Have you shipped on our edition?
AEP Standard, AEP Prime, AEP Ultimate, and AEP Healthcare Shield are not the same product. They differ on the identity service (Prime adds online/offline identity stitching, Ultimate adds federated audience composition), segmentation (streaming evaluation, edge segmentation, look-alike modelling are gated by edition), RT-CDP feature availability, Customer AI and Attribution AI access, and the regulatory framework the edition slots under (Healthcare Shield is HIPAA-eligible; the other editions are not). Adobe Experience League maintains the edition matrix; cross-reference any partner pitch against it. Ask the AEP implementation partner which editions they have shipped on, and ask them for a named client reference on your edition specifically. If they cannot produce one, you are funding their training, and the cost of that training tends to land on your timeline. The r/AdobeExperience subreddit has multiple threads from teams who learned this the expensive way during the Healthcare Shield rollouts of 2024.
Show me your last failed rollout
A serious AEP implementation partner has at least one rollout that did not land. Schema drift, source-data quality, attribution disagreement, RT-CDP and AJO sandbox mismatch, identity stitch debt, RLS scope change late in the engagement, something. Ask them to name it, walk you through what went wrong, and tell you what they would do differently now. Anyone who claims a perfect record either has not shipped enough rollouts to encounter the failure modes, is hiding the lessons, or is selling. This is the single highest-signal question in the entire conversation; every other answer is secondary. The Stack Overflow [adobe-experience-platform] tag and the Adobe Experience League community forums are good public sources for the failure modes that recur (XDM redesign mid-flight, identity namespace collisions, IP-pool warm-up surprises, frequency-cap conflicts). A partner who has not learned from at least three of these has not seen enough rollouts to be trusted with yours.
How do you handle row-level security?
Row-level security in AEP is where most enterprise rollouts get stuck, especially in regulated industries (financial services, healthcare, public sector) where data-access controls cannot be retrofitted. It interacts with how attributes are surfaced to RT-CDP audiences, AJO journey context, and CJA reports. A serious AEP implementation partner has a written pattern for RLS and can show it to you in 30 seconds. The pattern usually involves attribute-based access control (ABAC) on the schema field-group level, mapped to sandboxes and user-group roles, with a written delivery contract to the activation layer that specifies which fields cross which boundary. The Adobe Experience League documentation on attribute-based access control is the canonical reference, but the implementation patterns live in partner playbooks, not in the docs. If the partner says "we figure it out per client" or "it depends on Adobe support", they have not shipped one. RLS is the schema-design version of identity stitch debt: cheap to do right in week two, expensive to fix in week eleven when the production activation cannot export the audience.
Who owns the eval harness?
Every audience you ship in AEP needs an eval. A test set with ground-truth labels (the customers who should be in the audience, the customers who should not), run before activation, run again 30 days post-launch to catch drift, run quarterly thereafter. Most partners skip this entirely and call coverage testing "QA", which is not the same thing. Ask the partner who writes the eval, how big it is (we treat 100 cases as the floor, 500 as a reasonable target for production audiences), how the ground truth is generated, and who reviews the results. If the answer is "the client", you are paying for a setup, not an outcome. The eval-first discipline came from the AI/ML side originally; r/MachineLearning has a long tradition of arguing about test-set design, and the practice has fully crossed over to enterprise marketing over the last 18 months. The Anthropic and OpenAI eval guidance, both available as published documentation, are the cleanest references for what a serious eval harness looks like.
How do you measure success?
A serious AEP implementation partner agrees on the success metric before kickoff, with a number and a date written into the SOW. Common metrics for the first 90 days: audience size delta versus the prior approach (with a defensible methodology), journey conversion lift against a holdout (the holdout itself is part of the spec), time-to-decision on attribute changes (from request to production in CJA), and the all-in run cost of the platform per quarter (licence plus services plus team). The CFO test applies: would your CFO defend this metric in a board meeting next quarter? If not, change the metric before kickoff. The Forrester Total Economic Impact studies for AEP, AJO, and RT-CDP are the closest thing to a public benchmark; they are available from Adobe on request when you are in the buying cycle and worth reading line by line before you sign with any partner.
What does the kill clause look like?
Every AEP implementation partner should agree to a kill clause in the MSA: both sides can walk after the discovery sprint (typically the first two to four weeks) with no penalty if the success criteria cannot be agreed in writing. The clause is the discipline. Without it, the engagement drifts into status-deck mode, the partner stays embedded indefinitely, and nobody is accountable for outcomes because nobody has agreed what the outcomes look like. The Quora 'How to fire your agency' answers, written mostly by CMOs and VPs of marketing, always come back to the same point: the kill clause is the one thing that keeps both sides honest, because it forces an explicit conversation about success criteria at the start, when the leverage is balanced, rather than at the end, when it is not.
Further reading
Real, named sources the editor can swap in for specific URLs. We do not auto-link these because the right link changes over time. If you find a great primary source, write us and we will update the note.
- Adobe Experience League partner documentation. Adobe's official partner program tier list and edition matrix. Cross-reference against any partner pitch.
- r/AdobeExperience and r/marketingautomation. Practitioner threads on AEP rollout failures, RLS gotchas, and partner-selection regrets.
- Stack Overflow tag [adobe-experience-platform]. Schema, Query Service, and identity-stitch questions answered by people who have shipped.
- Forrester Total Economic Impact (TEI) studies for AEP and AJO. The honest numbers on cost, value, and timeline. Available from Adobe in the buying cycle.
- Adobe Experience League Community Forums. Adobe-monitored Q&A, slower than Reddit but more accurate for edge-case behavior.
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