Introducing Toast

After taking into account all of our user feedback, the sustained appetite for the more mood/experience/location based version of Last Eats, we decided to break from our earlier platform and create something new.

Enter "Toast." Toast is a food recommendation app that leverages your trusted network to make the decision of where to eat the fastest, easiest and most satisfying experience possible. We’re doing this through simple, trusted, actionable recommendations from friends (driven by mood and location).

Like it's predecessor, Toast is a word of mouth recommendation platform, but with some distinct differences.

  1. It's a native iOS app
  2. Mood and location are the foundation of the platform
  3. You can add as many Toasts or recommendations as you want. There is no limit, but you can designate a current favorite or "Top Toast" 
  4. Restaurant reservations are enabled
  5. We're launching in NYC only (with an emphasis on everything south of Union Square as well as Williamsburg)

From Last Eats to Toast

When we started Toast, our model of radical selectivity evolved. We softened the be-all, end-all singular destination limitation and extended our premise to include extraordinary food experiences that are tied to mood and emotion. We realized with all of our research into Yelp/Google and all other impersonal digital food discovery tools that mood based discovery was highly unreliable on other platforms.

If I'm looking for great Thai food, I can source any generic digital restaurant ranking/evaluation tool to find an approximation of this end desire. If on the other hand I want restaurant experiences that are "fun", "simple" or "comforting", these criteria are distinctly personal and much harder to reliably source from strangers - or people who don't know the nuance of my own personal taste (i.e. my definition of "fun" is likely very different than that of a random person on the internet).

Market Positioning and Analysis

We began by systematically breaking down the competitors in food discovery into relevant categories. These included: tastemakers, established tech leaders, first movers, photo based discovery, restaurant delivery/reservation apps, socially optimized food discovery and industry insiders.

We then partitioned the companies into quadrants that express their relative positioning to Toast respective of relevance and trust.

If Toast could deliver the most trusted, relevant recommendations that were tied to delivery, take out or reservations, we could differentiate our offering immediately.

First point of contact in app

When a user logs into Toast, we immediately have them select the mood that they are feeling and or seeking. Then we default to their current location, although they can easily choose a different one if they prefer.

Once they select a mood and a location we immediately showcase a series of restaurant that fit the collective criteria, sourced from friends and defaulted to the most recommendations and or closest location. When a user finds a restaurant that looks appealing, they can easily read toasts (reviews) from friends and friends of friends, determine the type of cuisine, price point and walking distance.  A user can then click on a restaurant to see photos of the food, a map of the location, menu, directions, website and more. The Foursquare API provides much of this data for us. Our task was to take all of this data make it as consumable and immediately actionable as possible.

Our ultimate goal with Toast was to get our users to an incredibly delicious, unique dining faster and more reliably than any other food discovery platform. First, we made every restaurant on Toast tied to one click Pick Up or Reservations. This was a critical point of emphasis for us as means to enable our users to take action on a compelling option faster and easier than any other food discovery tool

We did this by crafting an algorithm that took into account :

  • A user's proximity to the restaurants that fit their mood
  • The number of times a restaurant is toasted
  • Whether or not the restaurant was given a Top Toast designation - which was the equivalent of the singular, be all end all Last Eats declaration. We brought back a level of radical selectivity from Last Eats with the arrival of Top Toasts. These are singular designations that are tied to just one restaurant, put on a pedestal. Algorithmically these toasts carry more weight than a regular toast and are thus positioned earlier in the discovery feed. As with Last Eats, these designations can change at any time.
  • The number of likes a review for a place has received.
  • Eventually, our goal was for users to self-select their best friends on Toast so we could appropriately bias their reviews as part of our ranking algorithm.

In addition to the standard form of consuming content on Toast through the swipe to discover platform, there were a number of early, committed users that demanded another way to discover content. They wanted to see all of the toasts specific to a mood or a friend relative to their position on a map. Additionally, we added the ability for users to just see Top Toasts declarations or to just see recently added Toasts.

We also added even more  social functionality through an Activity Feed where users can see bleeding edge toasts made and endorsed by people within the community.

User generated hashtags added another layer of specificity and personalization that can be created and followed as another means of discovering distinct content. Although we provided some stock hashtags that we easy for users to select and add to their Toasts, we quickly noticed users were adopting their own tags for the experiences that mattered most to them.