How to make sense of Inherited Design
Tags: Design Thinking, User Persona, Ts, UX, Service Design

However, there’s a problem with that conclusion. It suffers from survivorship bias.

Only a live design gets bugs! Unless we’ve evidence that the design is utterly failing its purpose the design works. Overmore, if we’ve successfully added new features to the design for years — the design is extensible and robust.

It’d be crazy to throw away a system this good without studying it. Not studying it would add unknown risks for the user experience and the business.

The first step was to study the existing design and find the good (helps the user), bad (user doesn’t care), and ugly (deters the user). While going through the process of studying & redesigning the existing products at Headout, I took notes and here’s what I learned.

Let’s begin this process!

Design audits are a powerful tool to study existing products and how customers interact with it.

However, halfway through writing the audit goals, I realised my mistake. I was missing critical steps. I didn’t know who the customer was. Who were they, and why were they using our product?

I knew nothing.

So I turned to another design tool — the one that helps us study, understand, and model our customers (with their nuances and market realities) — User Personas.

User Personas without big teams or budgets

We didn’t have months, and a large team to conduct detailed research. Existing UX methodologies are compelling, but they fail in agile and startup environments — where clarity is iterative & asynchronous.

With the years of data to study, we took an iterative approach to draw our (provisional) personas:

The existing design Recorded user sessions for several critical flows Labelled & structured customer support communication (chats, emails, call recordings) Data for marketing funnels and their learnings in the paid & organic channels Existing knowledge of people who’ve been running operations, customer support, and the marketing department Relevant research published by airline, hospitality, credit card, and other companies

Interview with stakeholders gives us models (that different teams use to understand business or the customer) and a starting point.

Data from sessions recordings, customer support tickets, recorded calls, NPS rating, App Store/Play Store ratings — helped us verify the initial models and add more details. This process gave us a list of 20–25 attributes that affected the customers, and therefore, our business.

Finally speaking to 10+ potential users (people who took experiences abroad in the last 6 months, regardless of Headout) helped us reduce the 20–25 attributes to just 7:

The motive matrix- Social, Knowledge, Location/Physical, and Leisure. Different flavours of the motive take the front-seat as the user’s journey evolves Time at hand / Schedule: flexibility/rigidity in schedule Cost sensitivity Specificity / Preferences: Language, Cuisine, and other preferences Comfort level: Distance from home city/town & prior experience Who’s booking: Is the customer booking themselves? Do they make the decision? Who’s accompanying: Who all are coming along for the experience with the customer?

These are all the factors that can affect a customer’s decision. These are not “independent variables” (Eg: Cost sensitivity & specificity are heavily co-related); these attributes describe all possible information that a customer would consider while deciding to buy from headout.

Speaking to the customers also revealed our key-attribute — one attributes that disproportionately affects all other attributes — “Who’s accompanying”. All other factors (price sensitivity, motive, etc.) change depending on who is accompanying the customer.

Using this insight, we draw our user categories (not personas):

Lone Drifter: heading out alone Partners: heading out with the special someone Groups: friends, family, coworkers, Family with Kids: kids change everything

There are several personas in each user categories, but not all prefer us. From here, specific stories of the customers help fill in details, affinities, and help us narrow down to our provisional personas: