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Spatial Data & APIs

Plug-in Developer

Software startup developing a CRM plug-in leverages Pitney Bowes data to put itself on the map.

Client profile

  • Software service built on top of a leading customer relationship management (CRM) solution that facilitates development of location-based workflows
  • Plug-in capabilities include mapping, schedule planning, route optimization, real-time geolocation, territory management and geoanalytics

Business goals

  • Prepare for rapid growth by ensuring plug-in solution effectively serves diverse users
  • Provide a wide variety of unique boundaries to help users visualize sales territories and logistics considerations
  • Minimize work required to integrate datasets into the plug-in, to reduce impact on operational efficiency

Benefits

  • High-quality and up-to-date mapping information enabled startup to bring stronger product to market
  • End users can make better-informed decisions about sales and CRM activities
  • Startup has quickly become one of the most popular plug-ins for a leading global CRM system
  • Easy data integration enables rapid growth in customer base without taxing limited staff resources

Datasets used

US Census Boundaries

Pitney Bowes US Census Boundaries includes state, county, tract, block group, block, MCD, and place boundaries.

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Colleges

Pitney Bowes College Campus Boundaries provides polygons for nearly 4,300 colleges and universities across the United States.

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Residential Boundaries

Pitney Bowes US Census Boundaries includes state, county, tract, block group, block, MCD, and place boundaries.

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School Boundaries

Pitney Bowes School Boundaries more accurately delineates school district and attendance zone boundaries as well as individual school point locations.

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5 Digit ZIP Code Boundaries

Pitney Bowes 5 Digit ZIP Code Boundaries provides up-to-date postal code information and the most accurate boundaries available for the US and Puerto Rico.

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Neighborhood Boundaries

Pitney Bowes Neighborhood Boundaries provides a hierarchy of geographic boundaries, names, and other attributes that uniquely define the spatial extent and characteristics of a neighborhood.

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Overview

The developers of a mapping plug-in for a leading CRM system saw that they could better serve millions of users if they incorporated data about a wide range of geographic boundaries. However, the startup company had limited resources for pulling different types of data into its solution. It chose to work with Pitney Bowes® due to the quality and quantity of its data, as well as the ease with which it could integrate diverse datasets into the fledgling solution. The result: The solution has quickly grown to be one of the most popular plug-ins for the CRM system.

Business challenge

For CRM users, visual representations of details about sales territories can support better decision-making. Moreover, map-based data views can help salespeople improve logistical efficiency, for example, in finding the best route for a day’s in-person meetings.

That’s what the plug-in is designed to do. It offers mapping, schedule planning, route optimization, real-time geolocation, territory management and geoanalytics. To ensure all this functionality is based on reliable, up-to-date maps, the plug-in’s developers needed to pull in geospatial and demographic data from a trusted third party. They turned to Pitney Bowes.

The different datasets are easily ingested into the plug-in. Ultimately, that has enabled the company to scale very quickly from startup to proven leader in the CRM mapping space.

   

Solution

In its selection process, the plug-in company considered data quality, first and foremost. Pitney Bowes stood out because its data updates were frequent enough to ensure that the plug-in would always be optimized. The plug-in company also considered data quantity and diversity. The CRM system it serves has a broad global user base, so the plug-in needed to accommodate as many different types of users, within as many different types of organizations, as possible. Scaling up its user base would require it to incorporate many different types of data. But efficiency demanded that all this data should come from a single provider.

The plug-in developer chose to utilize multiple Pitney Bowes datasets. Neighborhood Boundaries, Residential Boundaries, ZIP Code Boundaries, School Boundaries, College Boundaries, Auto Boundaries and Census Boundaries combine to provide a wide assortment of unique boundary shapes on the plug-in’s maps. Other Pitney Bowes datasets offer additional color, providing more than 280 individual data attributes reflecting demographics characteristics for each boundary area, as well as information on crime, walkability and other statistics.

Benefits

In the resulting solution, users simply click on the boundary type of choice (neighborhood, school, etc.) to refine a search based on that data. They can also filter search results based on the Pitney Bowes boundary datasets, or they can view the boundary lines on a map. Finally, they have the option of narrowing their search by layering demographic information into their queries. The solution has become wildly popular with end users and is now one of the largest third-party plug-ins for the global CRM system.

The plug-in company has also derived operational benefits from working with a single vendor for all its boundary and demographic data. It avoids the additional work that would be required to maintain an assortment of different commercial agreements. More importantly, the plug-in provider receives all its diverse data feeds from Pitney Bowes in a standardized format. The different datasets are easily ingested into the plug-in, which minimizes integration work. Ultimately, that has enabled the plug-in company to scale very quickly from startup to proven leader in the CRM mapping marketplace.