Geographic Information System in online food ordering - Ordering Stack case study
The omnipresence of GPS and Google Maps-inspired systems the challenges for a swift and flawless online food ordering can be not that obvious. But there are several challenges to overcome when designing a reliable online food ordering system. This time, it is all about your knowledge, Jon Snow.
In the good ol’ days of phone food ordering everything used to be simple. The customer placed the order, while the staff had to manually verify if the address is in the delivery area. Larger fast food restaurant chains had a central customer service offices, with multiple assistants collecting orders and managing their flow to the right restaurant.
The process had multiple disadvantages and flaws. Just to name some:
The language problems - when it comes to voice communication,
there are multiple challenges to overcome. The customer can be a foreigner,
so the assistant needs either to speak his or her language (rather unlikely,
especially in multilingual cities and communities like Berlin or London)
or to communicate in some mutually comprehensible language.
That can be even more challenging when two non-native speakers whose skills are far from perfect try to communicate and understand each other despite different dictionaries and misguiding accents. Just think about Berlin mentioned above - there are people from 190 nations living there, constituting more than 20% of total city’s population. The majority of them come from Poland, Turkey, and Syria.
The communication problems - having a common
and understandable language equals not a communicational success.
The customer doesn’t have to be in his or her best condition
when ordering food. One can have a hard throat infection, fever,
be drunk or suffer from a hangover - you name it.
And forging a proper communication with such person can be challenging.
The social problems - food is a more delicate matter that it seems to be.
Nearly half (45% to be precise) of Millennials (people born between 1980 and 1990)
follow some kind of diet. Reasons vary - from reducing weight to staying healthy,
personal beliefs, or allergy. Regardless of the reason, people wish not to be
judged by another person while ordering food and when it comes to diets,
the process can take a long time. The customer asks multiple questions irritating
the assistant and discloses details of his personal diet.
Inefficiency - last but not least, a phone order is an inefficient process.
It can be scalable only by hiring new employees and providing them
with proper tools. Also, the system usually collects little to no data at all -
no more than notes and things that assistants remember - and that’s neither reliable
nor enough to collect data-powered insights, not to mention challenges
in collecting and processing this information.
Considering the challenges above, it is not surprising that there is an increasing need for digital ordering systems supporting the process. And that’s where the geographical information system comes in handy.
How a geographical information system supports digital food ordering
Near the end of an online food ordering process (in the end there is a checkout) the customer needs to provide the vendor with his or her address. That’s the easy part.
What is a geographical information system (GIS)
The GIS-class system is a digital application or a framework that captures,
analyzes, and provides the user with an interactive geographical data.
The main goal is to provide the user with a tool to create a query to the system,
edit the map-based data, and provide the output.
These operations need not be entirely delivered in a visual form - there are multiple uses where only a text-based answer is sufficient - these include all the statistical processing with geospatial data included, like migrations or employment. When it comes to online food ordering the geographical localization is crucial - the customer needs both to provide his or her position or address and select the desired restaurant that can deliver food to the chosen location.
How GIS supports online ordering
At this point the system needs to process the information about the customer’s address to check if he or she is in the area of delivery. This can be tricky for various reasons:
Improving customer experience - a more advanced
geographical information system can provide some good experiences
like autocompletion of the delivery address or an ability to find the
user’s location, assuming the access to the localization data of the device,
be that a GPS in a smartphone or an IP address in desktops and laptops.
According to the SuperOffice data, 85% of customers are willing to pay more
for a great customer experience, so in fact the absence or a presence
of a well designed map can be a difference between a large or thin margin
or even a sale or a lack of sale at all.
Multiple tariffs for different locations - depending on the distance,
the ease of delivery, an hour, or an existing promotion.
One can easily imagine "university happy hours" where there is
a discount for students ordering from university locations - because why not?
Limited resources for delivery - the driver has to deliver
multiple packages and dishes, so the system needs to estimate the time
and provide the customer with it. Also, a modern, more sophisticated
solution assists the driver with route suggestions to optimize the time
and cost of the delivery. The problem is one of the hardest challenges
for a combinatorial optimization known as a traveling salesman problem.
A strict area-based division - companies tend to use more
or less clear ways to divide the city into areas of delivery,
thus making the delivery system even more complicated.
A more sophisticated and integrated system can deliver a real-time
optimization of delivery based on the available couriers or general
workload of a particular restaurant. Sometimes it can be faster to
deliver a meal from a restaurant farther away, than from the near
one that suffers from lunch-attack from offices around.
Considering the list above, the GIS-class solution is the only way to deliver a modern digital ordering solution. But apart from powering the program itself, the system also provides the company with data to analyze and build further optimization;
Collected geospatial data can deliver multiple insights and usable information.
The first recorded example of this type of data-mining comes from 1854 and was delivered
by John Snow, a London-based physician, who tackled the cholera outbreak in London.
As he mapped the cases, he spotted that dots representing every case are clustered
around the water pump near Broad (Now Broadwick) street.
This time, you were the one to know better, Jo(h)n Snow.
For people of these days, who believed that the disease was spread by miasma in the air, the discovery was eye-opening. The pump appeared to be contaminated by a nearby cesspit. More about the story is shown in Guardian’s article and we will spare the details - we are writing about FOOD after all.
The company can harvest insights from geospatial data in the same manner as John Snow did - by collecting it and analyzing it a talented analyst can find:
Which neighborhood finds restaurant the most popular -
it can be used further in promotions or targetted offers
Which localization brings the biggest and the lowest income -
this can be used in further expansion, to spot the best locations in advance
What are ways to optimize the deliveries -
more sophisticated app informs about the ways to maximize the drivers’ efficiency
What are locations that are out of reach, but could be profitable -
the system can contain the information about the non-processed orders
from potentially attractive locations.
Historical data about the orders -
by data correlation the company can easily assume the upcoming orders
from particular locations and assume the reasons behind it. For example,
with every exam session on nearby university there is an increased need
for a pizza and significantly lower demand for alcoholic drinks.
A talented analyst or a resilient manager can dig out multiple insights from geospatial data.
Considering all the advantages, it is not a surprise that Ordering Stack uses a GIS-class solution.
Geographical Information System in Ordering Stack
Ordering Stack uses a Placematic GIS solution that delivers all needed data by API,
making the solution easy to maintain and reliable. But as we mentioned above,
a sole map processing is only the tip of an iceberg when it comes to advantages from GIS systems.
The system provides also a statistical analysis for better placement of restaurants and potential income from it. The tool is flexible and sophisticated enough to be used by all restaurant-aimed tools delivered by 3e software house, including mobile apps and management systems.
The delivery areas are managed by the UpGrid tool, which enables the user to manually add and manage certain locations.
An obvious connection between the food delivery software and the geospatial
data is only the tip of an iceberg when it comes to building the modern ordering tool.
In fact, the best comparison is a restaurant - while the customer benefits
from everything he or she sees, most of the work is done in the kitchen.
Or in a backend, if you wish.