Data and the customer experience

In the not-so-distant past, when customers were often thought of in terms of transactions, coupons were a quick way for marketing to boost results. A business could easily compile a list of customer addresses and send them coupons. Determining the effectiveness of coupons and other traditional marketing tactics has never been easy nor do they produce much of a customer experience. But analytics is changing the marketing landscape by improving the hit rate of marketing campaigns and allowing companies to adopt a more holistic approach to the customer journey. Data-driven marketing can not only create a richer experience for customers, it can also improve the quality of marketing efforts, boost revenues and cut costs for the company.

A study by Aberdeen Group found that companies using analytics to craft customer engagement initiatives have significantly higher cross-sell and upsell revenues, better returns on marketing investment and higher annual profits compared with those that don’t. Another study, by Forbes Insights, revealed multiple other benefits, among them greater engagement with customers, improved collaboration between departments, improved reaction time to market changes and faster, more confident decision-making by management.

You need the right data, not just any data

Of course, embracing analytics to improve the customer experience comes with challenges. There may be reluctance within the company to adopt the technology in the first place; after all, the vast majority of companies (94 percent, according to the Forbes Insights study) are currently not capable of seeing the entire breadth of their customers’ experience – and companies may not grasp the potential of being able to do so. And, once data-driven customer experience (CX) has been put into place, there may not be full understanding of how best to take advantage of its opportunities or to make its impact felt across the entire business. In addition, there is the challenge of determining which of the many metrics collected are most relevant to customer satisfaction and for buying decisions.

Infrastructure enables analytical insights

From an implementation standpoint, there’s also a general concern among executives that existing IT infrastructure isn’t up to the job of advanced data-driven CX. Sophisticated management of CX is not just about using the right machines: Staff involved in managing back-end systems at a company have a marked impact on customer experience delivery, thus it becomes crucial to make their jobs easier through a more comprehensive approach to company systems. Also crucial is sharing the data well, because the need is twofold: Company decision-makers must be able to readily access and understand the information provided by customer experience data; equally, that data must be widely available and understandable, enabling employees at all levels to gain insights that might enhance the customer experience.

So, there is much to consider. But the opportunities are there. Forward-thinking organisations are already using analytics to improve their marketing in myriad ways, notably to gain a better understanding of the customer journey from issue identification to purchase consideration to final sale. And to improve and hasten their customers’ decision-making. The Forbes Insights study suggests that almost one-third of enterprises’ data-driven CX is effecting a significant shift in elevating customer experiences.

Citrix Systems, for example, which serves 330,000 organisations worldwide, has used predictive analytics to uncover the fact that sales were stronger when sales representatives followed up with customers to provide additional support, dispelling the widely held notion that time spent on support takes away from time spent on sales. In the healthcare sector, NYU Langone Medical Center in New York City has used a dashboard of metrics crucial to patients’ experience, including length of stay, discharge times and number of open beds, to drastically alter the workflow in the emergency department. These changes resulted in a reduction of wait times to see a doctor from several hours to ten minutes.

Data has been proven to increase understanding of customer desires, too, with what is known as “sentiment analysis” or opinion mining. These use artificial intelligence processes to extract data from sources as varied as social media posts, audio recordings and complaints.

Predicting tomorrow is tricky, but anyone in business knows that operating at the optimum in the present has become ever-more important. That’s why data-driven CX is also being used to improve the customer experience in real time by using machine-learning methods to select the best form of communication for each customer, further prioritised by, for example, the customer’s lifetime value to the company. Other technologies are also being pressed into service to improve CX. GPS location information can be employed to generate mobile coupons that draw nearby customers into retail premises, for example, while in-store mobile beacons deliver dynamic and localised web content to shoppers.

Expanding your data channels

One homebuilder cited in the Forbes Insight study has taken this knowledge of the customer even further, using CCTV footage and Wi-Fi data tied to smartphones to gather non-personally identifiable data about visitors to welcome centres in its various communities. The data is used to answer questions about how long potential customers spend in the visitor centre, what catches their attention while they are there and some demographic information such as age and gender. The answers to these questions have allowed the builder to see that certain communities were attracting more young professionals—an insight that was then used to make real-time adjustments to the marketing for those communities.

Indeed, refining information about the specific needs and interests of the individual customer is, arguably, the ultimate aim of data-driven CX. And that is getting closer all the time. Collecting and analysing data from all of the many touchpoints a customer may have with a company will make for the kind of sophisticated customer profile that will allow prediction of their preferences to an astonishing degree of accuracy.And, with smartphone adoption soaring, artificial intelligence becoming increasingly sophisticated and more and more data being generated through customer experiences, such accurate predictions are going to come sooner rather than later. The stock of data is growing rapidly. Companies investing in and taking a long view on approaching the customer experience through analytics can expect customer satisfaction to grow in tandem.