eCommerce Customer Acquisition Research
PROJECT OVERVIEW
This research project was launched to gain a better understanding of the target customer segments for the digital commerce space in support of our eShop new customer acquisition objectives for 2022.
ROLE Project Lead / UX Research
YEAR 2022
DURATION 2 months
TOOLS Userlytics, Excel, AlphaSights
Portfolio Brief
For portfolio purposes, I’m showcasing primarily how I go about my research projects and how I organize my research & data analytics
Goals & Objectives
The research study aims to validate assumptions and identify the correct target customers for e-commerce. It will evaluate pain points and opportunities in the customer journey, identify areas of friction, and suggest improvements to optimize the user experience. The goal is to help the company improve their e-commerce strategy and provide the best possible experience for their target customers.
Timeline
Week 5
Synthesize Findings
Week 6
Hold report-out
Week 1
Define scope & target participant profiles
Hold recruitment kick-off call
Week 2 & 3
Run recruitment & review profiles
Design research study
Week 4
Conduct user interviews & usability tests
Methodology
Using the purchase profiles in the back end of our platform, I identified 2 major segments and further divided them into 2 minor segments each, resulting in a total of 8 profiles. AlphaSights was used to source the participant profiles which were filtered through screener questions tailored to these profiles.
30 Minute Usability Test
Participants completed 4 website activities related to checkout, product exploration, and account registration. Usability tests used metrics including task success, SEQ, time on task, SUS, and a 5-point Likert scale.
30 Minute User Interview
I scripted questions beforehand to facilitate conversational exploration of the participant's experience with online purchasing for their organization.
Synthesize Findings
Quantitative Findings
Task Success / SEQ Ratings / Time on Task
Tasks were measured by time, success rate, and difficulty rating (SEQ). Raw data was compiled, organized, and calculated using Excel, including standard deviations and confidence intervals.
click to enlarge images
SUS / Likert Scale Shopping Experience
Usability test questions included SUS and a 5-point Likert scale on the shopping experience. Graphs were created using all data, including standard deviations and confidence intervals.
Task Difficulty
Task difficulty was assessed by the moderator to note how difficult challenges were by each user, even if they successfully completed a task through a non-straightforward approach.
Qualitative Findings
Qualitative observations were compiled in a document with observer names, coded by severity and type for each task and user interview.
I’m not including this as it contains the participants names but it is a 33-page document containing their comments, notes, and observations taken throughout testing.Observations
Observations were compiled into a rainbow chart Excel file tracking shared user experiences, organized by themes.
Quotes
Quotes were extracted and organized by themes, participants, and notes for context, providing concise user perspectives and references for validation.
Issue Severity Table
After conducting research and tests, the next step was to determine important data for moving forward.
An issue severity table was created in Excel, containing all "found issues" from qualitative and quantitative data. Each issue was numbered and identified by task and description, and scored by Criticality, Impact, and Frequency.
Task Criticality
Rated in terms of impact on the business or the user if the task is not accomplished
Impact Score
Rated in terms of how high the interference of the issue on the experience
Frequency Score
The sum of issue occurrences within participants (P1+P2+P3)/total
Severity Score
Task Criticality x Impact x Frequency
The severity can then be sorted from most severe to lowest to address the most severe issues first. The goal of this is to show stakeholders what our most prominent issues within the platform our and what should be addressed first going forward in order to improve the user experience.
Solutions Table
The solutions table proposes multiple solutions for each issue ID, aiming to address multiple issues simultaneously for efficiency. It is organized accordingly:
Solutions ID
Solution
Issue Solution Effectiveness (Strength of solution rated 1,2,3,5)
Impact Score (Sum of effectiveness strength x Sum of all issue severities - calculated from the previous table)
Complexity (Effort & Uncertainty Score, rated in sprint points)
ROI (Return on Investment, Complexity/Impact)
Next Steps (UX Project? Dev Bug? Customer Service Issue?)
JIRA Key (DEV key for reference)
Solutions are organized by ROI to determine which solution to implement first based on effectiveness and severity ratings. This guides next steps for the organization.
Wrap Up
After completing the research and data compilation, I will present my findings to stakeholders, allocate issues and proposed solutions to team members, and highlight key findings. I then work on related projects and validate the solutions once implemented.