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Espresso Vision



PROJECT SPECS
2019, 18 weeks, Mobile Application


MY ROLE
Product Design Lead, Front-end Developer,
UX/UI Design


PROGRAMS
Adobe XD, Sketch, AI CC, ID CC


TAGS
Research & Design, User Testing,
CSS Coding, Computer Vision








PROGRAM
The Boston University Spark! Fellowship Program is anintiative that provides design and tech support for student driven projects. One of it’s sub-groups, the Spark! UXD allows students of design background to be part of another student’s innovative idea.

I joined Espresso Vision, a technical group of two, who was inspired to provide coffee enthusiants a way to collect data from their daily coffees with an app.




PROCESS
CONTEXT / PROBLEM
My team, deemed Espresso Vision by our innovative lead, had the purpose of finding a digital and assessible fix to hand lever coffee machines

The objective is to create a universal application to all hand lever devices, but because our project timeline only spans 4 months, it was narrowed down to one specific machine: the Flair Hand Lever Espresso Machine.

It is lightweight, portable, and inexpensive compared to some products by LaPavoni, Ponte Vecchio, or Astoria, which retail at around 800+ US dollars.


The problem statement we arrived to, and unanimously agreed on was:

“Espresso making is a difficult process for a home hand lever espresso maker, and applied pressure is one of the most important factors in that process.”







VALUE PROPOSITION
The Espresso Vision project helps espresso enthusiasts who want to improve the quality and consistency of their espresso by providing a low cost method to track pressure.



PRODUCT INFO / SOLUTION

Espresso Vision targets espresso enthusiasts that would like that perfect cup of espresso using a Flair hand lever espresso machine. While the machine cost around ~$200-400 in price for refurbished or new, many of the add-ons for taking the pull’s data is much more expensive. The Espresso Vision team sets out to create an app that reads the Flair’s pressure gauge, and formulate your pull datas in a one place.





CUSTOMER PROFILE / MVP





PROBLEM INTERVIEWS



Each problem interview lasted around 45 minutes with inquires including the person’s background / demographics, duration as a coffee drinker, their ranked importance in the coffee making process, and purpose.

how often?
» 100% drink coffee twice in a day

how long?
» 40% started drinking as teenagers; 40% started drinking as children; 20% started in adult life

who do you make coffee for?
» 40% only make for themselves; 40% makes for themselves + family / friends; 20% makes for themselves + customershow to you drink coffee when travelling?
» 3/5 brings an aeropress with hand grinder / pre grinds; 2/5 use word of mouth to find best coffee shops; 2/5 brings their V60 coffee maker kit

what is your most important pain points (by rank)?
» person 1: grind size, temperature control, flow
» person 2: water quality, coffee quality, grind
» person 3: freshness of beans, grind size, dose
» person 4: temperature, grind size
» person 5: coffee quality, water quality, grind

what’s your purpose for making coffee?
» 5/5 say it is for experimentation; 2/5 for nostalgia; 3/5 for taste; 1/5 for ritual; 1/5 for rewarding feeling

GOALS
» allow users to record video » an integral component of the process in providing more data for the user to improve their espresso quality or discover a new tasteful combination

» to send video to remote server for processing (generation of pressure data) » remote server running R allows faster development of algorithm

» to retrieve pressure data from remote server » have data sent back to app for viewing is faster, more manageable, and simplier for users to access; quicker than email, web login, or other platforms

» to store acquired data along with extra information provided by user » allowing users to provide additional information within app to contribute to more meaningful analyses

» display “shot data” in a clear manner » a simple organized composition of the data will allow users to review their shot history and determine trends, progress, etc.

» create an intuitive and accessible interface » neccessary for a complicated process; prove beneficial to users





COMPETITOR REVIEW / RESEARCH
   


Decent Espresso and/or Rocket V60


Their problem claim:
Controls pressure / temperature of the water with a touch of a button, achieve precision in coffee making, and simulate professional machines


Their product/solution:
Product profiles the key components of espresso making using sensors to display and control values via tablet


Their audience:
Coffee enthusiasts who want to achieve professional coffee machine results; $2500 - $4500 price

Their value proposition:
Containts features for controlling the coffee making process, ones that are not seen in other machines; as well attributes that are only available in professional machines

Their focus:
Mostly for household use with opportunity in learning about espresso; also toward scientifically inclined users—since their product is a tool for experimentation and testing theories about espresso

Their strengths:
Excellent machine ergonomics; charming interface for profiling; control over extraction profile (highly accurate and reproducible); user can specify temperature, pressure, and flow rate throughout the extraction; real time extraction data

Their weaknesses:
Price deterence or difficulty with self servicing (though not a huge issue as their cutsomer support is very well rated)




» Their problem claim: Grants all compatible espresso machies the ability to read pressure / flow (note: only seen in advanced, stat of art devices)

» Their product/solution: An easy to use tool to record and improve espresso extractions by enabling repeatable pressure and flow profiling

» Their audience: Coffee enthusiasts who use either a vintage lever machine or a modern pump machine; they don't specify beyond that requirement; $400 device

» Their value proposition: It can be attached to regular hand lever coffee machines without the need to purchase a more high-end one. You can also collect data using your smartphone

» Their focus: Profile pressure and water flow in order to achieve repetability in the quality of espresso made

» Their strengths: The ease of set up and plug and play nature of the device

» Their weaknesses: Battery life lifecycle of device might not last that long with hot water in contact with the pressure transducer or near the battery



Custom Pressure Transducer

» Their problem claim: Data logging of continuous pressure

» Their product/solution: Direct conversion of pressure applied from piston to electrical values for data logging by a microcomputer or other processsing device to generate continutuously applied pressure values

» Their audience: Extremely technically confident individual with electronics understanding, and interest / ability to construct a pressure transducer by themselves

» Their value proposition: Continuous stream of data of pressure applied - core job

» Their focus: Troubleshooting or recreating espresso shots as well as repeatability and dialing in

» Their strengths: Continuous measurements, and depth of data (sensitivity of 1.0014 bar vs 1bar); enhanced ability to troubleshoot shots and record data

» Their weaknesses: Techincal requirements to build a custom solution; loose wires running off of the machine; not plug and play or easy to set up





Manual Jounaling of Pressure

» Their problem claim: Discrete logging of pressure points

» Their product/solution: Manual tracking of applied pressure by the user while pulling a shot

» Their audience: Any espresso maker with sufficient understanding and knowledge of espresso principles; desire to track pressure as a variable (likely a hand lever user)

» Their value proposition: Pressure data points collected to hopefully troubleshoot or control variables (rougher than continuous)

» Their focus: Troubleshooting or recreating espresso shots as well as repeatability and dialing in

» Their strengths: Simplicity (current standard method when thinking about pressure in troubleshooting shots); free

» Their weaknesses: no a substantial view of the actual pressure being applied; leave out many other points in between each timestep




ASSUMPTIONS / VALIDATIONS






STYLE GUIDE / LOGO
Style Guide

The primary colors are chosen from espresso funneling through the filter. The yellow represented by such, and the brown and green for the unfrosted and roasted coffee beans. The secondary colors are founded from a set of espresso mugs and chosen to inspire the first palette with a fun and lighthearted collection.

The typefaces are: Pacifico and Kohinoor Devanagari; and are selected as attention grabbing for the former, and a more legible typeface for the latter.



Logo

The logo of Espresso Vision is comprise of the letter E in espresso and the coffee bean. Originally set as just a logotype “Espresso Vision” in Pacifico, the team came together and voice that it’d be something simple, yet particular to our brand. In the end, this design was chosen as the winning logo fitted to be our symbol.




KEY DELIVERIES

The main push for this project is to launch a phone application on IOS and Andriod during Spark! demo day, however, due to the mass amount of technical work in the back end, and a limited timeframe of 12 weeks of sprints, our team decided to create as much of the main functions as we can.


INNOVATION JOURNEY
Pre-sprint conference / Mentor Meet Up:

Design / technical mentors from various companies ( like Hubspot, Red Hat, Wayfair, and many others) come and help the student innovative teams develop their idea into an feasible entity.
 




The main component of this app was in utilizing computer vision. The app used the idea of computer vision to digitally read and record the angle of the pressure needle using geometry, speed, and frame of each image. As the shot is being pulled—aka as the lever is being pressed down—the camera would follow the needle and create a graph similar to a bell curve.

Another part of the project was know where the data was going to be stored.

The first solution: Have it placed within everyone’s phones internally, however…

(1) if enthusiats were to keep the data there, their phones would run out of storage quite quickly,

(2) if enthusiats were to delete the data everytime they made a shot, it would be to much of a hassle for them to keep using the app

…so, our final solution was to store the data in the cloud, and building the connection with React and AWS.





On the UI side, the objective is to have a design that most fits the Espresso Elysse profile. The user would have the option to sign in through Google, Facebook, or on the app itself. The onboarding process would be two videos demonstrating (1) how to use the app itself / its features, and (2) how to use the app in relation to your Flair hand lever espresso machine.

At the bottom of the app, there is a navigation bar that presents 5 connecting actions: home, settings, record, history, and favorites. Earlier versions of Espresso Vision did not contain a home button since the team were more focused on the workings of how users will access the history and data they want to keep, but as the project progressed, it was deemed a homepage was neccessary for an overview calendar, to collect notifications, and to retain tutorials in case users need a review on the features.

The idea of placing an infinity scroll on the history and favorites page, was that so the user can view more of their pull data than the overview calendar on the homepage; both the history and favorites would have filtered as most recent on top and less recent as the user scrolls up.




When a user desires to make a recording of their pull, the pre shot page offers them spaces to add data that can help with their experimentation, and calculation of averages on the history page. The actual recording would be taken with the stopwatch and button rotated counterclockwise to assist with positioning to the Flair. Afterwords, a post shot page serves as an additional chance to insert more information.

A major characteristic of the recording is that the rendering is NOT a live analysis of a presenting pull. The video would be taken simoutaneously as the pull, but it would take up to two minutes afterwords for it to process the data and create a graph for the history page. Our intial intention was to have the feature preform in similiarity to the Snapchat recordings, but factoring in the time restraints and limited team meetings, our mentors suggested we operate the best we can on each component of the app instead of focusing on one idea.

As demo day came and went—though we were not able to launch it digitally to the app stores—there were some proposals by the event’s attendees on features in which could improve the app:

» search bar on home
» filtering on history and favorites
» a larger space for the account settings
» a way to download, export, and share .


Interview
Insights
» Interviewed 5 coffee enthusiasts (1-45 year range of experience)
» Earlvangelists’ understanding of espresso principles deeply
» Interesting differences in making and tracking approaches and processes
» Pains - manydifferent variables, early learning proces is continuous trial and error, and frustrating for many
User Testing

We tested on 5-6 participants for 30-60 minutes, and decided that instead of surveying as much people as we can, we would be using the shotgun approach; a method that specifically targets users that are deemed closest to MVP profile. In addition to the coffee enthusiats interviewed, we were lucky to have the opportunity to have one of the product leads at Flair provide us some analyses.





WIREFRAMES / MOCK UPS
In rough drafts, the wireframes are sketched out to fulfill the MVP in our statement. Each iteration is provided by the feedback of espresso enthusiasts, and coffee barista.








SAMPLES / PROTOTYPE






*Currently seeking
design positions
& opportunities


Skyler Tse © 2021
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