Location based analysis in action for retail businesses

Technological changes cannot be foreseen, especially for industries like retail businesses. While once things were slow for them, online stores came into the picture and pushed the envelope on how we perceive the retail sector. With tough competition, there has never been more need for marketing methods and strategies that combine analytical data, like location analysis.

As more businesses make themselves mobile—friendly, it has become easier for companies to create a treasure trove of data where they can observe their consumers’ behavior. For example, companies can gather data about where our consumers live, where they go, what they need, and what are their likes and dislikes. The data collected can be tough to grapple with, but retail location analytics breaks down the data into insights that can be profitable to the retailers. 

What are location analytics?

Location analytics is the process of collecting data and insights from the location/geographic component of business data. All the collected data is laid out in a geographical information system. The insights from the data can be beneficial for businesses as they help understand their audiences based on their geographical location. Through targeted information, they can increase their sales and customer retention capabilities.

In the context of big data and other data models, location analytics can help retailers gain more insights while foreseeing the trends in the marketplace. The demand for location—based analytics keeps increasing as businesses aim to provide their customers with the best experience. It becomes easier when you have data from their earlier preferences. 

Transformations in retail businesses

Analysis and data collection have enabled the retail industry to take a new approach toward their customers. A significant transformation in the industry has to be concerning personalization. All businesses now aim to provide a unique in—person experience to their customer at their store, online or offline.

The three radical changes that have changed the functionality of businesses are:

1. Higher expectations play a vital role in the operation of businesses. Each retailer has to set a new bar in how they offer their products and services to the customer. As a result, the customer’s experience should be far better than what their competitors could provide. This is because customers with higher expectations will shift to another retailer if the experience is not up to the mark.
2. Stores are now operating both online and offline. There is no stringent standard of how the retail business should work. Both online and offline stores have their share of benefits, neither of which makes them better than the other. 
3. Personalized experiences are here to stay. The retailer knows each customer’s preferences, likes, and dislikes based on their purchase history. This enables them to offer services that appeal to their mindset. 

What challenges in retail businesses does location analytics address?

Location analytics uses the power of highly accurate location—based data to unlock previously—stored insights. It works by realizing that location can be a common denominator in the vast pool of business information. As a result, the data can help retailers address their most significant challenges and other roadblocks using the right analytical tools.

• Improve Return on Investment (ROI)

Retailers constantly need to invest in their products, services, and customers to remain at the top of their game. In times of economic difficulties, it is crucial to make suitable investments. Location analytics can help retailers know where and how to invest by testing investment plans, thereby reducing risks after implementation.

• Increase sales

The changing or reduced patterns in customer spending make it difficult for retailers where their sales will come from. Location analytics can help businesses understand the psychology of their customers, especially their preferred products and services. In addition, the analyzed data can help in building marketing strategies that effectively target specific customers.

• Control costs

Retailers need to be aware of all the ways through which they can protect their profits. Cost analysis throughout the company isn’t enough, but location—based analysis can bring confidential data to light. A centralized location—based analytics system helps in:

• Get more details of costs and expenditures at various levels of the organization. For example, you can get in—depth information about the financial status in manufacturing information, logistics data, supply chain, and other records. 
• Data can help you flag issues before they become a costly affair. Retailers can set benchmarks to measure and control stringently going forward. 

 

• Boost customer satisfaction

Keeping customers happy is the primary objective of any retailer. Despite the budget, the customer experience keeps customers returning to a retailer even after a competitor provides better services. In addition, data analytics can help understand existing issues in the system and determine methods to tackle them.

• Enhance customer loyalty

On the monetary side, it is easier to keep existing customers than sourcing new ones. This is why customer loyalty is on the top agenda for retailers. For this, customer segmentation is effective and is why location—based analytics is popular today. 

Where can location-based analytics be applied to retail businesses?

The five top use cases for applying location intelligence in the retail industry are:

• Retail site selection

The advancement in location—based intelligence has helped the retail industry to develop in the previous decade. The earlier analysis could be done by physically surveilling a place for days and months and collecting the needed data. For example, counting the number of visitors during certain hours, the cars in the parking lot, and the number of carts coming in and out of the store for needed data.

With advanced location intelligence data, retailers can create dynamic map visualizations that determine the population and demographic groupings. Additionally, by adding the competitors’ locations in the mix, one can get an idea about the potential profitably of a specific site. Demographics can help in creating the best experiences for the target audience.

• Better merchandising

Retailers can use location—based analytical data to serve the customer better in an area. For example, retailers can get an idea about the people living near their store and provide products that connect with their needs. Additionally, retailers can advertise their products in publications and media outlets catering to the same audience.

For example, if a grocery owner learns that many Indians live nearby, it is an excellent opportunity to get food items that Indians are familiar with. Advertising on media outlets and posting updates on social media can make the information pass on to the target audience at hand.

• Targeted advertising

Location—based advertising is another opportunity for retailers to increase their revenue. A food outlet store that provides free delivery can advertise to people who have busy schedules and hardly have time to visit the store or to senior citizens and physically challenged people who cannot travel to the store. It can be presented as a push notification to their mobile phone and delivered through a third—party application installed on the mobile device.

• Customer experience

Location analytics helps retailers to link their customer’s online experience with their brick—and—mortar stores. Connecting website visits and browsing history to the person’s physical presence at the store, retailers can understand the spending habits and needs of the person. It also helps link incomplete or fragmented data like the email address by associating it with the digital marketing activities of the customer.

• Performance management

Retailers can use location—based data to set performance benchmarks for individual stores in specific areas. Setting targets for the fiscal year becomes easier once the last year’s performance is taken into hindsight. Furthermore, with location intelligence, retailers get a clearer view of each location’s true profit—making potential. 

Leveraging location analysis in the retail industry

The factor that restrained location analysis from being applied in the global retail industry was the computational power required to make data work in real-time. But as more companies adopt more analytical tools, it has become affordable for businesses of all shapes and sizes. As a result, accepting location intelligence is the most promising way for retailers to enhance customer engagement and increase overall sales. 

By B Naomi Grace