Tactics to Gain more from Customer Data

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“By leveraging customer and consumer data, retailers can make personalized recommendations, inform shoppers of special offers, and promotions that are most relevant to them and fully maximize cross-sell and up-sell opportunities to realize increased revenues,” – Scott DeLancey

Information and knowledge permeates every aspect of the natural world. We can decipher significant levels of information by observing the daily rhythms of the natural processes, the biological world, the physics and chemistry that animates our natural environment, etc. Information and data also drives the modern state of human civilization. Commerce, the Internet, and consumer markets are heavily dependent on the generation and assessment of market information. The interactions between commerce and consumers are generating incrementally higher volumes of data. Therefore, brands and businesses should work to gain more from customer data in a bid to evaluate market conditions and react accordingly. We will examine some of the techniques in the paragraphs below.

Data generated from the various formats of modern loyalty programs can help businesses to spark innovation and drive growth. For instance, a video game manufacturer can accumulate data pertaining to individual customer interests from its business interactions. Most modern commercial operators drive such programs in a bid to read contemporary consumer trends. The said manufacturer can request each customer to offer feedback in the interests of developing a better product. The generated data can help the business to customize the shopping experience for each customer. The business can also evaluate such information to provide bespoke recommendations that suits the taste and preferences of each customer. This instance clearly underlines the processes through which businesses can gain more from customer data.

Traditional brick-and-mortar businesses can leverage customer data to design more efficient store layouts for their visitors and customers. Market research indicates that customers are attracted to large format stores that feature a fragrance counter near store entrances. This information has been widely leveraged in designing the layouts of modern large format stores. In a similar vein, customers from a particular geography may prefer certain classes of merchandise at the expense of other goods. This information can help retail stores to feature appropriate products in store displays and in key locations inside the store. These instances spotlight the fact that businesses can gain more from customer data in the modern world.

Customer surveys driven by social media campaigns can help businesses to gain more from customer data. This technique draws its efficacy from the fact that most customers in the civilized world are highly active in multiple social media platforms. This cost-efficient technique enables brands and businesses to reach a very large number of potential customers through the Internet. The data generated by such online surveys enables businesses to gain a flavor of customer preferences and adjust their business strategies for maximum mileage. For instance, a confectionary maker that is contemplating a new product line can use this tactic to assess customer preferences. A majority of those polled may vote for a certain flavor or color of confectionary products. In response, the said business can appropriately calibrate its new product developments. This action assures the confectionary maker of a favorable market response to its new product line.

Electronic cookies and the content of search engine result pages empower commercial operators to ‘read’ the browsing habits and online shopping preferences of modern consumers. Businesses that seek to gain more from customer data can deploy web analytics (and similar technologies) in a bid to generate insights into customers’ online habits. For instance, an online business enterprise can use consumer analytics to track the most popular items sold on its app and flagship website. This information is useful because it indicates contemporary shopping behavior and future shopping trends. Consequently, the business may choose to stock heavy volumes of its most popular products in a bid to cater to market demand. In addition, the business can use such information to offer variations of such products and even create custom recommendations for individual shoppers. This technique spotlights a useful method through which businesses can gain more from customer data.

Brands and businesses can use artificial intelligence and ‘number crunching’ technologies to create roadmaps into the future. This tactic is critical because it enables a business to reduce business risks and optimize the utilization of business resources. For instance, a commercial banking entity can apply analytics to customer data in a bid to reduce banking fraud, forecast credit demand, and reduce customer churn. Groups and departments within the entity can use the generated information to spotlight risky accounts, recommend adequate risk reduction measures, and to boost business profits. We note that these actions essentially originate in the analysis of customer data in its many forms. This tactic can be refined to help businesses across industries to gain more from customer data.

High value customers represent significant business opportunities for every business operator. Therefore, commercial operators are advised to pay special attention to this customer segment. This recommendation hinges on the fact that a high value customer is more likely to contribute heavily to business bottom lines. For instance, a manufacturer of industrial parts must collect information on the spending patterns of its high value customers. This exercise may indicate that such customers typically value the business advice proffered by distributors. The data may also reveal that other forms of marketing gain low traction when such customers navigate options to arrive at a purchase decision. In response to such findings, the said manufacturer must fine tune its marketing pitch and pitch collaborative efforts with distributors in a bid to influence its high value customers. This tactic amply demonstrates that businesses should devote their energies to gain more from customer data.

Product personalization helps consumer businesses to discover new customer segments and to cater to existing customers. A cookies and biscuits manufacturer, for instance, may discover that pre-teens often influence purchase choices when a family shops for said products. This information is critical because it enables said manufacturer to gain a ‘handle’ on a huge customer segment. Subsequently, the manufacturer may elect to offer children’s gifts when customers buy a certain number of its cookies and biscuits. This instance illuminates a business decision premised on action designed to help a business gain more from customer data.

Transaction histories are an important source of customer data. Modern businesses often use CRM systems to track the transactions of individual customers. E-commerce operators collect transaction histories from various data points delivered from customers’ online shopping carts. The collected information helps a business to forecast customer behavior. We note that past purchases are a reliable indicator of a customer’s tastes, requirements, and preferences. Therefore, such data can be utilized to personalize product suggestions and recommendations. In addition, transaction histories enable a business to incentivize customers through special offers and bonus discounts. The information also enables a business to create a profile of each customer with a view to step up customer engagement. The use of transaction histories thus helps businesses to gain more from customer data.

In the preceding paragraphs, we have examined some of the tactics that enable businesses to calibrate their marketing and development efforts in tune with customer data. A combination of these tactics will likely empower businesses to expand their market share and pull ahead of the commercial competition.

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