What is location intelligence?
Location intelligence combines business data with spatial data to communicate a correlation between the location of people, transactions, and assets. Although many businesses analyze their own data, few are looking at it from the perspective of how location data and spatial analytics can improve their business insights and analytical workflows.
How is it important for business?
Location analytics uses important metrics and key performance indicators to provide accurate insight into how business is performing. Combining the appropriate data (e.g. retail sales) with location information (e.g. addresses, postal codes) can result in visualization methods such as heat mapping to identify hotspots at a moment in time and provide tangible insights while simply looking at spreadsheets and tables may not. Are you overspending or underspending in a certain geographic area? Common today, interactive real-time maps are used to identify correlations and patterns between the data at various geographic lenses from a national view all the way down to trade areas surrounding a store or service location.
Where are your customers?
We live for optimizing the customer journey. Part of building that customer relationship and loyalty includes personalized products, offers, and services. Locational analytics provides a way to help serve your customers better whether it’s exceeding their expectations or delivering what was promised. Connecting customer location data to your workflows creates the ability to identify where they are and how they’re accessing your product or service, which can help you to isolate and resolve customer service issues across a geographic area.
What are some use cases for location intelligence?
Location analytics can be used in many industries, so finding how it can fit into a project is important. In your organization, you may want to research how to acquire location data, consider forming data privacy guidelines, and determine skill level required to integrate location data into existing business data. Here are some possible use cases that may give you some ideas:
- Insurance: Geocoding household location data can proactively assess whether a property is designated in a flood zone or earthquake fault line. The difference could have high-cost implications if done improperly. Having customer-facing interactive maps where potential or existing customers could check themselves can also provide a sense of transparency to insurance costs.
- Financial Services: Fraud detection based on a customer’s banking behaviour can be enriched using geo-intelligence. Did a customer make an ATM withdrawal at one location and suddenly have their account accessed at a different one? This can be done by creating customer profiles and understanding transaction behaviour, areas of variable risk, and determining the geography between transactions.
- Retail: Properly understand a retail store’s potential trade area by looking at factors such as the household income, share of wallet, neighbourhood census, and travel times. This could determine whether a location will continue to grow business and capture future customers or justify spend on marketing to an expanded footprint to ensure potential new customers are targeted.
- Customer Experience: Using accurate location data, organizations can improve customer experience by providing next-level targeted offers to proactively meet or exceed customer needs. For example, special offers that are only sent to customer mobile phones within a geofence or targeted service improvements when at a large venue like a sports event or concert.
- Public Sector: Many public organizations already rely on location analytics to deploy services for emergency situations, social services, or public safety. This can improve the allocation of resources and combat inefficiencies and save public tax dollars.
- Logistics: Delivery services are very popular with customers. Whether it’s a package of office supplies or a hot meal, businesses are using location data to provide more transparency to customers on when to expect delivery. Higher customer expectations today means optimizing these types of business processes add plenty of value.
What’s needed to develop a location intelligence strategy?
Data. Lots of it. Organizations need to properly collect, access, and prepare business data to be used with location data. The first step is to determine a geographic focus of entities the business wants to analyze (by postal codes, by latitude/longitude, by customer addresses). Prepare business data in a form that will be compatible with external data sources like census data, market research data, consumer spending and integrate the data for analysis. We recommend organizations collect as much relevant data as possible over a period of time to find a movement or discover patterns of customers and assets which will help reveal efficiency and performance. As location data could include personally identifiable information, it is recommended to have data privacy and protection policies in place.
If you have a business challenge involving location information, please contact us at email@example.com.
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