Location analytics groups device-location signals to estimate how people move through places such as shops, streets or event sites. Marketers use the resulting patterns to study catchment areas and visits, subject to consent and data-quality limits.
Retailers use location analytics to study where store visitors come from, how often devices return and how movement differs between places. These patterns can support decisions about catchment areas, opening hours and local campaigns.
For a business to provide products and services that add value to its consumers’ lives, it needs to know what its customers want and how they want it. Consumer analytics help bridge this gap by providing marketers with valuable insights into how consumers are thinking and what they respond to. Location analytics, in particular, can help provide in-depth information on various consumer behaviors and help brands build loyalty and drive conversions.
When used in combination with other operational and customer analytics obtained from other sources, location intelligence can help businesses be more efficient and enhance customer experience like never before.
Excelling at delivery and pick up
Consumers aren’t just shopping in stores now. Home delivery, click and collect, and online purchases are different shopping options that consumers are turning to save time and keep up with a fast-paced lifestyle. A positive delivery experience makes it more likely for a consumer to return for another purchase. Additionally, longer delivery times and expensive shipping options are two of the most common reasons for cart abandonment.
Given this, businesses need to present accurate delivery information on their website to ensure consumers don’t leave in the middle of the shopping process. This information can only be correct when businesses have real-time location knowledge about where clusters of customers are located, where they go, and the route they’ll follow to reach their destination.
Location intelligence, thereby, helps businesses streamline their operations and perform accurate and fast deliveries, helping them remain competitive. By cutting delivery times, logistic companies can increase the volume of deliveries and improve the fulfilment times of e-commerce businesses.
Offline visits
While online sales are quickly becoming the primary source of sales for many businesses, many shopping processes begin in retail stores as customers check out products in person before they buy it online. Hence, businesses can use location intelligence by tracking the number of visits and sales taking place in retail stores and how many visits are online pickups.
By keeping track of the customer journey for each store, visit can help bridge the gap between online and offline shopping by providing valuable insight.
Better customer profiles
Location analytics gives way to more enhanced customer profiling. Geographical information serves as a commonality for other kinds of customer information, such as what customers buy, where they buy it from, and where they live. It also links together customer complaint information, point of sale information, and online activity. By using different kinds of information in conjunction with each other, businesses can build more comprehensive customer profiles for a more targeted approach.
Building more detailed profiles helps businesses initiate more customer-specific strategies. Businesses can create shopper profiles based on their own data analytics and analyse the effectiveness of their current strategies and model certain improvements.
Conclusion
Location analytics is increasingly becoming a fundamental factor that dictates business operations. It serves as a key enabler that provides marketers with real insights on their target audience. Analyzing such insights can businesses build their intelligence and provide them with a more in-depth understanding of their consumers.
At the same time, it could potentially lead to privacy concerns as more information about customers become public. It would be interesting to see to what extent businesses can use location intelligence to understand mobile shopping behavior and to what extent consumers would let them do so.
Location data can improve geographic planning when analysts document the source and limits of each signal. Teams should report an estimated visit as an estimate, protect user privacy and avoid claiming that device presence proves a purchase.
A location signal does not explain a purchase
A device near a store may belong to an employee, passer-by or shared household device. Analysts should document how they define a visit, remove repeated or impossible movements and report uncertainty. Location patterns become more useful when teams compare them with store operations and sales data without trying to identify individual shoppers.
