia_waliany wrote:

Hi @rhornick, this question was posted by christiner93676: "Please provide best practice / recommendations on leveraging traffic allocation methods (auto-allocate to best experience vs. auto-target for personalized experiences)"

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Hi @15110672 ! The choice here really depends on your goal.

Auto-Allocate will result in a non-personalized overall winning experience being chosen for most visitors.

Auto-Target will result in a personalized experience chosen for each visitor, with multiple experiences receiving traffic.

Apart from this distinction, there's one additional consideration to keep in mind. Because Auto-Allocate is non-personalized, it can get lift more quickly than a personalized model can. So Auto-Allocate is preferred in time-constrained circumstances (e.g. promotion around a holiday, landing page for an email campaign, registration page for a conference) when Auto-Target might not get to build personalized models. Auto-Allocate can also be preferred when you have many experiences to test, but little traffic (for example, if with your site's traffic, running a standard A/B test takes 30 days to reach significance, and your content changes monthly, Auto-Target will likely not be able to produce personalized models in a timely fashion to deliver lift.)