Unfiltered: Adobe Analytics – Key takeaways from session #2

Tips to strengthen engagement, ideation, and foster a culture of experimentation using Adobe Analytics, Adobe Target, and more.

Our recent Unfiltered: Adobe Analytics session focused on how organisations can enhance experimentation practices and ideation using Adobe Target, Adobe Analytics, alongside complementary platforms such as FullStory and Mixpanel.

Participants explored practical approaches to hypothesis development, A/B testing, driving user engagement, and developed some tips for creating a successful culture of continuous learning and experimentation.

Below is a quick summary of 8 key takeaways from the discussion which you can begin applying to your own analytics practice today.

8 ways to strengthen tool engagement and experimentation culture in your organisation:

1. Align objectives and KPIS: Ensure personal objectives are aligned with business objectives and that the impact is codified. We noted that establishing some KPIs that link clearly to business goals and experimentation outcomes helps define clear expectations for success.

2. Establish a semantic layer: Agree consistent definitions for all key metrics. Employ a Semantic Layer to create an agreed-upon, single source of truth (e.g., what exactly constitutes your “monthly active users” to avoid it being subject of debate later).

3. Define success upfront: Avoid ambiguity later by codifying what success looks like in business commercial terms and how it will be measured before the test results come in. Again, this prevents confusion and subjective debate afterwards.

4. Adopt a unified customer journey framework: Align metrics and priorities around shared understanding of the full customer lifecycle. Agree on your organisation’s unified customer journey and understand the upper to middle experience and major points of opportunity beyond just final conversion. This helps to view the holistic picture, highlight any problems (e.g. acquisition cost), and observe any negative knock-on effects – e.g. a successful test to reduce bounce rate at the top of funnel could increase low-quality traffic further into the funnel or perhaps in other directions, affecting measurement more broadly across products or departments.

5. Don’t trust averages… Instead, question “what’s that average hiding?” – check for differences in performance across segments (e.g. devices type – desktop vs. mobile) or cohorts to find genuine learnings and uncover hidden trends rather than baking in any generalised, face-value insights into your onward decisioning.

6. Embrace and communicate “failures”: This tip comes up often because it’s difficult to do. Sharing lessons from unexpected or negative results often represent savings if reframed in commercial terms – e.g. ‘We saved X by not doing Y’ – and always provide valuable learnings for your team. Communicating these failures or unexpected results fosters a culture where it’s okay to fall, get up, and pivot to the truth or your next best set of actions quicker.

7. Create champions and super users: Take the time to Identify, empower, and support enthusiastic advocates or ‘super users’ across teams. These users multiply your ability to reach/influence the business and accelerate adoption and enablement.

• Provide shared spaces to communicate and celebrate success: Use Slack/Teams channels, in-person or digital meetings where super users can discuss ideas, share knowledge, and celebrate incremental progress and bigger successes.
• Continuous education and reinforcement: Provide ongoing training and refreshers to sustain engagement and skill development. Continuously educate and reaffirm the process, resources, definitions, and guidance – remember these are all sustained efforts, not one-time events.

8. Gamify participation: Use friendly competition and success stories to boost enthusiasm and collaboration. Develop and share narratives that spotlight any progress and help contribute to light-hearted competition across teams or departments – e.g., a quick message: ‘of the 20 ideas we had, we validated 4 and are currently seeing a 5% decrease in customer support requests’.

Concluding insights:

• Building maturity with Adobe Target and Analytics requires not just technical proficiency but organisational alignment and cultural buy-in to be aware of.
• Testing should be collaborative, inclusive, and celebrated effort, not siloed or fear-driven.
• ‘Super users’ and champions play a vital role in driving sustained engagement, bridging gaps between technical teams and the wider business.
• Ultimately, success depends on clear processes, shared definitions, transparency, and a culture of curiosity.

Continuing the conversation:

We welcome you to join us at our next user group event to connect with peers, share your challenges, and discover ways to drive analytics forward by addressing common Adobe Analytics pain points.

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