The ability to collect and harness big data has transformed businesses worldwide. This process, which is continually improved by data scientists and companies that heavily invest in big data, has allowed for dramatic changes to numerous industries. The benefits of using big data include improved processes, data-driven business decisions, and better resource allocation. Here is the increasing need for hyperlocal data collection.
Hyperlocal data refers to a more niche version of local data. A zip code, for example, is an example of local data, but a street address is hyperlocal data. It’s more specific and tends to surround a very particular, defined geographic area. This data is more difficult to collect, but its uses in business are growing.
There are more obvious uses for hyperlocal data for businesses that rely on Google Maps or location-based services. A food delivery company, for example, would benefit from having more addresses and exact locations of restaurants in a particular area because they can then offer customers more unique choices, gaining an edge over their competition.
Google Maps itself also benefits from this data because the company can offer more accurate, up-to-date information to users, including directions and nearby locations.
Both marketers and advertisers use hyperlocal data to hone in on local customers. Near-me searches have risen in popularity, and marketers are capitalizing on these searches to get customers into local stores and restaurants.
Instead of focusing on a potential customer that may come to the area later, these campaigns focus on customers that are already in the vicinity. Of course, marketers must also focus on strong Google My Business listings and SEO to beat out the competition fighting for the top spots on search engines.
Hyperlocal data has a place in a traditional business or finance setting as well. A company applying for a loan may overstate its value. Hyperlocal data can capture accurate information such as credit cards accepted, hours of operation, number of employees, etc. All of this information is necessary for financial institutions that want an accurate portrayal of a business. However, there are far more uses for hyperlocal data than just this.
With the world battling a pandemic, many have turned to hyperlocal data to track the spread of Covid-19. By mapping out global cases, experts have been attempting to take a worldwide view of how the virus has spread and its impact on businesses.
More importantly, they want to look at areas that have begun to flatten the curve so that other affected areas can mimic their efforts. Of course, none of this is possible without hyperlocal data that tracks infected populations. This data will play a key role in both curbing the spread and creating lessons to draw from in the future.
What is particularly interesting is how hyperlocal data can benefit the Internet of Things. With improved mobile technology, people are constantly creating data. Now, more than ever, people are sharing this data for the benefit of others. Take traffic reports, for example. There are apps where users can report accidents, and delays, which helps others traveling in the vicinity.
The report is given to a GPS application, which can then reroute drivers to avoid sitting in long delays. It’s even expected that self-reporting will soon become unnecessary as AI will become sophisticated enough to collect hyperlocal data without user input.
Connected cars have grown in popularity and will soon play a substantial role in hyperlocal data collection and distribution. Equipped with smart sensors, this type of car could report weather information to a cloud service, which could then alert others in the area.
If there is a severe storm or ice on the road, other travelers would know about it, assuming they are in connected vehicles themselves. Hyperlocal data can power IoT simply by offering larger amounts of accurate data.
The challenge of data collection, particularly in emerging markets, is one hindrance to this movement. While data is readily available in developed cities, data in underdeveloped locations is not as easily accessible. This data, however, is growing in its value as more global companies seek to enter these markets.
There are solutions to this problem of gathering data in underdeveloped markets, and big brands are starting to vie for this data as it directly impacts expansion plans.
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