The great news is that analytical capabilities previously limited to larger companies with deep pockets are now available to a broader range of organizations. Plus, even larger companies are benefiting from new SaaS and cloud-based technologies that allow easier access to data often locked in legacy systems. More and more companies can therefore take a proactive approach to their decision making, an approach based on facts, vs the reactive approaches of the past.

Police report

Take law enforcement. When SpatialKey first launched, we immediately received interest from police departments looking into better approaches to crime fighting. Most already used sophisticated RMS or CompStat data systems, yet those systems did not take into account data from other systems or outside sources. For example gang data might be in one database, crime incidents in RMS, and offender information in a spreadsheet with no easy way to pull the information together to make better policing decisions. What they saw in SpatialKey was a way to get a better ROI on their investments by adding new dimensions to their data analysis capabilities.

With SpatialKey, a commander for example can bring in data from multiple sources and start looking for patterns: there are a string of robberies happening in a neighborhood- how can we curtail these? Who are the parolees or known offenders living within x miles of that area? Is there a specific time of the day that these crimes occur? In the police world, they call this Intelligence-led policing- the ability to leverage intelligence to guide crime fighting decisions. So if the commander sees a pattern in the time when crimes occur, increasing the number of patrol cars in the neighborhood at that time is a fact-based approach that hopefully will generate faster/cheaper results. And all it took was a couple minutes of analysis with SpatialKey vs randomly patrolling the area.

Well data is data is data. What we’ve seen in the past year is that a Sales VPs’ data analysis needs are actually not that different from a police chief’s (or any other decision maker for that matter). At the end of the day, what’s important for organizations is to find ways to pull together information critical to decision making and make it available to the people who need to actually make those decisions. So for one parolees, crime logs, or calls for service are key data points to look into to make fact-based decisions, for the other it might be sales leads, product sales, customer calls or customer demographics. And of course the types of data SpatialKey clients need to analyze is as varied as their industries.

The common thread we’ve found amongst all of our clients is that although they already have data analysis capabilities (most already use some form of BI or GIS system), those systems do not provide them the ad-hoc, “get the answer now” data analysis needs the addition of SpatialKey provides.

So although a Sales VP might be using Salesforce as a great CRM tool, there is no easy way to tie the salesforce data to other internal or external data sources to make better decisions to maximize sales opportunities. By incorporating SpatialKey with Salesforce, he/she can now bring in demographic information or competitive data into the picture. Are there patterns, geographic or otherwise, that can help guide sales staff deployment or lead closing activities? Is there a correlation between deal size and marketing activities? What works best to close leads in this geography vs the other?

In a fast-paced world when we all need an answer yesterday, the benefit they see in SpatialKey is that not only can they leverage knowledge they never had before, but they also don’t need to wait on data analysis gurus to get answers. They can do that analysis themselves- on the fly. Many actually use SpatialKey in meetings so that “what if” questions can be answered immediately. Maybe we should call this Intelligence-led sales…..

Please visit spatialkey.com for more information. We also offer a free trial if you want to take a spin of the app with your own data.

Analyzing conflicts via maps is not new. For centuries generals and politicians have moved pushpins on maps to help guide troop movements, understand enemy positions, or help avert conflict altogether. What’s new to conflict and crisis mapping are the tools now allowing military, politicians, and humanitarian groups better understand what drives political instability and violent conflict, and better address it.

One of the more rewarding uses of SpatialKey has been driven by a team led by Dr Clionadh Raleigh. Dr Raleigh and team members from the PRIO Center for the Study of Civil War created the ACLED (Armed Conflict Location and Event Data) database. The ACLED project team’s objective was to provide a better read of conflicts by understanding the relationships between combatants, social groups, economies, and even natural phenomena such as droughts or floods. Ultimately their goal is to achieve a more stable, just, and peaceful world.

Crisis mapping

Thanks in part to funding from the World Bank, ACLED provides up-to-date, immediately accessible analytics and maps for over 50 countries in the developing world to help academics, the World Bank, NGOs, aid agencies and more gain insights on civil war dynamics. The database includes for example the date and location of conflict events, event types, rebel and other groups involved, as well as specifics on battles, killings, riots, and recruitment activities by rebels, governments, militias, armed groups, protesters and civilians, and much more.

The difficulty of creating a central database for crisis mapping is that it needs to bring together vast amounts of diverse information coming from a wide variety of sources. In technical terms: a data mess. Since neither Dr Raleigh nor the users of the ACLED database are trained GIS (Geographic Information System) professionals, they decided to use SpatialKey to centralize and analyze the data. SpatialKey is web-based and does not require special training or programming. All users need is an internet connection to immediately create highly visual maps and reports.

The benefit of using SpatialKey is that each agency using ACLED data can now create maps to help answer totally different questions, no data specialists required. Some groups need to better understand how to mitigate conflict in a specific area, others want to find the safest zone to place a refugee camp, and yet others want to understand the impact of possible floods and droughts on a conflict so they can arrange their resources accordingly.

This has allowed researchers to analyze data with more precision, as well as create a more collaborative environment to help the researcher community create predictive models of civil war. It has also helped challenge assumptions. For example Dr Raleigh says that many people considered civil wars to be primarily rural events, but SpatialKey has showed that these conflicts tend to happen close to larger cities, as rebel groups attempt to engage with the military. She considers that the combination of ACLED and SpatialKey goes a long way toward advancing the field- it provides the next generation in conflict analysis and crisis mapping.

If you cannot attend Doug’s session, please read our case study on the use of SpatialKey by ACLED.

For more information on SpatialKey, or to start your free trial, please go to spatialkey.com.

SpatialKey as a visual dashboard is a great example to highlight since it’s commonly used by our clients- but since our clients don’t really want to share their company data with the world for us to use in demos, we thought we’d use ours! Of course, we changed employee names and client revenues for this video since we don’t want to reveal our secrets either.

As a background, Universal Mind, SpatialKey’s parent company, is a leader in the field of Rich Internet Applications (RIA) development using next generation Web 2.0 technologies. The company is comprised of employees, as well as a network of consultants, all spread throughout the US. Clients include companies as diverse as Adobe, Cisco, Behr, CVS, Ben&Jerry’s, Visa, Children’s Hospital Boston, Verizon and many more. Dispersed teams often don’t get the big picture of how their work fits within the broader company or how they are performing compared to others. For Universal Mind, SpatialKey has helped bridge that gap.

Tom’s presentation focused on sales activities and sales performance. How did we do last year? How did we grow geographically? Which clients generated the most aggregated revenue? What trends do we see for the year ahead? Are there any location trends we should capitalize on? Who were our top performing sales reps? Is there a correlation between the location of our reps and the success of our sales activities? Which consultants generated the most billable hours? Where are they located? What revenue did they generate across clients?

See the video above for a small example of the many visualizations and analysis capabilities SpatialKey offers for sales data. Notice how quickly Tom gets answers to any question he asks about the companies’ sales activities. Universal Mind uses Salesforce to track and manage its sales pipeline, so the data you see highlighted comes from a direct import from Salesforce, but any CSV-type data would work just as well.

If you are interested in finding out more or need help setting up your free trial, do not hesitate to contact us.

We’ll compare a zip-code thematic map with a heatmap. Both maps show average home sale price by geographic area (either zip codes or clusters of points). The image below shows the two map types side by side.

Now we’ll step through an analysis of these different map types to see why they produce different views of the same data.

Thematic map by zip code

First, let’s take a look at mapping home sales in Sacramento by zip code. The map below shows thematic zip codes colored by the average sale price. You can see the highest range is $400,000 and up and includes 3 zip codes in the image below. I want to focus on comparing the two labeled zip codes, 95818 and 95822. You can see that the 95822 zip code area has a much lower average sale price than 95818, which is immediately north of it.

Density heatmap with zip-code boundaries

However, if we switch to a density heatmap we see a different picture. Switching from thematic zip codes to a density map takes literally 3 clicks in SpatialKey. The map below shows average sale price as a density map, with the boundaries of the zip codes overlaid in red. This is the exact same data showing the exact same attribute (home sales showing average sale price). But if you compare this image with the thematic map above you’ll notice that the hotspots tell a different story. A fluid area that overlaps both the zip codes we looked at above is actually the area with the high average prices. That area doesn’t cleanly fall into a single zip code.

This isn’t too shocking, since it intuitively makes sense that fairly arbitrary boundaries like zip codes wouldn’t directly map to more or less expensive areas of town. But it illustrates the difficulty of rendering your data thematically by certain shapes, like zip codes or counties.

Density heatmap with neighborhood boundaries

To further analyze the dataset I decided to load in the boundaries of the neighborhoods in Sacramento (the file was downloaded here). Now we see boundaries that come much closer to matching the home prices. Intuitively this also makes sense; if you think about home prices in your city you’ll likely think of expensive and cheap neighborhoods, not zip codes.

Everything has its place

Both thematic maps and density maps are useful when exploring geographic data. Both show you important aspects of your data, but it’s important to keep in mind the inherent limitations of the different methods. With SpatialKey, we provide you with the tools to easily switch back and forth between these rendering methods in seconds.

Try it out for yourself

You can start uploading your own data and making thematic maps right away by signing up for the 30-day trial of SpatialKey.

Photo courtesy of CNN and Google maps.

On the business side, 80% of business data has a location component which provides a goldmine of untapped information for marketing, sales and operations. But current visual mapping and analysis tools are expensive, can only be accessed by trained specialists, and require heavy IT involvement to set up and maintain. This is a big barrier to entry for most businesses. They want to “see”, understand and communicate data trends, but don’t have the time nor means to invest in yet another expensive infrastructure.

The businesses that already do leverage visual mapping and analysis can more effectively and more quickly see geographic or time-based data and trends critical to sales and operations. This provides them a real competitive advantage. Many oil and gas companies for example have invested in sophisticated Geographic Information Systems (GIS) and brought in GIS specialists to gain insight on their location intelligence via visual maps. This allows them not only to plot areas with the highest potential to drill in, but also better manage their pipelines, operations, retail facilities, and more.

…. or….    . …and…            … and..     

Thankfully, a revolution is taking place that allows “regular” business users -with no GIS training nor deep pockets-  to leverage the power of visual mapping and analysis. Enter Software as a Service (SaaS). SaaS is transforming mapping and data visualization in the business world the same way Google Maps revolutionized mapping for consumers. Using cost-effective, user friendly SaaS mapping and analysis applications, such as SpatialKey, organizations of all types and sizes can now import their business data, combine it with geographic or competitive information, and start visually analyzing trends critical to their business. Where are key customers located? How can they maximize results in their sales territories? How best to map their sales territories? Where should they open a new retail outlet? How does Q2 sales compare to Q1 on a geographic basis? What marketing campaign resulted in the highest ROI? And so much more.

Opportunities and threats previously hidden within row and column-based datasets are now clearly visible via interactive maps. Concepts difficult to explain in text or PowerPoint presentations can now also be shown and therefore easily understood resulting in better decision making. What’s more, since everyday decision makers can use these applications, “what if” questions can be answered on the fly versus having to wait for an analyst to do a new data query. Decision-making, communication, and collaboration are improved. After all, seeing is understanding and believing, even in the business world.

Note: we’ll be adding blog posts around visual mapping for sales and marketing users over the next few weeks. In the meantime you can find out more at our sales and marketing and/or enterprise solutions pages.

Map of all Saturn dealerships

View the interactive report in SpatialKey

Fortunately for Saturn owners, all of these locations are near GM dealerships.

The app was created as part of Intuit’s Workplace contest, and we’re proud to announce that it was chosen as the winner. This is the first non-preview release of the SpatialKey system, and we prepared a few videos to help you get started. The first shows all the steps necessary to sign up for the SpatialKey app and launch your data.

The other videos (which introduce the Data Exploration and Charting Dashboard Builder visualization templates) can be seen on our landing page for the Intuit app. For more information on SpatialKey and the Intuit Partner Platform, see these articles:

• Slick data-visualizer launched for QuickBooks users (CNet)
• Intuit Workplace Analyzes SMB (PCMag)
• SpatialKey Mashes Up QuickBooks Customer Data (Programmable Web)
• Universal Mind Wins Intuit WorkPlace Application Contest (Intuit)

…it’s a combination map of satellite images, street map, and my geographically assigned patrol beat map in layers. The company has made it so user friendly that I can literally research and plot over 400,000 calls for service in the last 5 years in about 30 seconds. The system is web based so quickly analyzing What-Ifs can be accomplished anytime, anywhere…

Chief Greiner further highlights the ease-of-use of SpatialKey and its appeal to younger officers:

At the end of the day I want to give each of my officers the ability to do What-Ifs from home. My newest officers are gamers raised in a world of video games. I want this to become their new game of choice in helping solve crimes and arrest suspects more quickly. OPD [Ogden Police Department] officers work the same area for a year and this gives them a tool for their area to use during their un-committed time.

With SpatialKey, our goal is to put powerful visualization and reporting tools into the hands of those who need them most: the decision-makers. We continue to work with the Ogden PD and other departments to test our tools, implement their feedback, and ensure that they are able to make best use of their geotemporal data.

The article — about the use of browser-based visualizations and analytical dashboards for business intelligence — features an interview with Chief Jon Greiner of the Ogden Police Department in Utah. Ogden is the first police department in the country to implement the enterprise version of the SpatialKey Law Enforcement Dashboard:

Today, the officers are using the new BI tools to perform geographic profiling of crimes and analysis of police data “in seconds,” he says. Before, it could take days for the department’s single crime analyst to fulfill a report request. An added bonus is that experienced police officers with extensive street experience are now able to apply their firsthand knowledge to crime analysis.

It’s great to see our crime mapping tools featured in an article aimed at the broader business intelligence and IT fields, especially as we expand the focus of our tools with the SpatialKey Technology Preview and SpatialKey Personal.

The standard cartographic approach to symbolizing point data with attributes attached is the proportional symbol map.  Such maps, which are one of the three symbolization methods currently offered in SpatialKey, use symbols (typically circles) scaled proportional to point values.

Offering multiple symbolization options — each available at all times and map scales — allows users to switch to a more appropriate rendering for their dataset and switch back-and-forth to see their data in new ways.  In addition to the proportional symbols shown above, our templates currently offer two raster-based aggregated renderings: the heat grid and heat map.

In the above screenshots, the colored heat grid and heat map represent the density of Wal-Mart stores. In this case, store locations are aggregated to an arbitrary, scale-dependent grid. Thus, the brightest grid squares (and the hottest areas on the continuous heatmap representation) represent the areas of highest Wal-Mart concentration.

These renderings can also be used to show attributes of point data, in which case the hottest/brightest areas represent the areas with the highest average or total value for a given attribute. And of course mousing over the map reveals tooltips with exact values for these “quadrats” (screenshot below shows Sacramento home sales data).

The heatmap symbolization is newer, less vetted by the cartographic community, and perhaps less straightforward than the proportional symbol and heat grid renderings. But with the proper user interface, and in concert with other available renderings, we believe heatmaps can help facilitate effective visualization of geotemporal data.

We are particularly interested in feedback on the use of the heatmap symbology for mapping attributes of data (like home prices). We are excited to add additional symbolization options to our templates, as well as improvements to existing renderings, as we continue to develop the SpatialKey visualization system.