V. Sri

I am a writer designer

Portfolio

Function

Design

Content

Experience

Perception
Comprehension
Task completion
Usability


Information architecture
Messaging strategy
Taxonomy
Voice
Microcopy
Localization
 

Interface
Interaction
Visual systems
Gestalt
Accessibility
Prototyping
 

Data Security
APIs
Infrastructure
Performance
Analytics

Contents

Machine Translation, Mindfully Explained

Yelp, 2014

Yelp creative

Yelp's in-house creative studio serving community managers, business marketing, and product

introducing machine translation

Machine translated reviews would let users read local reviews in their own language while traveling.

 

But there was an interesting caveat.

Interesting caveat

Machine translation is imperfect

reviews are hard to translate

Yelp reviews are full of slang, colloquialisms, misspellings, grammar errors, made up words, and other stylistic choices that make them hard to translate—let alone automatically.

  • Be introductory and informative

  • Be realistic while optimistic

  • Be brief

Heads up! We’re using machine translation to interpret this review. Please excuse us if the result is less than perfect.

“Heads up!”

Because it's not a warning.

“Interpret”

Legal advised against “translate.”

“Excuse us”

We shouldn’t apologize either.

Scroll down to see how I might approach this problem today

                    We’re using machine translation to interpret this review. Your result may be less than perfect.

{¡Hola!}

Could we find a friendly greeting for each language?

"Your result"

Lose "please" and "excuse us" and focus on the user.

How I might do this in 2022

{Howdy!}

{¡Hola!}

{नमस्कार}

here's what shipped

The final content and design featuring Hammy the hamster.

Launch

In August 2014, the international team launched machine translation to the Yelp mobile app.

Contents

Story Ads: A New Chapter in Search Advertising

Google, 2018

Ads quality UX

I was the UX writer for the Ads Quality UX team. We were responsible for the look and feel of ads on Google.com.

Ads quality UX

It was an incredibly fun job. And we took our mission seriously.

 

I worked with quantitative and qualitative UX researchers, interaction designers, UX strategists, UX engineers, data scientists, and product managers every day. 

2017

2018

2019

How might we introduce visual formats on search?

Story ads

Why don't search ads typically have images?

Advertisers struggled to meet our aesthetic standards.

Which images would you approve?

1

2

3

4

5

6

1

2

3

4

5

6

OUR STANDARD WASN'T CLEAR BECAUSE THERE WASN'T A CLEAR STANDARD

In search of a standard

I had the Ads Quality UX team rate sample ads by asking them two questions:

 

  • How would rate the ad in terms of quality?
  • How interested are you in the ad?

Title Text

Subtitle

I plotted the results on a 2x2

The dregs

The preems

spammy

Snoozy

How might we translate this to standards?

My initial approach

Let's think about the Audience

 

Digital marketers not creative directors

More technical and analytical

Less aesthetic and artistic

More like this

Granularity was the key

numbers and nuance

To keep the search results page (SRP) useful, the search query needed to be clearly represented in the image.

framework for advertisers

I also developed a framework for advertisers to craft copy that worked with our auction mechanics.

Where we started

Where we ended up

These specifications improved image quality by 86%

Launch

After more testing and a successful pilot, this product launched as “Gallery Ads” at Google Marketing Live in May 2019.

 

Un-launch

After about a year, Gallery Ads were retired in favor of Image Extensions.

Image standards live on

I was approached by another team at Google to repurpose these standards for Responsive Display Ads.

Contents

Coming into focus mode

Zendesk, 2020

Zendesk

At Zendesk I work on a globally distributed team of content designers who are each embedded in specific product areas or areas of focus.

 

My area of focus is the agent experience.

Moonlighting

A "timeboxed effort" indeed

Because this was a side hustle, I could only meet with the Dublin-based team once per week.

 

The entire thing took 12 weeks from soup to nuts. This is that process.

This took 12 weeks

Mutual exclusive channels → Focus mode

Who are we talking about?

What are live channels?

Agents struggle with live channels

What is mutual exclusivity?

A look under the hood

The user's point of view

Decisions, decisions

I wanted to make sure my product partners agreed with my approach. I presented two ways forward:

  • data-oriented language
  • user-oriented language

Key Learning

Check in with your product partners at every "fork in the road" before you move too far ahead.

what do we call this thing?

Three approaches

Setting name

Heading

Description

Naming the approaches helps partners

Deeper dive

Named approaches

In situ

How else will this language be used?

Including explorations of onboarding modals

Different contexts can help stress-test your language

the entire process was welL-documented

Final design

A sneak peek at the final setting for focus mode on the settings page.

Final design

A sneak peek at the final setting for focus mode on the settings page.

Anatomy of agent workspace

Zendesk, 2020

Agent workspace

I was on a team tasked with integrating two of our flagship products, Support and Chat into a single unified experience.

Sensemaking

Part of my approach is to take inventory of the UI. Because we were combining two separate products, we needed to understand the entire set of concepts.

Sensemaking

We abstract away the UI to get a sense of all the major parts of the UI facing the user.

Adding detail

I broke apart the UI in this medium-fidelity mockup to show how different parts of the screen served different content needs. I wrote descriptions of each part and divided the UI into zones that reflect different levels of intent from the user's point of view.

hey@lookandpoint.com

Portfolio

By V Sri

Portfolio

A walkthrough of three content design projects from Yelp, Google, and Zendesk.

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