STOOPR CHATBOT
Creating a Chatbot Experience to help Stoop Furniture in NYC
Stooping is a longtime New York tradition: someone casts away their no longer needed furniture (and other things) on the sidewalk in front of their home and anyone who needs them can salvage the items for whatever use they desire.
In this project, my team and I worked on a chatbot called Stoopr that helps people with finding or posting about furniture and other items in and around New York City through stooping.
Conversational UX Design | Flow Chart | Voiceflow Prototype
Team
Shadiya Fairoose, Jessica Drozd, Mishi Sarda
Duration
April 2022 to May 2022
Tools
Lucidchart, Voiceflow, Figma, Miro
Problem Statement
Sustainability is the name of the game in every industry right now. It has become crucial for diverse companies to integrate sustainable and eco-friendly practices into their day-to-day workflows to reduce their carbon footprint. However, corporate initiatives might not be enough to make a significant impact.
Communities must adapt to the growing need for positive sustainability while not drastically affecting the livelihoods of the common man. Reusability is one such tenet that could prove helpful in meeting the goals of a sustainable future.
THE SOLUTION
My team and I worked on a concept that helps enhance the reusability experience while adhering to a societal methodology familiar to the current world and economy - through a media platform and crowd-sourced information. Introducing Stoopr, a chatbot that helps you stoop for furniture and items in and around NYC.
Research
To learn more about the users and the market, our team used 4 different UX research methods that include:
User Surveys
User Interviews
Market Research
Competitive Analysis
USER SURVEYS
For our user surveys, we utilized Instagram, and the Pratt Institute's Listserve to reach out to people that could help us understand more about how they view stooping. In total, 29 people performed in our survey.
Our survey consisted of questions such as, “Do you trust that the information people post about furniture/ appliances/ decor is true? i.e. its condition". My team and I wanted to get a thorough understanding of what current products people were using currently to find furniture/ appliances and how often they engaged in that type of behavior.
Insights from the survey results showed:
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72% of survey takers use a product for finding/ posting about furniture/ appliances/ decor
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83% of people like finding free furniture
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Most people had a positive experience while stooping
USER INTERVIEWS
For our user interviews, we began by coming up with goals that we wanted to achieve through conducting our interviews. These goals included understanding user motivations, uncovering users' pain points when finding furniture/ appliances, and how they felt about privacy concerns when it came to stooping. For the study, we recruited 3 friends and family who had experience with stooping.
Insights from the interviews showed:
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Stooping is the easiest method of acquiring furniture for people who are on student visas studying in the U.S.
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Data from user interviews also helped support the notion that people would use a chatbot to find furniture/ appliances.
MARKET RESEARCH
For our third research method, we conducted market research. We took advice from a senior research manager at a global market research company for the same.
Insight from the market research showed:
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Able-bodied individuals who can lift and move heavy objects can help transport furniture residing within New York City limits.
Strengths
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This is a crowdsourced information-based app, which reduces data over head costs.
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It’s 24/7 available, handles more customers and there is no other chatbot specifically designed for this purpose.
Opportunities
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Stooping has become more widespread since the pandemic.
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An activity you can do outdoors and one that ultimately enriches your home.
Weaknesses
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The lack of human touch may frustrate the users and cause them to abandon the platform.
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Data may not be up to date at all times and could cause the app to be deemed as unreliable.
Threats
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Regulating the posts on the app, making sure its all family-friendly content
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Susceptible to data security breaches
COMPETITIVE ANALYSIS
For our last research method, we conducted a competitive analysis using the responses from our user survey. The top three most used products to look for furniture were Facebook Marketplace, Instagram- specifically, the Instagram handle “@stoopingnyc”, and Craigslist.
Insights from the competitive analysis showed:
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We found what other products out there lack for finding second-hand furniture.
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None of the competitors had customized listings.
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Two of the competitors do not have anonymous user identities.
Personality Design
Conversational interfaces exist for better interactions between humans and computers. Personality building makes the chatbot more relevant to the users.
🏆 INTERACTION GOALS
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Fun - finding free furniture should be a fun activity
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Frictionless - so the user can focus on getting their task completed
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Low Cognitive Load - the bot gathers information to present it in a simple way
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Efficient - users should be able to get information quickly
🤖 LEVEL OF PERSONIFICATION
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Medium level of personification
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Interaction is transactional- you look for furniture, post furniture, or update post
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Efficient, transparent, and consistent
⚡️ POWER DYNAMICS
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The user holds the majority of the power in this dynamic. Chatbot serves as an assistant.
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This relationship should not be intimate at all.
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Over time the relationship will develop with the bot saving users' posts.
💬 TONE
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Casual - helps users be more comfortable using this platform and trust the process.
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Intermediate - facilitates the interaction.
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Cool - attempts to be sassy and fun.
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Excited - helps the user become more excited about stooping.
💁♀️ CHARACTER TRAITS
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Straightforward
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Amiable
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Obliging
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Energetic
Sample Script
Sample scripting is the designer’s first step before flows. It is essentially wireframing with words. Writing sample scripts helps us flesh out what should go into the flows. It is best to explore with many sample scripts which is why we had created 3 different sample scripts for three different scenarios.
Scenarios were:
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A person wants to post information about some furniture lying in their neighborhood for two days.
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A person who wants to get free furniture got to know about this stooping bot and is interacting with it for the first time.
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A person wants to update information about the item they posted about and wants to remove that listing.
Training Data and Flow Chart
We designed Intents, Utterances, and Slot values to create a flow chart providing all the details on the conversation between the bot and the user along with future intents.
Here's a snippet of our Flow Chart:
Prototype 1: Low Fidelity Virtual Script
We used templates available in Miro to set up the scripts. Each scenario was on its separate frame to keep the scenarios understandable and clear for post-it notes.
Methodology:
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A stooping survey was created to recruit participants for both user interviews and testing the low-fidelity prototype which was in this case a script reading.
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The participants were given all three scenario scripts on a miro board with both red and green post-it notes to help highlight any positive or negative feedback.
WHAT WE LEARNED
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Certain areas of the script were not clear in terms of terminology. So when users were reading through certain parts, they were unsure what the bot was saying.
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Sometimes the feedback can be subjective and might not align with the scope of the project.
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There is always room for improvement. Conversational design is always an iterative process and should be built upon cycles of feedback.
Prototype 2: High Fidelity Wizard of Oz
We conducted a high-fidelity Wizard of Oz prototype for prototype 2 with the help of the script scenarios that we created at the beginning of our project. We used standard iMessage on our phones to test prototype 2 on our phones.
Methodology:
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We conducted our testing asynchronously. Our participants were recruited through word of mouth by the team members.
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The test was conducted with the help of IMessages where the team members acted as the “Bot” and were conversing with the participants. All three scenarios were explored in the process to test the usability of the bot and get users’ feedback to improve the scripts.
WHAT WE LEARNED
The participants found the bot straightforward to understand. They appreciated the fact they were given options to choose from and that made the conversation more intuitive and less complicated. The majority of the participants loved the idea of gifs at the end of the conversation which gave it a personal touch. Participants highlighted the bot's personality to be friendly, fun, chatty, vocal, extroverted, helpful, bubbly, and considerate. All participants agreed they would be open to using the chatbot if they are on the lookout for some items.
Final Thoughts
The Stoopr bot is a concept that can be fleshed out into a proper digital product such as an app or a website. Given the opportunity, we would like to develop a simple app that encapsulates the functionalities defined for the chatbot, where the chatbot will act more as a support entity 24/7. This would require a more technical approach, such as defining the systems designs and MVP. Once a prototype is in place, we would also love to conduct some more evaluative research and A/B testing and see how if the app meets the usage as well as sustainability goals we defined at the start of this project. We would want to add more features like expanding the search radius where the items can be listed.
As mentioned before, creating sustainable and ecological functionality through the digital space is our primary aim, and want the app to be built around this ideology. This could include featuring articles on sustainability and how stooping reduces your carbon footprint and maybe having popular environmental ambassadors promote the app.