Geospatial analytics: Uncovering insights not found in charts and tables
Summer is almost here, and you may be planning a trip to Disney World or another entertainment venue over the next few months with your family. As you walk through the park your senses will be bombarded with rides and costumed characters, multiple vendors, shops and restaurants. How much money will you spend while checking out the various attractions? More importantly, how much would you spend given the right circumstances? Will you buy ice cream, a hamburger, a souvenir T-shirt or cap—or all of the above? Will you shell out extra cash for add-ons such as musical performances or dining at premium restaurants?
Now imagine that the theme park has historic information on you and your purchasing behavior from previous visits—information like whether you shook Mickey’s hand or the venues you ate at during your visit. The marketing team can use predictive analytics to predict what you are likely to buy, what offers you are likely to respond to and which items you are likely to purchase together. With this information, the park is equipped to make sound business decisions. The information is compelling, but is there a way in which predictive analytics can deliver even more insight?
To add a little more color to the story, suppose you’re near a kiosk or special attraction and you have downloaded a location-aware app on your mobile phone. The theme park has your profile stored in its database and can send a promotional message to your phone. A mesh of spatial sensors throughout the park can detect which attractions are closest to you. How can the park analyze you, your location and the items for sale at a kiosk, store or restaurant in such a way that an employee can receive information on what to offer you and when?
This kind of scenario is where geospatial analytics come into play. Geospatial data can provide answers and insights not found in charts or tables, and it can be instrumental in helping organizations answer critical questions:
- What are customers buying, and where are they buying it?
- What infectious diseases are on the rise?
- Where are high unemployment or crime rates?
- Who are your competitors, and where are they located?
Geospatial analytics can improve predictive insights by accounting for both time and space in predictive models, enabling highly accurate forecasts of events at a specific location for any future point in time. This accuracy helps to see patterns and trends in a familiar geographic context. As a result, these insights are easy to understand and respond to, effortless to prepare for changing spatial conditions or location-based events, and straightforward to develop targeted solutions for business challenges that may require different responses in different locations. Geospatial analysis is useful in many business functions, from marketing to operations, and has applications in just about any industry, even in our amusement park example.
If you’re still wondering how geospatial analytics can benefit your organization, consider other common use cases:
- Financial services firms can use the geographic location of suspicious transactions to spot potential credit card fraud.
- Government agencies can detect fraud in social programs such as Medicare.
- Insurers can incorporate geospatial insights into their underwriting process to determine which customers are at higher risk of floods, hurricanes or earthquakes.
- Law enforcement agencies can study past geospatial data to see crime hot spots and use that insight to predict and prevent future crimes in those areas.
- Retailers can strategically plan for store expansion by understanding areas in which the supply of product is predicted to be lower than the demand.
To learn more about geospatial analytics and other advanced techniques available with IBM SPSS software, join our IBM big data analytics experts for a 30-minute discussion on how the right analytical techniques can broaden analytics infrastructure. You’ll learn how predictive analytics can help you expand both the sources and the quantity of the data you analyze, create more accurate predictions and deliver the insights your business strategy requires. Register for the webinar today.