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Data analytics makes retail better

June 2, 2015

Businesses are required to tailor their sales plans and marketing campaigns to suit the needs of customers. 

Today’s retail environment is very different from the one we had 20 years ago. Consumers are more sophisticated and have more specific preferences, and accordingly, businesses are required to tailor their sales plans and marketing campaigns to suit those needs. One of the best ways you can improve your operational strategy is to employ the power of data analytics. However, before you can use data to reach customers better and sell more, you have to collect it. Point of sale systems and loyalty cards are excellent ways to do this.

Collect data and then make actionable goals
Consumers today do not only buy products in brick-and-mortar stores and they don’t just “go shopping” anymore.  People like to explore their options and do their research before they buy. A quick look online will tell a customer all about a particular product or service they are interested in as well as give them an idea about pricing. Kirthi Kalyanam, director of the Retail Management Institute at Santa Clara University, told AdExchanger that retailers and merchants are required to collect data across multiple channels in order to paint a complete picture of customer buying patterns and originate marketing strategies.

“As the customers shop across channels, CMOs need to optimize their ad spending to reflect cross-channel advertising impact,” Kalyanam told AdExchanger. “This is a very complex undertaking since there are different data sources and norms across different channels.”

“Many people do research on their mobile device while they are actually in the store.”

It is important to point out that data is not just useful for creating marketing strategies. It also helps companies gain a better understanding of which products sell better than others, effects of seasonality and other factors that are important to know when writing business plans.

Data must be collected in-store as well as online
Because consumers are likely to research products before they buy, they will go online, or go to stores and check out items they are potentially interested in. Interestingly, many people do research on their mobile device while they are actually in the store. In order to collect relevant data about customer behavior, a company must employ flexible strategies. FourthSource explained that online sales are not the only way a company can understand customer behavior. Implementing WiFi analytics in-store is another way to collect customer information and gain a better understanding of what day-to-day operations call for.

POS systems help retailers collect valuable information. Retailers should work to understand customer buying patterns.

Modern in-store analytics technologies use a store’s existing WiFi infrastructure to capture how and when customers behave at your store. Looking at this information goes a step beyond simply looking at bestsellers and favorite colors – it factors the time spent in each aisle or department as well as how much time is spent at the register. Wi-Fi analytics is praised for its cost-effectiveness and ability to provide accurate data. FourthSource likened it to Google Analytics for the physical store.

Don’t forget the basics of retail data analytics
VentureBeat mentioned that data analytics essentially helps companies find out what they don’t know. Sometimes, the basic questions need to be answered. Questions like: Which products to customers like best? What is the average age of our customers? Which technology products are customers using currently? By factoring this type of information, businesses can begin to come up with predictive models and create better strategies going forward.

There is also an area where data analytics and marketing overlap – customer loyalty. Using rewards programs, you can foster loyalty at your company, send promotional material to interested parties and enjoy the benefit of having your customers directly provide you with information regarding their buying patterns. Understanding customer experiences at this level means you can offer more meaningful suggestions as well as recommend products they are likely to buy from you. 

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