Seamless / by Isabelle Ringnes

For project 2 we were tasked to come up with a new product feature for an existing company. I was tasked with the Seamless Challenge. After multiple hours of brainstorming I finally landed on the new product feature "Food Surf". You can view the presentation on the bottom, but the following documentation is how I envisioned the product would evolve from idea to launch. 

Product Requirement Document


Project Food Surf is a new meal discovery feature integrated into the Seamless mobile application. The core feature is swipeable images of food ready to be delivered. Food Surf will allow users to swipe through pictures of various dishes posted by restaurants on Seamless.

Project Food Surf is launched to increase users restaurant delivery choices.Through visual cues, the users will feel encouraged to order food from undiscovered restaurants.

The feature will be a valuable addition to the Seamless user-experience as well as drive more in app-engagement. The overall goal of the product is to drive profit with increased frequency of purchases, customer acquisition and new restaurant partnerships.

“From desire to deliver in just one click!”


P0: Must have P1: Should Have P2: Could Have

P0: As a time-pressured and lazy millennial I want to flip through visuals of what I am ordering because I don’t bother to read through all the food-descriptions.

P0: As a college-student who loves food I want a fun way to discover new food options because I often feel bored and like to browse seamless during class.

P0: As a fitness-blogger I want filters so I have control of exactly what I am ordering because I don’t want to order anything unhealthy.

P0: As an adventurous eater who loves to try new things I want to discover new restaurant dishes and easily add them to a favorite list so I can revisit them the next time and keep track of what I have tried.  

P0: As an indecisive foodie I want a one-click order now option to make the decision making process easier - if not it takes me forever to choose.

P1: As a hungover college-student I want to flip through high quality and delicious pictures of food because I feel sick and need to stimulate my appetite with visuals.

P1: As a foreigner with poor-english skills I want to view what I am ordering because I can’t read the descriptions.

P2: As a working mom I want to filter what I am looking at because I don’t want to flip through food-pictures that I know my children will not like.

P2: As a bored professional I need to find something truly mouth-watering for lunch because I need something to look forward to at work.

P2: As a professional athlete I want a way to order super quickly because I need to eat all the time and don’t have time to make food myself. .


Feature Details




  • Upon logging into the seamless application, our test A beta-users will be met with a pop-up notification prompting them to try the new “Food Surfing” feature.


  • If the user clicks “YES”, the user will be taken to an interface in which an image of a tempting food is displayed. The first time users interact with this screen they will be given a 3-step description process of how to use the feature, including the swiping gestures, favorites list and “instant order” function”. After clicking “Got it” they will be able to interact with the feature as intended.


  • Users will have the ability to swipe to the right. If the user swipes right, the meal will automatically be added into a favorites list. This feature will also be enabled by tapping a “yes-equivalent” icon.


  • User will have the ability to swipe left. If the user swipes left, the image will disappear and a new image will show up. This feature will also be enabled by clicking a “no” icon.


  • User will have the ability to click an “i” icon in order to access more information about the food-item and view other menu items from the the same restaurant.

  • Users will have the ability to filter the images they are shown based on price, delivery time and ratings.

  • Users will have the opportunity to view images filtered by cuisine through a separate tab.

  • The user can click a large one-click “order now” button and the food will be delivered directly to the user within the estimated delivery time.



  • User will have the ability to click a tab icon representing favorites. Upon clicking the tab, users will be taken to their favorites list.


  • Users can click on a ‘back’ and a ‘shopping cart icon’. The shopping cart icon will take them to their shopping cart.


  • Upon entering the favorites list, users can tap a favourite meal. Upon clicking which meal they want they will automatically order that dish and be thanked for their order.

  • Users will be prompted to leave feedback on the new feature by answering one simple question with three check-box options.


  • Upon answering the question they will land on a “thank you for ordering page” and have the opportunity to navigate back to the original UI.


  • When re-entering the original seamless user-face subsequent times, a small, but noticeable “Food Surf” widget displayed on top of the UI will take the user back to the Food Surf feature.



Metrics and Goals

Financials and Facts (Q4, 2014):

  • Grubhub Seamless had 182,800 daily orders to restaurant partners (30 000 partners)

  • Total user-base: approx. 5.03 million

  • Gross Food Sales $1.8 billion

  • Revenues: $253.9 million

  • Record-Earning growth in 2014

  • Fast growing mobile user-base (>46%) with equal purchase rate

  • Fast-growing market place

  • High Margins

  • Satisfied customers and restaurants


Data Insights:


Note! The following information is based on the Seamless Website (due to limited data insights to the mobile application). We believe that this audience is a statistically valid representation of our mobile audience.

Targeting Demographics:

Our website statistics show that Seamless is significantly more popular among females. After conducting research into other food-sharing photo sites we have increased confidence in our assumption that our new feature will be valuable to the majority of our user-base. Women are more attracted to photo-sharing services in general as multiple data statistics show. A few examples of demographics across the most popular image-sharing sites are displayed below:
















There is also research proving that this feature will appeal to our male users.

A scientific study of young, healthy men examined the specific physiological reaction of the test subjects to images showing either delicious food or non-edible objects.

The concentrations of different hormones in the blood such as grehlin, leptin and insulin, which play a role in the regulation of food consumption, were measured. The researchers observed that the concentration of grehlin in the blood increases specifically in response to visual stimulation with food images. This study demonstrated that the release of ghrelin into the blood for the regulation of food consumption is also controlled by external factors. Human brains process these visual stimuli, and the physical processes that control our perception of appetite are triggered involuntarily.

Furthermore, a study conducted by the Society for the Study of Ingestive Behavior suggests that this specific hormone, ghrelin, increases peoples willingness to pay for food, while simultaneously decreasing their willingness to pay for non-food items.

Market Opportunities:

Based on GrubHub Seamless financial reporting data from Q1 2014, there is reason to believe that we have a massive and untapped market opportunity. 

The US has over 350 000 independent restaurants, whereof 30 000 currently are Seamless Partners. Americans spend 67 billion on take-out annually, while only 5% of this is online. As mobile adoption continues to grow our products will only become more attractive. Through further product/business development and marketing, Seamless can potentially increase revenues from 1.8 to nearly 8.5-9.5 billion.  

Foodie - Trend

Internet trends and networks in the food category is also a profitable and attractive market to leverage. Social networks, apps and blogs about food, recipes and restaurants are spreading virally. To provide a mild indication of what the demand looks like we have looked into some popular food-related hashtags on social media.


#food: 153,968,305

#foodporn (popular term for good food): 46,050,502

#foodie: 14,248,985

#nomnom: 7,425,798

#dinner: 32,440,363

#yummy: 50,142,383

Market Size:

  • Beta-user launch: 10% of total active users: ca. 5 000 000.

  • Our 500 000 beta- users will be from the New York City’s five boroughs.

  • Population New York City: 8,336,697

  • This is due to the vast number of NYC restaurants delivering through the seamless app. Currently NYC accounts for 7074 of >30 000 total Seamless’ restaurant partners across 800 cities in the US and London.

  • Our beta-testers will be selected based on the following criteria:

    • Users who use the Seamless service >3 a week.

    • Users who primarily use the Seamless mobile application (>40% users order on mobile (vast growth))

    • Gender ratio of beta-users should be equivalent to the gender ratio of our total user base to get accurate results.


  • Open-rate: % beta-users that click yes to the alert upon logging into the seamless app after product-launch.     

    • 20% open rate at first login after launch.

  • % of beta-testers that try new feature even though they dismiss initial invite/push notification.

    • 60% over 2 months following launch.

  • Total aggregate of favourited food-images across user profiles.

    • >2/images per active user - 2 weeks after launch

  • % of favourited foods ordered.

    • 40% within first month.

  • Instant order/purchase-rate using the “order now” button. % of users using the “order now” button.

    • 30% within two months

  • Drop-off rate : % of users who try it once and never return to use the feature (churn rate).

    • <40% within two months

  • Satisfaction rate: % of users that report satisfaction on customer feedback request.

    • 60% of users after trying feature first time within two months

  • Conversion rate:

    • 50% active users after two month launch. Active users= uses feature twice weekly.

  • Revenue: % increase in Seamless revenue

    • 10% increase over first year months

  • % of users that order from restaurants they have not previously ordered from.

    • 50% during first month


  • Our minimum product adoption rate should be over 40% (200 000), with a goal of 50%(250 000) over Q2 and Q3.

  • Our overarching goal is to increase the amount of new restaurants users order from. Our goal is 2 new restaurants per week per active user within first year.

  • By enhancing the seamless experience and increasing engagement and purchase-rate within the Seamless app, more restaurants will profit from our users. As restaurants grow their profits through increased customer acquisition, more restaurants will want to partner with us. As our partnerships continue to expand, more customers will become aware and drawn to our platform and thus continue the upward spiral.

Key Stakeholders


  • Management: Make decision and give OK to project by February 18th. Owner: Director of New York.

  • CFO: Establish final budget and outline financial cost structures by February 23th. Owner: CFO of New York Office.

  • Developers/engineers: Develop MVP by March 25th based on design and prototype from designers. Owner: CTO of New York Office.

  • Design: Sketch design and prototype by March 10th ready for user testing. After usability test, final design delivered to CTO by March 15th. Owner: Head of Design.

  • Product: Conduct User Research by March 5th. Deliver 10 users for user testing by March 9th.

  • Sales: Approach >100 restaurants with a variety of cuisines in New York City and encourage them to participate in initial launch by explaining their gains, offering to take pictures of their plates and submitting them to app. Owner: Head of Sales.

  • Marketing: Ensure quality of photos submitted by restaurants. Send photographers to restaurants to maximize quality of initial feature photos. Develop marketing materials for new feature within 6 weeks, ready by April 14th. Owner: CMO of New York Office.  


‣ design: March 10th. Duration from budget sign-off: 15 days.

‣ design signoff: March 15 th. Duration: 5 days.

‣ development: March 25th. Duration: 10 days.

‣ internal testing/QA: March 28th. Duration: 3 days.

‣ launch signoff: April 5th. Duration 7 days.

‣ launch: April 6th. Duration 1 day.

Evaluation of Initial Launch: June 5th, 2015.



Risk #2 Restaurant partners:

Primary research suggests positivity towards the feature, so it should not be a challenge to get partners onboarded. We will initially approach restaurants with rich photo material of menus. Due to the vast amount of venues in NYC, if some restaurants choose to opt out we have many alternatives (more than 6000). Should images not meet our quality standards we will hire photographers to ensure their quality and/or help venue owners build portfolio.


A risk is also that users ignore the invitation or find the feature useless/clutter/unnecessary. If we see lack of engagement or high drop-off rates we will revisit and refurbish the content and basic functionality/UX/UI of our feature.  If users reject to try the feature we will incentivize through discounts when ordering food through the new feature the first time they try it. 


Future Plans (Product Roadmap)

Screen Shot 2015-04-07 at 14.01.22.png


TIMELINE Product rollout


Assemble team and build MVP


Roll-out MVP to Beta-testers in New York City


After our MVP roll-out we will consider our KPI’s and evaluate our goals and metrics. If we succeed to meet our calculated KPI’s, we will continue to refine, build and roll-out the product in other big cities, starting with these three after a two month initial launch in NYC.

  1. Chicago

  2. Los Angeles

  3. San Francisco


If product still meets KPI’s, we will roll out the feature to our entire user-base when new restaurants partnerships are successfully established, within one year.

To help facilitate the inclusion of over 30 000 restaurants that may want to participate we will send out an email where they can request invitations in order to control the sudden demand. We will need to set specific requirements for resolution and quality of images submitted in order to ensure the products continued value.

Q1 2016:

When development requirements are met, restaurants will have the ability to upload images of chosen menu items into the feature themselves. We estimate this to be possible within 1 year of initial launch.


Social Recommendation

Our user research also provided us with some interesting information indicating the value of social recommendation and recognition from users social networks inside the Seamless platform.

Our next steps would be to consider the overall value and ease of implementing a social feature within the product that would allow users to view which friends in their social networks have ordered or liked the images that show up in Food Surfs stream.

This should be a quick process as Facebook’s API is open and requestable.

In addition, the social implementation will open other interesting opportunities, including, but not limited to the following options:

  • Inclusion of social profile widgets underneath presented photos to symbolize who has favorited/ordered the food before you.

  • Food recommendations based on friends preferences, derived from algorithmic-patterns of similar food-taste profiles

  • Social-food sending - enable users to send food to other friends

  • Social food recommending - users can recommend dishes to other friends manually within the app

  • Social Food Sharing - Users can share on social networks when they order food and what they order.

Increased Revenue from restaurant sponsoring

The new feature also opens exciting opportunities in terms of new revenue streams coming from sponsored images.

A solution would be that restaurants can have the opportunity to pay a premium to have a larger user-base view their images and to have their menu items featured more frequently in the stream.