2024 - Current
Places
The world's most powerful AI dining search is here!
Overview
The Places mobile app features over 12,000 restaurants, bars, and cafes in Dubai, with their digitized menus.
Challenge
Filters are out. Open Search is in.
Search is shifting. People today are transitioning to conversational interactions with their digital devices. Think ChatGPT being prompted to make an email sound more professional, or Alexa being asked to turn the lights on.
On the other hand, the F&B tech space is over-saturated with food delivery partners, discount programs, loyalty programs, and even digital payment rails to settle a bill once you're at the venue. Yet, practically no one was doubling-down on the "Get people in the door" discovery element.
Why? Because LLM's don't have the data sets that are required for this use case (and will likely not for a very long time), which leaves the only other option - harvesting all of this data manually. The sheer complexity of gathering all relevant data and supporting assets, then sanitizing them, and then repackaging it all in a seamless one-size-fits-all experience is a task only the insane would embark on. (We're pretty crazy at Places).
Solution
A new standard has arrived.
As Head of Design for Places, I was tasked with my biggest challenge yet - design an AI dining search experience specific to the F&B segment that has no checkbox filters, but rather relies on a single search box to cater to even the most diverse and complex search queries in any language.
Furthermore, I had to design a browsing experience that allowed quick high-level comparative discovery, as well as allow users to easily deep-dive into selected places for additional information. This was particularly challenging to finding the sweet spot in how much information to show, when, and how to display it in the most natural, intuitive, and familiar way to users.
From the countless simulations we ran, we continuously streamlined the experience to shave taps and milliseconds off the journey experience to getting to the intended destination. Whether it was getting directions to a place, viewing its menu, browsing offers, or reading/leaving a review, etc.
Execution
One app to rule them all.
We kicked things off with a Design Thinking Workshop to define our key personas and ended up with 4 target users:
Raj: A loving father looking for great deals across the city to enjoy with his family.
Ziad: A male socialite who likes to let loose at the city's latest and greatest hot spots.
Jane: A social mother looking to explore new places to enjoy with her crew for breakfasts, brunches, or afternoon coffees.
Sarah: A digital nomad who takes her laptop to hip and equipped cafes around the city to get some serious work done.
For the MVP, we decided to focus on Raj, and how he might use Places.
We asked ourselves, "How would a discount-seeker go about seeking discounts around the city". Surely he would need visibility on:
Menu
Reviews
Location (and Directions on getting there)
Opening Hours
Amenities (Parking situation at the venue, WiFi available, outdoor seating, dog-friendly, EV charging, etc).
Price Point ($, $$, $$$, $$$$ average spend)
Offers Available (Taco Tuesdays, etc)
Ability to add a place to a "Favourite" list (or create custom lists).
These needs were cleared by the other personas where we added a few more offerings, but then I got to work defining the user journeys Raj would embark on.
Search to Venue Journey
Menu Discovery Journey
Read Reviews Journey
Promotions Discovery Journey
Table bookings Journey
etc
Each of these journeys went into wireframing, and were validated in tandem with tech leadership, app development, AI, business leadership, and even our sponsor users we consulted to represent Raj.
Wireframes went from low-fi to high-fi, graduating to UI that we proudly released to the public and continue to measure, learn, and refine as needed until present day.
Outcomes
Onwards to the moon.
Since it's official launch in October 2024 (with earlier soft launch in April 2024):
40,000+ total app users
300+ new users per day
1M+ unique searches
12,000+ Places indexed
3.5M+ menu items digitized
Featured on Dubai One TV news (unpaid)
Featured on DubaiEye 103.8FM (unpaid)
Invited by Amazon Web Services to coach regional CTO's on the power of AWS integration (unpaid)
$2M in funding already secured with Series A underway to accommodate scaling to new cities.
Other Work
2024 - Current
Places
The world's most powerful AI dining search is here!
Overview
The Places mobile app features over 12,000 restaurants, bars, and cafes in Dubai, with their digitized menus.
Challenge
Filters are out. Open Search is in.
Search is shifting. People today are transitioning to conversational interactions with their digital devices. Think ChatGPT being prompted to make an email sound more professional, or Alexa being asked to turn the lights on.
On the other hand, the F&B tech space is over-saturated with food delivery partners, discount programs, loyalty programs, and even digital payment rails to settle a bill once you're at the venue. Yet, practically no one was doubling-down on the "Get people in the door" discovery element.
Why? Because LLM's don't have the data sets that are required for this use case (and will likely not for a very long time), which leaves the only other option - harvesting all of this data manually. The sheer complexity of gathering all relevant data and supporting assets, then sanitizing them, and then repackaging it all in a seamless one-size-fits-all experience is a task only the insane would embark on. (We're pretty crazy at Places).
Solution
A new standard has arrived.
As Head of Design for Places, I was tasked with my biggest challenge yet - design an AI dining search experience specific to the F&B segment that has no checkbox filters, but rather relies on a single search box to cater to even the most diverse and complex search queries in any language.
Furthermore, I had to design a browsing experience that allowed quick high-level comparative discovery, as well as allow users to easily deep-dive into selected places for additional information. This was particularly challenging to finding the sweet spot in how much information to show, when, and how to display it in the most natural, intuitive, and familiar way to users.
From the countless simulations we ran, we continuously streamlined the experience to shave taps and milliseconds off the journey experience to getting to the intended destination. Whether it was getting directions to a place, viewing its menu, browsing offers, or reading/leaving a review, etc.
Execution
One app to rule them all.
We kicked things off with a Design Thinking Workshop to define our key personas and ended up with 4 target users:
Raj: A loving father looking for great deals across the city to enjoy with his family.
Ziad: A male socialite who likes to let loose at the city's latest and greatest hot spots.
Jane: A social mother looking to explore new places to enjoy with her crew for breakfasts, brunches, or afternoon coffees.
Sarah: A digital nomad who takes her laptop to hip and equipped cafes around the city to get some serious work done.
For the MVP, we decided to focus on Raj, and how he might use Places.
We asked ourselves, "How would a discount-seeker go about seeking discounts around the city". Surely he would need visibility on:
Menu
Reviews
Location (and Directions on getting there)
Opening Hours
Amenities (Parking situation at the venue, WiFi available, outdoor seating, dog-friendly, EV charging, etc).
Price Point ($, $$, $$$, $$$$ average spend)
Offers Available (Taco Tuesdays, etc)
Ability to add a place to a "Favourite" list (or create custom lists).
These needs were cleared by the other personas where we added a few more offerings, but then I got to work defining the user journeys Raj would embark on.
Search to Venue Journey
Menu Discovery Journey
Read Reviews Journey
Promotions Discovery Journey
Table bookings Journey
etc
Each of these journeys went into wireframing, and were validated in tandem with tech leadership, app development, AI, business leadership, and even our sponsor users we consulted to represent Raj.
Wireframes went from low-fi to high-fi, graduating to UI that we proudly released to the public and continue to measure, learn, and refine as needed until present day.
Outcomes
Onwards to the moon.
Since it's official launch in October 2024 (with earlier soft launch in April 2024):
40,000+ total app users
300+ new users per day
1M+ unique searches
12,000+ Places indexed
3.5M+ menu items digitized
Featured on Dubai One TV news (unpaid)
Featured on DubaiEye 103.8FM (unpaid)
Invited by Amazon Web Services to coach regional CTO's on the power of AWS integration (unpaid)
$2M in funding already secured with Series A underway to accommodate scaling to new cities.
Other Work
2024 - Current
Places
The world's most powerful AI dining search is here!
Overview
The Places mobile app features over 12,000 restaurants, bars, and cafes in Dubai, with their digitized menus.
Challenge
Filters are out. Open Search is in.
Search is shifting. People today are transitioning to conversational interactions with their digital devices. Think ChatGPT being prompted to make an email sound more professional, or Alexa being asked to turn the lights on.
On the other hand, the F&B tech space is over-saturated with food delivery partners, discount programs, loyalty programs, and even digital payment rails to settle a bill once you're at the venue. Yet, practically no one was doubling-down on the "Get people in the door" discovery element.
Why? Because LLM's don't have the data sets that are required for this use case (and will likely not for a very long time), which leaves the only other option - harvesting all of this data manually. The sheer complexity of gathering all relevant data and supporting assets, then sanitizing them, and then repackaging it all in a seamless one-size-fits-all experience is a task only the insane would embark on. (We're pretty crazy at Places).
Solution
A new standard has arrived.
As Head of Design for Places, I was tasked with my biggest challenge yet - design an AI dining search experience specific to the F&B segment that has no checkbox filters, but rather relies on a single search box to cater to even the most diverse and complex search queries in any language.
Furthermore, I had to design a browsing experience that allowed quick high-level comparative discovery, as well as allow users to easily deep-dive into selected places for additional information. This was particularly challenging to finding the sweet spot in how much information to show, when, and how to display it in the most natural, intuitive, and familiar way to users.
From the countless simulations we ran, we continuously streamlined the experience to shave taps and milliseconds off the journey experience to getting to the intended destination. Whether it was getting directions to a place, viewing its menu, browsing offers, or reading/leaving a review, etc.
Execution
One app to rule them all.
We kicked things off with a Design Thinking Workshop to define our key personas and ended up with 4 target users:
Raj: A loving father looking for great deals across the city to enjoy with his family.
Ziad: A male socialite who likes to let loose at the city's latest and greatest hot spots.
Jane: A social mother looking to explore new places to enjoy with her crew for breakfasts, brunches, or afternoon coffees.
Sarah: A digital nomad who takes her laptop to hip and equipped cafes around the city to get some serious work done.
For the MVP, we decided to focus on Raj, and how he might use Places.
We asked ourselves, "How would a discount-seeker go about seeking discounts around the city". Surely he would need visibility on:
Menu
Reviews
Location (and Directions on getting there)
Opening Hours
Amenities (Parking situation at the venue, WiFi available, outdoor seating, dog-friendly, EV charging, etc).
Price Point ($, $$, $$$, $$$$ average spend)
Offers Available (Taco Tuesdays, etc)
Ability to add a place to a "Favourite" list (or create custom lists).
These needs were cleared by the other personas where we added a few more offerings, but then I got to work defining the user journeys Raj would embark on.
Search to Venue Journey
Menu Discovery Journey
Read Reviews Journey
Promotions Discovery Journey
Table bookings Journey
etc
Each of these journeys went into wireframing, and were validated in tandem with tech leadership, app development, AI, business leadership, and even our sponsor users we consulted to represent Raj.
Wireframes went from low-fi to high-fi, graduating to UI that we proudly released to the public and continue to measure, learn, and refine as needed until present day.
Outcomes
Onwards to the moon.
Since it's official launch in October 2024 (with earlier soft launch in April 2024):
40,000+ total app users
300+ new users per day
1M+ unique searches
12,000+ Places indexed
3.5M+ menu items digitized
Featured on Dubai One TV news (unpaid)
Featured on DubaiEye 103.8FM (unpaid)
Invited by Amazon Web Services to coach regional CTO's on the power of AWS integration (unpaid)
$2M in funding already secured with Series A underway to accommodate scaling to new cities.
Other Work