In summer 2019 I designed & prototyped 3 features with the goal of improving flight search experience on the Kayak desktop site.

During my internship at Kayak I worked on the Flights web app. Kayak is over a decade old & is a highly numbers & experimentation driven company. In summer 2019 I worked on designing 3 features, experimenting with different hypothesis to help users find the best flights for their travels.

Traveling leisurely & comfortably can mean different things for different users. For some it's finding an late evening flight on friday & early morning flight back on monday. Or for a family it may mean lesser layovers & services provided for childcare by the flights.

This lead to helping future travellers answer 2 questions:

To understand how users navigate flight search for different scenarios such as weekend trips, family trips, business trips, etc. I & fellow PM intern Luciana ran user studies.

From these user studies we found,

These insights combined with previous ones gathered by the team we set to work.

First question we helped answer,

To help users answer this question we developed two features;

For longer connected flights to slightly less popular airports it’s significantly cheaper to buy tickets with connecting airlines or have airport layover. What does this mean? let’s take a scenario

The user can save significant money by doing this but it means they have to take the extra effort to change airport with their luggage. This is where context comes to play. A lone traveller may find this as a reasonable offer but for a family with kids this maybe an impossible option.

Even though users had different mental models for searching flights for domestic & international travel one preference persisted. Airline preference, avoiding certain airlines. Either due to service or points with other airline partner.

Second question we helped answer,

Flights are a major chunk of expense during a trip. Getting the cheapest & best deals is a huge motivation and the reason why services such as Kayak exist. Flight prices are in a constant flux with variable demand, availability, etc contributing to the price changes.

To address this the flight price predictor was built.

On the flights desktop results page(top left) lives recommendation. It tells the users to “buy” or “wait” to buy tickets based on prices predicted till the departure date.

To add authenticity & give transparency to user why these predictions are being made. A visual indicator was added in the form of a price graph.

As travel plans are made rarely people are unaware of what the average price of flights to the destinations they are travelling to. The next version of the graph included colors & price ranges to help users identify if they are paying more or less than average prices. Giving them additional information to take a decision.

The aim of the feature was to drive users to get email alerts of notifications on their app when the price drops or is at the minimum.

I hosted a prototyping workshop while at Kayak where I talked about the aspect of creating more high fidelity prototypes by mixing designs with code & understanding how design systems live as code.

I helped with the micro-animations for a teammates project.