Using Big Data Analytics to Better Understand Customers

<span id="hs_cos_wrapper_name" class="hs_cos_wrapper hs_cos_wrapper_meta_field hs_cos_wrapper_type_text" style="" data-hs-cos-general-type="meta_field" data-hs-cos-type="text" >Using Big Data Analytics to Better Understand Customers</span>

Oct 11

Oct 11

Big Data

big_data_analytics-1.jpgOffering superior customer service and satisfaction is what separates you from your competition. Therefore, learning more about your customers—what they like, what they don’t like and why they prefer doing business with you—gives you a competitive edge. If you can crack the code on what makes your customers tick, you can increase sales with current customers and use that same insight to attract new business. That’s one of the reasons big data analytics has become so valuable to businesses of all sizes in all industries.

Customer experience (CX) management is one of the latest disciplines gaining ground in customer-centric industries such as retail. The more you can improve the customer experience, the more valuable each customer becomes, both as a source of additional sales and as an advocate for your brand.

Statistics from various CX trackers show that:

  • Customers who experience a positive social customer care experience are nearly three times more likely to recommend a brand (Harvard Business Review).
  • 68 percent of customers say they’ve switched service providers due to poor customer service (Accenture).
  • 59 percent of consumers aged 25 to 34 share poor customer experiences online (NewVoiceMedia).
  • $41 billion is lost by U.S. companies alone each year due to poor customer service (NewVoiceMedia).
  • 95 percent of dissatisfied customers tell others about their bad experience (Zendesk).
  • One happy customer can equal as many as nine referrals for your business (American Express).

There is real fiscal value in customer satisfaction, but as the old saying goes, you can’t manage what you don’t measure. Measuring customer satisfaction is the first step to improving CX, and big data is the right tool for better understanding your customers.

Develop a Better Understanding of Your Customers


Every customer interaction tells you more about that customer. If it’s an in-store transaction, then you discover what product the customer prefers, in what color or size, how he or she chooses to pay for it, whether he or she is willing to buy an extended warranty, and much more. E-commerce provides an opportunity to learn even more about consumers, because you can track the entire shopping process, tracking the customer’s progress through the online store to see where he or she pauses, what he or she investigates and more.

Big data allows you to harness all those customer insights to develop a comprehensive portrait of your ideal customer. Big data experts recommend that you record every aspect of every customer transaction to avoid any blind spots. Once you have the data, you can apply analytics to provide real-time opportunities to enhance CX and increase profits.

Targeting your ideal customer – Developing customer personas is not new, but big data analytics makes the process much more accurate. The most valuable customers are traditionally defined as those who spend the most, but that criterion is too limited. Those who spend the most may be too costly to maintain.

To find new customers, you need a more detailed definition. You need to consider factors such as acquisition costs, retention costs, average purchase size, spending over the customer’s lifetime and overall customer satisfaction. Assessing all these factors requires different types of data from different sources in different forms—clearly a job for big data analytics.

Anticipating what the customer wants – Once you start to track shopping patterns, you get to know your customer intimately. That makes it easier to recommend new goods and services based on the customer’s past purchases or behavior. Amazon, for example, recommends goods based on your shopping history. Netflix offers viewing options based on movies you’ve watched. Spotify and other music services make recommendations of new selections based on your past musical choices. These recommendations are made in real time based on analytics running in the background. They even go so far as to feed ecommerce advertising on social media and other online sites, using your shopping interests to entice you.

Improving customer service – Big data is increasingly being used to evaluate customer service, which is one of the most important influences on CX because of its ability to win or lose customers. When customers call the help desk or seeks out help online, they want to be heard and to have their problems solved right away.

Effective customer data tracking makes it possible to maintain a complete portrait of the customer so that the help-desk representative has everything that he or she needs to know at his or her fingertips. Big data helps aggregate that customer’s problem or complaint across the entire database, making it easier to find the right solution to the problem. The companies with the tools to extract more data from customer interaction tend to perform better in customer service. For example, many call centers are using speech-to-text technology to capture customer responses for analysis to improve help-desk training and develop a better understanding of their customers.

Every business is hungry for a deeper understanding of its customers, but most don’t know how to develop an objective customer portrait, nor do they know what tools are at their disposal to measure customer satisfaction. Perhaps even more critical is that most businesses think they know their customers, so they are already working from imperfect, subjective data.

Solution providers can be an invaluable resource in addressing the customer conundrum. Big data experts can help companies inventory their data resources and build analytic models that can shine a light on various aspects of the company’s customers and what motivates them. Solution providers can bring objectivity to the process and deliver empirical results that are sure to lead to additional profits for their customers and demand for more big data analytics.

Topics: Beginners/Introduction

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