Create customer and business outcomes with geospatial data 🎯
In today's world, geospatial data is everywhere, enabling location-based services and optimizing business processes.
Our favorite apps and websites tell us where to find a coffee place or where we can find and return a shared bike, scooter or car. They also allow us to see what on-street parking for our own car costs, exactly where we just parked and let us instantly pay for it. Also, companies of different sizes and industries have applications in place to manage and optimize their strategy and execution for assets and actions around geographical distribution and routing.
With the Geoman.io Editor, we offer a SaaS solution with options for everyone to find what they need. The free version already provides the most powerful online editor to draw, update and convert geodata. If you also want to store your data with us to make sure everyone is working on the latest and greatest or if you want to benefit from some advanced or even professional drawing, editing, collaboration, conversion and customization, we got your back too.
Let's have a high level look at some use cases supported by Geoman.io and how those create value for individuals and companies from different industries:
- Shared Mobility
Create and update operating area and stations in order to define, where cars can be picked up and returned. Forecast demand in different areas as adjust pricing in order to maximize utilization and revenue.
- Urban planning
Municipalities divide city areas into different zones from multiple perspectives like planning and optimizing the mobility mix and priorities for different modes of transportation or to define land use.
- Real estate development (PropTech)
Monitor real estate prices and shifts in demand in order to identify investment and housing opportunities and to allocate development capacity accordingly.
- Financial Services (FinTech)
Detect and prevent fraud by checking for abnormalities in customer movement profiles.
- Insurance Services (InsurTech)
Adapt insurance premiums depending on customer whereabouts for pay-as-you-go insurance plans.
- Logistics (IoT)
Manage and simulate merchant vessel routes and corresponding predictive arrival and departure times in order to optimize the network.
Map out network coverage scenarios in order to plan grid optimization, expansions or the introduction of new technologies.
Plan detailed routes of autonomous vehicles in order to train and optimize machine learning models.
- First Responder
Create situational awareness for first responders to plan and execute operations.
For most of those use cases, huge amounts of geospatial data have to be created and updated. Often involving distributed teams or otherwise more than two people, not necessarily sitting next to each other. Ultimately, the data has to be stored and made accessible via graphic user interfaces as well as programatic interfaces in order to create the intended outcomes.
In many cases, we could observe a similar sequence of events:
- A new application requires both, visual and programmatic handling of geospatial data or the handling of geospatial data for an existing application by sharing Excel files and the like just became too cumbersome.
- After some initial exploration, engineering teams find that there is no fit for purpose solution on the market. As the use cases at hand do not seem to be very complex, "just a basic user interface to draw on a map and store it", they suggest to build a custom solution (plus engineers love to build things).
- Teams start to build a custom solution, realizing that it is a more effort than expected. Drawing useful geometry on a map comes with a steep learning curve for users and requires quite some comprehensible data validation and autocorrection functionality to avoid gaps, overlaps and invalid data.
- Fast forward a few months, the solution is ready and somewhat does the job.
- As the teams now gained some first-hand contextual experience, they start to discover what other value pockets geospatial data management can unlock.
- From now on, the use cases and related complexities are in a different order of magnitude but as there already was the invest in a custom solution they (feel like they) have to continue.
Imagine, you could get geospatial data management as a service. Imagine, Geoman.io would be a little bit like Google Docs for geospatial data. Imagine, you could:
- Draw geometry using mature and proven drawing and editing tools
- Invite colleagues and partners to create and update geospatial data leveraging their local knowledge
- Visualize and share data in order to validate the quality of the data or involve stakeholders in your workflows
- Provide a wider audience access to your geo data and be surprised what people with different skillsets can do with geo data
- Access your geospatial data via state-of-the-art APIs and not worry so much about formats or integration with other applications and interfaces
Geospatial data management, done right instantly adds value and creates a basis for future use cases leading to outcomes you cannot even think of today.
Tell us about your use case for geospatial data management. We are here to help.