Linking experiment insights to the Customer Journey

Linking experiment insights to the Customer Journey

How to communicate 'The Big Picture' of experimentation roadmap using a Mental Journey Model?

How can you prevent experiment results from getting lost among all other learnings from experiments you have conducted? How do you maintain an overview of everything you've learned about the customer over time, both for yourself and your colleagues?

Registering experiment insights

The final step after any experiment is to document your learnings. Tools like Trello, Jira, ClickUp, Asana, Airtable or Effective Experiments are useful for planning, executing, and organising experiments. You should also consider tools like Datatrics, BloomReach, Insider or BlueConic for setting up the complete customer journey's for each user type. Regardless of how you document it, having a clear overview of insights is crucial for your stakeholders.

As a Customer Experience Manager, I aim to provide clients with insights not only on learnings per hypothesis but also on their impact on the entire customer journey.

Adding value to insights

A helpful way to make experiment insights transparent is by assigning a score. This score should not only apply to the experiment number (e.g., AB021) but also link to the psychological effect on which the experiment is based, such as Social Proof, Authority, Fear of Losing, or Scarcity.

An experiment should be related to a psychological effect and a phase in the customer journey to provide clear insights.

Scoring psychological effects

Each experiment has its own impact. To link an experiment to a general value, I use the 'value' from the RICE model; the Reach, Impact, Confidence, and Effort of the experiment related to overarching KPIs. KPIs can have different scores. You can use a score between 1-3 or 1-5. The RICE model helps prioritise and plan experiments by assessing their reach, impact, confidence, and the effort required to implement them.

RICE Model Breakdown:

  • Reach: How many people will the experiment affect?
  • Impact: What is the expected improvement?
  • Confidence: How sure are we about the impact and reach estimates?
  • Effort: How much time will it take to implement the experiment?

If an experiment is a big winner, you add the 'value' score from the RICE model to the experiment. If it's a big fail, don't forget to subtract that score.

Segmenting users for phases in the customer Journey

Based on user behaviour on a website, you can segment users. For example, distinguishing between visits via Ads or retargeting, whether there was a search query, new users without conversion, or returning users with conversion.

Depending on users, projects, and industries, the criteria for a user phase will be entirely different. With these criteria of user behaviour, you can create segments within your analytics package and define target audiences for new experiments. This also allows viewing user data from different phases in the customer journey.

The foundation of the Mental Journey Model

Next is combining all psychological effects and the customer journey, making the added value per psychological effect visible per phase of the customer journey. When the wins and fails are incorporated into the model, the basis for the mental journey model is created.

Mental Journey Model


Reading and processing results

With the mental journey of the user clearly defined, it's crucial to determine where on your website a psychological effect has the most influence. For this, the following results are processed in the model:

  1. Page Types Sorted by Number of Views: Recognises which page a psychological effect adds the most value.
  2. Device Category Sorted by Number of Users: Depending on your target audience, one device category may be used more or less in a phase.

For example, during the first two phases, mobile is predominantly used, and users in the awareness phase rarely visit the homepage. However, this changes in the consideration phase.

Deriving Insights from the Consideration Phase

Result: "During the consideration phase, the homepage, along with product pages, is most visited by mobile users who value their self-efficacy."

New Hypothesis: "Since users in the consideration phase can compare previously viewed products on mobile, they can make an informed decision and purchase the product within 10 minutes."

Execution: Clearly indicate on the homepage which products the user has visited and make it possible to compare them.

Summary

By plotting psychological effects on phases within the customer journey, you gain insights into validated user behaviour. This allows your organisation's communication to align with the users need for information or confirmation.

Using the mental journey model, overarching experiment results guide new hypotheses with the same psychological effect in more effective locations on your platform.

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