Consumers nowadays are inundated with offers for products and services, especially when shopping online. It’s very common for a customer to see advertisements for products he or she may have recently searched for, but sometimes the marketing emails and pop-up ads are not necessarily in line with the consumer’s interests and may come across as more intrusive and annoying than actually useful. If driving sales and delivering excellent customer service stem from giving customers an optimal experience, brands need to take a more strategic approach. With big data analytics, companies may analyze a mix of complex data sets from various sources to gain important insights into customer behavior and use such feedback to drive sales and provide better customer service. In what ways does big data impact the customer experience?
One important use of big data analytics is sifting through transactional data, or a customer’s purchase history. Such data may reveal how much a customer has spent, how often, and—most importantly—on which products or services. This kind of data is critical to making marketing offers to customers for future purchases, as well as recommendations based on customer preferences. When the customer is satisfied with a good deal, brand loyalty increases.
Big data further presents an opportunity to personalize and customize the customer experience. For example, financial management and personal banking websites may track a consumer’s spending habits and offer cash rewards or other incentives when customers spend money, while health-management sites or even devices can provide feedback and encouragement for people who are monitoring their diets or tracking their vital signs. Big data therefore offers a chance for companies to connect with their customers by tailoring their products and services to the customer’s needs. This translates into greater sales, greater customer satisfaction, and sustained brand loyalty.
Customer feedback surveys, call transcripts, and most any text produced by the customer in exchange with customer service agents (SMS, social media posts, and chats included) are vital sources of big data which allow for optimized customer engagement. Specifically, big data gleaned from social media activity can provide tremendous insight into customer concerns and lead companies toward identifying and fixing customer service issues. Contact centers may be reorganized to accommodate high demand channels, and managers may train and staff agents to work more on channels that receive the most customer contact (for example, focusing more heavily on Twitter if it proves to be a high demand channel for a certain brand). Companies may also use such analytics to better carry out marketing campaigns on the most in-demand social media sites, catering to customers’ preferences. It is important to know how to manage your customer Datas.
Big data analytics can also show which channels are most frequently used by customers (and which ones need better engagement), thus providing additional opportunity for brands to optimize their omnichannel strategy. As customers are often connected to brands on many channels, it is vital to collect, analyze, and treat all data in order to provide employees with the right tools for understanding so they in turn may provide optimum customer service. By understanding customer behavior, companies may resolve issues more efficiently, as big data will enable representatives to quickly and accurately offer solutions without a need for asking many questions. Big data analytics provides brands with a meaningful approach to understanding consumer behavior, which in turn can lead to greater sales, stronger customer service, and an optimized customer experience.
