Shaping agent behavior and persona — Klook
Asking questions like: How an agent speaks, what do we think about anthromorphic responses, and what user problem does the agent solve? | Nov 2024 - Jun 2025
Iteration 1: Tours and activities comparison tool Sep-Nov 2024
What is it? The MVP of this feature would appear on the search results page for day tours. Users would be able to select 2 tours to compare. This feature didn’t have a text field, and users would have to use the prompts provided.
Content design challenges: Explaining to users what this feature is and what it could do for them. This was difficult to fit into the entry point, which was as mall circle with space for maybe 2 letters. Both product and design were not willing to budge on the size of the entry point. While I tried to explain that the limited UI space would negatively impactu sers’ understanding of the entrypoint, product and design were insistent. My manager, a product director, was also insistent that this entrypoint would work just fine.
So, in the first iteration of the content, I did my best with the space available, and figured this was something I could prove with user testing later on. To come up with “VS”, I tested this content concept on non-product and localisation colleagues.
User testing in Australia: We conducted usability and feasibility tests, and found that while the feature was fairly easy to grasp and useful, it lacked a useful intoruction. Users, within the context of the test, already found it frustrating and took them several screens to grasp what the feature was, and what it could do for them.
In summary, we found that the lack of affordances and guidance to users made it difficult for them to grasp and use the feature effectively. I emphasized
Outcomes and content design takeaways:
- New features needed more introduction and guidance - a vague, oblique entrypoint with low affordances wasn’t suitable to introduce a new feature.
- Friendly, approchable persona was appropriate and users welcomed it. They liked the use of emojis and the friendly, conversational language, which helped reinforce that this was a feature meant to help them take the load off comparing tours and narrowing down their choices.
This feature was deprecated shortly after for further iterations, so I didn’t follow up on the feature after. Content design lessons were applied to Iteration 2: “Travel buddy”, which I worked on subsequently.
Iteration 2: “Travel buddy”Apr-May 2025
What is it? In this iteration of the AI feautre, I worked with product and design on the entrypointrs to the MVP of an AI travel assistant feature, to provide recommendations based on users’ booked trips.
Applying content design lessons from earlier AI features:
1. Entrypoint needs clearer affordances, taking into consideration where users might encounter it. For instance, on a page showing users’ trips, I worked with product and design to add a pop-up to the entrypoint, explaining what the AI could do for users.
2. Keeping affordances high to guide users through their early interactions with the feature. Drawing on lessons from the AI comparison project, I focused on building a conversational, friendly and reassuring persona, e.g. in its introductory preamble and in its thinking process.
3. Designing an effective conversational counterpart: Apart from using “my” and “your” to lend a conversational tone, my content decisions were driven by building the “travel buddy” as a helpful counterpart that can carry a conversation. This was a key difference from the earlier AI comparison feature, which didn’t have a conversational element (users couldn’t type and participate in the conversation).
4. Pushing back against feature names that didn’t align with the style. Several members of senior management wanted to either call the feature a generic, lakclustre “AI assistant”, or something too edgy like “Travel homie”. I worked together with the product manager to lay out why “Travel buddy” would be the best choice, based on recognisability in our markets (”homie” leaned more American, for instance), tone and voice, style, and scalability. This avoided jury by seniority, and highlighted that content decisions were not made arbitrarily.
Outcomes and lessonsDesigning for AI is an iterative and ongoing process. Need for more affordances and guiding from content design, and actively doing content testing and usability testing to refine design (including content) decisions.