Once I was happy with the above flow, I created three simple optimisation plans below to further iterate and improve the multi .

Test 1— Optimising the hook


To see whether users interact more with the hook when placed in a more obvious place.

Test variants of the multi-trip hook placement.

Success Metrics

  • An Increase in multi-trip link click interactions.
  • Increase in overall ticket sales.

Test 2— Staged trip entry

To see if users find it faster to enter their trip details one step at a time.

One test variant showcasing a multi-step entry UI.

Success Metrics

  • A reduction in the overall average time spent in this stage of the journey.
  • Satisfaction score of 8 and above (Max 10). ( Defined by a feedback feature ).

Test 3 — Alternate basket UI

To measure whether users interact better with an alternate tab interface.

Different Basket view variants.

Success Metrics

  • Interaction with the second tab is greater than basket interaction.
  • Only 5% of overall users who submit feedback complain about the tabs.


Next, I placed each idea into an effort vs impact matrix to help decide which ideas to take forward.

Note* the following order of the ideas is based on my own technical and product knowledge.

Effort vs Impact Analysis.

Here’s a breakdown of my thoughts:

Test 1 — Optimising the hook

The effort to reposition the link would require little engineering input but may not be as effective as the other two as it is such a small change.

Test 2 — Staged trip entry

The effort is significantly more than the previous test. By applying more focus to the input fields, users may navigate through this step faster than the original, thus impact.

Test 3 — Alternate basket UI

Again, the effort is substantially large, especially with two variants, however, we may see a larger shift in core metrics as this is where users decide to commit. By having a simple UI, users might find it easier to buy.

To conclude, I decided that test’s two and three would have the most impact out of three.

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