A N N A B L E A K L E Y / R E S E A R C H P O RT F O L I O

RESEARCH PORTFOLIOAnna Bleakley

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A N N A B L E A K L E Y / R E S E A R C H P O RT F O L I O

Due to non-disclosure agreements and user data regulations I cannot fully disclose the results of the research projects. This portfolio is only meant to provide an overview of my research process with a snippet of previous research reports.

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A N N A B L E A K L E Y / R E S E A R C H P O RT F O L I O

SHORT INTR0

Hi! I’m Anna • Previously an Experiment Manger at adidas

• With 3 years experiment in UXR

• Pursuing a PhD in HCI at UCD

• Talk to me about filters & forms

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SKILL SET

A N N A B L E A K L E Y / R E S E A R C H P O RT F O L I O

C R E D I T: E L I Z A B E T H B A C O N S U N D I A L M O D E L

Usability Engineering

Service Design

Human Factors

Content Management

Interaction Desgin

Branding

Visual Design

Design Research

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TABLE OF CONTENTS

WHAT IS USER RESEARCH? PART 1

SOLARBOOST

NEWSLETTER SIGN-UP

PART 2.1

PART 2.2

PART 2.3

COMMERCIAL MOMENTS

CURRENT PROJECTSPART 3

PROJECTS

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WHAT IS USER RESEARCH?

PART 1

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EXPLORATORY RESEARCH

EVALUATIVE RESEARCH

OPTIMIZATION

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EXPLORATORY RESEARCH

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• Semi-structured interviews and focus groups • Identify pain-points • Understand motivation, needs, frustrations

High level, tries to understand the problem :

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OPTIMIZATION

• A data-driven approach • Iterative • A/B Testing • Pre/Post Analysis • Implementing quick wins

Effectively directing traffic through a funnel through:

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EVALUATIVE RESEARCH

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• Usability Testing (content, design solutions) • Iterative • Online

Touchpoint oriented research, solution oriented :

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MY WORKFLOW

EXPLORE EXPLAIN

OPTIMIZE

• Estimating opportunity costs with analytics • Findings quick wins and best practices • Hypothesis/Design driven testing • Understanding user pain points, needs,

frustrations through exploratory research creating a design direction

• Customer journey experiences • Usability testing • Pinpointing touch points, features, and

further understanding

• Small tweaks , design/personalization optimisations. Looking at refining small elements in the funnel

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DATA ANALYSIS HELPS US ANSWER WHAT AND WHEN USERS DO THE THINGS THAT THEY DO

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HOWEVER, THAT DATA DOESN’T ANSWER THE QUESTIONS OF WHY THEY DO IT

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USER RESEARCH HELPS US ANSWER THOSE WHY QUESTIONS

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SOLARBOOSTPART 2.1

Evaluative

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RESEARCH SETUP

MAIN RESEARCH QUESTIONS

I. Do users understand what Solarboost is? II. To what extent do users understand Solar is a franchise/group of products?

With the recent campaign launch of Solarboost Adidas has created content relating to the shoe as well as shoes in the franchise. The study aims to evaluate what users’ perception of the shoe based on content in the campaign landing page.

MOTIVATION

SETUP

- 16 participants from the UK and US - 4 persona types relating to running (serious runners, beginner runners, active women, etc.)

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RESULTS

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Consumers understand from product features and visuals that the shoe is for professionals, but still do not understanding what type of running SolarBoost is for. Consumers have varying understanding of the Solar franchise and which models are included in the franchise.

NEXT STEPS

Additional content relating to: (1) what type of running Solarboost is for; (2) how various features of the shoe are linked to the marketing campaign are needed. In future launch of products belonging to franchises, results of this research should be consulted to ensure that content is briefed in a manner that informs consumers on franchises within Adidas.

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COMMERCIAL MOMENTS

PART 2.2

Exploratory Research | Evaluative Research

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76 INTERVIEWS 2000+ RESPONSES

INITIAL INTERVIEWS

BLACK FRIDAY STUDY HOLIDAY STUDY

INITIAL INTERVIEWSGetting to know our participants, outlining the requirements of the diary study, understanding the intended purchases, budget, and shopper type, needs.

SURVEYVerifying insights found in our diary study. Questions in the survey are often market research question e.g. which products consumers consider as holiday gifts.

DIARY STUDYTasks and daily entries used to understand emotions, thoughts, and habits of participants. Follow ups are used to inquire into further details. Entries in the diary feed into the surveys.

PRE-BLACK FRIDAY SURVEY

BLACK FRIDAY UNMODERATED

TESTS

POST-BLACK FRIDAY SURVEY

CLOSING INTERVIEWS

INITIAL INTERVIEWS

PRE-HOLIDAY SURVEY

HOLIDAY UNMODERATED TESTS

CLOSING INTERVIEWS

CLOSING INTERVIEWSSummarizing results - here participants are asked additional follow-up questions based on entries in the diary and for tasks.

RESEARCH SETUP 1

UNMODERATED TESTINGTo uncover what works/doesn’t work in the current commercial moments’ experiences and to compare adidas experience with other brands/sites.

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RESEARCH SETUP 2

This study is meant to inform the Black Friday and Holiday season strategy for EU and American markets (participants therefore were recruited from UK and US). The study aims to identify key dimensions of the experience of gift giving and Black Friday that will be used in a future evaluation of user experiences during these sales periods.

MOTIVATION

SETUP

!12 diary study participants - 250 survey participants (for each survey) - 30 participants for unmoderated test (for each test)

The project was divided into two phases: (1) Black Friday Study; (2) Holiday Study

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OVERVIEW OF RESULTS

A N N A B L E A K L E Y / R E S E A R C H P O RT F O L I O

The study highlights the importance of delivery times, visible discounts on the PLP, and the importance of the planning phase in consumers’ purchasing behaviour. Results from the diary studies show that users purchase all throughout the week of Black Friday rather than on Black Friday itself.

NEXT STEPS

Results will be used to inform a strategy for Black Friday and the Holiday season. Another benchmarking study will be performed to evaluate new Adidas content for the following year looking particularly at: delivery, holiday themed website content, and discounts to compare these against competitors.

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NEWSLETTER SIGN-UPPART 2.3

Evaluative

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RESEARCH SETUP

ASSUMPTIONS

Users are more likely to provide their personal contact information once they have committed to a previous task (preferences + legal terms and conditions).

Due to long development times this test could not be inserted into the A/B testing roadmap. We have instead tried launch a quick usability test (speak aloud study) using SUS to measure how easily users filled in the form. Results will inform an iteration of the design for another round of testing.

MOTIVATION

SETUP

2 newsletter forms with:

- different UX copy (different tone of voice) - component order

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LATEST NEWS 15% DISCOUNT

INTRO TEXT [CASUAL] INTRO TEXT [SEMI-FORMAL]

AGE CONFIRMATION

AGE CONFIRMATION

MARKETING CONSENT

MARKETING CONSENT

EMAIL

PREFERENCES

GENDER

GENDER

PREFERENCES

CTA [CASUAL] CTA [SEMI-FORMAL]

TEST 1- CONVERSATIONAL TEST 2 - PERSONALIZATION

EMAIL

2ND STEP

OUTLINE OF FORM SETUP FOR NEWSLETTER SIGNUP

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RESULTS

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Overall users had a preference of Test 2 based on the quantitative score in the SUS test. Users appreciated the ability to select preferences and mentioned they were more inclined to provide their email address after selecting their preferences.

NEXT STEPS

A redesign of the newsletter signup flow will be created with the component order in Test 2. Based on qualitative data from the speak out loud study we will revise the tone of voice in both tests and add this to the A/B testing roadmap.

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CURRENT PROJECTSPART 3

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PhD Topic: Designing to support common ground building in multiparty VR dialogues Funded by SFI Ireland

CURRENT PROJECTS

Publications (to appear in ACM Digital Library):

Exploring Mental Workload and Lexical Diversity in Non-Native Speaker Interaction with Intelligent Personal Assistants - CUI2020

Finally a Case for Collaborative VR?: The Need to Design for Remote Multi-Party Conversations - CUI2020

See what I'm saying? Comparing Intelligent Personal Assistant use for native and non-native language speakers - MobileHCI2020

Research Areas:

Visual & Joint Attention | Common Ground Building | Visual Feedback | Turn-taking | Design Heuristics for VEs | Natural Language Processing |Intelligent Voice Assistants (VUIs) | Multimodal Interaction