What are Static Locations?
For a company, static locations are entities of their business that don’t move as time passes. For example, for a micro-mobility company such as Bird, or Lime static location would be a station. For a food delivery company like Instacart or Doordash, it would be a restaurant. For a grocery delivery company, it would be a warehouse. For hotel and restuarant chains, all their business is about static locations.
A static location is a big enough entity that can influence how the supply or demand behaves. Hence it is imperative to analyze how these locations perform and behave in context to users or partners or vehicles. Sometimes, static locations are defined for a business (as explained above) and sometimes we can create them.
For example, for a carpooling company, the static assets might not be defined for the business specifically. But, even office tech parks could behave like a static entity. Point of interests such as parks, malls that act as pickup points can also be insightful static locations for a ride-hailing company.
Decisions on Static Locations
What kind of decisions businesses can take on static locations?
- Restaurants for food delivery companies
- Hotspots / Stores for last-mile delivery companies
- Warehouses for supply chain companies
- Shuffling scooter between stations
- Doing dynamic pricing based on location (like Airbnb)
- Stations for vehicle sharing companies
- Bus Stops for bus shuttle companies
- Bank branches / ATMs
- Restaurants (or any retail business)
Which translates to the following questions:
- How much time does a rider spend on this restaurant for parking?
- What is the average shelf life of an object in this warehouse?
- How far are people from this station when they look for scooters?
- How much time does it take to reach this store?
Trips or Movement
- Where do people go from this bus stop? What are the common routes that they take?
- How many of trips come back as a round trip? Top origin-destination pairs?
Trip or Movement analysis is a different ballgame altogether. Trip analysis is useful if you have questions such as:
How do my users move in this city? Where do they go? What does the “flow” of this city look like? How does that change throughout the day?
Analyzing Static Locations
To make those decisions, what are the kinds of analysis you should be doing on static locations?
I- Properties of Events
To analyze the performance of the static location:
- Cancellation of rides on a station
- Orders accepted for the restaurant
- Start/end trip ratio for the bus stop
- Number of power users at each location
With these metrics, also analyzing their:
- Time trend
- Percent change from last month / last day
II- Demand and Supply Analysis
To decide whether to shut down a static location:
- User searches within 4 km to the warehouse
- Distance distribution of idle riders to the restaurant
III- Time Spent at the Static Location
To decide the bottlenecks in the journey funnel:
- Idle time spent by scooters on the stations
- Prep time of orders of the restaurant
- Time spent in the last-to-last mile (ie, from the main gate to the apartment door)
IV- Movement Analysis
To analyze how users move with respect to the static location:
- Destinations they go to
- Paths they take
- Round trips taken
- Repeatable users/ trips from each of the locations
Depicting Static Locations
How should we analyze these static locations geospatially?
Since static locations are fixed points on the map, you can either represent as a point on a map or as a marker. The attributes you can play around with the size or the color as the attributes.
Table View is a good way to get a bird’s eye view for all metrics and understand in one view your top-performing locations.
How can Locale.ai help?
If you are a micro-mobility or a last-mile delivery company, chances are these static locations are a primary aspect of your business. At Locale, we are creating examples of companies that are their unit economics, cost per delivery, utilization by doing geospatial analytics and rapid experimentation.
Our product allows you to get all your geospatial data of your users, vehicles, partners, stations and create all these analyses in minutes and get insights to optimize and improve ground operations.