DAVID MCCLUSKY: Hey everyone.
My name is David McClusky.
And I'm a solutions engineer with the Google Maps API team.
So as a solutions engineer, I work
with Google's top customers and partners
to help them solve their business
problems with the power of the Google Maps API.
So as Monica and Paul mentioned, location intelligence
has become increasingly important
to businesses of all sizes.
But only now are they really available to businesses
of any size.
So you don't need to be an Uber or an Amazon to take advantage
of location intelligence.
Any startup, any company can build a platform on Google Maps
through the Google Maps API.
So I'm going to tell you a little bit about some
of the APIs that Paul showed you on a previous slide,
how they can be used in a real life situation.
So I'm going to show you a demo today that
demonstrates how a small company can use location intelligence.
This is a fictional coffee delivery
service called Coffee Pop.
And I'm going to show you how they
can use the API to drive better engagement,
streamline their operations, and deliver greater satisfaction
to their customer base.
OK, so Coffee Pop, what is Coffee Pop?
So this is a small, again, fictional coffee
and cake delivery service.
I stress fictional because last time
we had people trying to download the app on their phone
and order coffee, and it wasn't working out for them.
So Coffee Pop, they brew coffee out of barista trucks.
They have a bicycle riding workforce
that delivers coffee and cake to people at their own location
on demand.
And then they can move their barista trucks around
to better optimize their service area to maximize
the number of customers.
So therefore they need to connect their customers,
riders, and delivery trucks together in real time
to keep everyone informed about current operations
and the itinerary and allow management to keep
an eye on the entire operation.
So to do this, they built three separate applications,
one for the customers, one for the riders,
and one for the managers.
So what does the management team do?
So they have an app to view and improve
the real time performance of their entire operation
in real time.
The customers have an application
so they can place an order for coffee and cake
at their location.
And then the delivery riders have
an app so they know when there is an order ready
and to get routed to the customer.
So I'm going to show you how each one of these applications
can be built with the Google Maps APIs.
All right, so this is our management dashboard.
So this provides a view for management
into the entire operation of their business.
So we have things here on this dashboard like customer
satisfaction scores, the number of active orders,
the percent of orders that are late or behind schedule.
I can see recent feedback.
You know, someone says three stars, my coffee was on time.
Someone says one star, you were three minutes late.
I can also view a map.
So this map gives me a live, real time view
into everything that's going on in my delivery zone.
So what I have here in the middle,
this icon here represents my barista truck.
This is where we're brewing the coffee.
So I can click on it and I can view our entire delivery
service area.
So this polygon here represents--
it's what we call an isochron.
It's everywhere you can drive within 15 minutes in this case.
So we want to set up a delivery zone in real time
to ensure that all of our customers
can be serviced within 15 minutes.
So we're using real time traffic data
to generate this in real time.
Let's look at some of these other icons
and what they represent.
So here we have a delivery rider.
I can click and zoom on him.
So this is one of our bicycle riders.
And I can view what his current task is.
So he's right now tasked to go pick up coffee
at a barista truck and then deliver it
to this customer over here.
I can also see these icons.
You see the little happy faces.
And if I zoom, yeah, there's some frowns over here.
These are customers that have already been serviced
but are either happy or unhappy.
So I see over here I have a couple unhappy customers.
So then I want to dig down and try to investigate, why
were these customers unhappy?
Was their orders wrong or maybe they were late?
And I can bring in other layers of information,
other sources of information to try
to analyze what went wrong here and better understand
the situation.
So one thing I can do is I can turn on a real time traffic
layer right here in the app, and I can view real time traffic
conditions to see if maybe that's impacting
our service in this area.
Maybe I need to change our service area a little bit.
So the next thing I'm going to show
is now what the Coffee Pop experience
looks like from the perspective of a customer
from a mobile app.
So here I have an iOS application.
This is built with the Google Maps SDK for iOS.
And in this case what the customer would
be doing and interacting with this experience
is dragging the pin around here to indicate where they
want their coffee delivered to.
Typically this is just going to be their existing location.
So we get their location from the device and say,
this is where I want the coffee delivered to.
But perhaps you're on your way to the park
and you want your coffee delivered there.
So you can move the map pin.
Now the interesting thing here is the number you see here
at the bottom of the screen.
So this is the time estimate.
Now a lot of things are going into this time estimate.
It's the amount of time that it's
going to take the delivery rider to get to the barista
truck, the amount of time it's going
to take to process the order and then get that order over here
to the customer.
And so it's doing an assignment from the orders
to the delivery riders in real time in an automated
fashion behind the scenes.
So there's no dispatcher here involved.
This is all just happening in an automated fashion.
So now that I know my time estimate,
I can click to place my order.
I can say I want some coffee, some cake.
I click Confirm.
It's been assigned to a delivery rider.
I can see a map.
I get time estimate.
And I can click Order Now.
And then now I can monitor, in real time, that delivery driver
as they come to deliver me my coffee.
So I can see what's going on here.
And then I will now show you the third application.
So this is the application that the delivery riders
would have with them on their mobile phone.
So in this case this is an Android-based application
using our Android API.
So the first thing that it would do
is detect that the delivery rider is inside
one of the active barista truck delivery zones.
And once it is, once that rider is there,
they are allowed to sign into the application.
And instantly they're matched up with a job
that's waiting for them.
So they can accept the job and they can view the active job.
And in this case, it doesn't really
actually the most sense just to be
assigned to one delivery job.
It could be several.
So you want to go to a barista truck, pick up several orders,
and then deliver them all.
So our Directions APIs being used here behind the scenes.
And what that's doing is actually
doing waypoint optimization.
So it's routing them in the most efficient route
to these multiple destinations.
They can view the-- first thing I need to select a job,
activate a job.
Yes?
AUDIENCE: Is it doing the traveling salesman algorithm?
DAVID MCCLUSKY: It's doing a variation of the traveling
salesman problem.
So in this case it's one worker and up to-- we
can do up to several dozen waypoints in this.
It's not doing hundreds or thousands
of waypoints, which becomes very computationally intensive.
But with a smaller subset, yeah, we can do that.
So the driver's given a route, and he's
given the set of directions to go to and do
those multiple deliveries.
And when the deliveries are done,
you can mark them as complete.
Or what you can do is actually use
the location from the device itself.
So if he's actually traveling around,
it could detect that the driver has entered
into the same zone as the customer location and said,
hey, that delivery's been made.
Mark those jobs as complete.
So this is just a few of the ways
you can take advantage of the Google Maps APIs
to build out an entire business in an automated fashion.
So it doesn't require much infrastructure.
It doesn't require servers.
It doesn't require data centers.
You can build this all in the cloud with just
a few applications, and really power
your business with location.