UXDI - Research case study
With an evolving food delivery landscape, users are more inclined towards platforms that allow them to compare and and select from a plethora of options. How might we develop a best in market, all encompassing food delivery service app?
Background
My client wanted to develop a platform that aspired to become the "Kayak/Skyscanner for online food ordering". The ultimate all in one search platform where users can seamlessly search across different food delivery services to compare prices, delivery times, etc, to find the best deals. With an aim to aggregate multiple food delivery services such as Deliveroo, Uber Eats & Just eat.
Role
User Researcher, responsible for all aspects of the research process ie planning, execution & analysis.
Research goals
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What are the main reasons as to why customers use online delivery services?
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How frequently do customers use food delivery services?
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What motivates their decisions to choose one provider over another?
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Can we identify patterns in the type of food choices that are commonly ordered from new and existing customers?
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What frustrations have customers faced in the past when ordering food, via a delivery app?
In any discovery project, having well defined research questions helps you understand what you want to accomplish with your research. The justification for my question are as followed.
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In order for us to build a strong customer profile, we must understand their motivations for using an online food delivery service. This will aid our knowledge of their goals and context of use.
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Frequency of use will strengthen our understanding of typical customer behaviours around ordering food online vs at home cooking.
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Understanding the driving force behind choices of competitors over another will help us succeed in developing a product inline with customer expectation, such as delivery time, deals, pricing, variety of food ect.
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Maybe a little too futuristic, but with ongoing observation, we may be able to provide tailored experiences for customers by providing recommendations on what food choices they may like to try in the future, based on previous food orders.
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Identifying pain points from previous experiences will help us identify common areas of frustration within a customer journey. Allowing us to take this into consideration when developing a new product.
Methodology
Based on the variety of research methods available, I took time to establish the best ways to uncover the most valuable insight across the research landscape. After careful consideration I explored two research methods from an attitudinal and behavioural lens.
Attitudinal approach
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User interview - To listen to users thoughts, feelings and opinions
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3x (45-60) sessions
Behavioural approach
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Usability test - To observe users and draw data from these behaviours
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3x (45-60) sessions
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Research artefacts
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Consent forms created and sent to participants
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Discussion guide drafted and used to aid topics of conversation
Analysis
Typically broken down into stages to reduce the risk of cognitive overload.​
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Review of video recordings and transcripts
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Notes extraction and codes generated
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Affinity mapping - using collaboration software (Miro)
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​Persona development - profiles were created to represent the behaviours, challenges and needs of participants who represent prospect customers. *Empathy maps could be used as an alternate choice*
Documentation
After completing the analysis, I spent time crafting a playback deck to highlight what had been learnt. This document is available upon request and covered the following areas.
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Objectives and research questions
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Chosen methodology
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Personas
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Findings & elaborations
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Recommendations
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Learnings
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Next steps