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The Importance of Analytics in Digital Business

What is the secret to making your organization successful in the constantly evolving and turbulent economy? It's analytics.

• By Troy Hiltbrand
• March 24, 2016

In recent years, McKinsey Global Institute, a global economic research organization, has reported a division in the economy based on the business utilization of digital technology. Those companies that are successful at leveraging technology to enhance their business processes are prospering, while those that are not continue to fall behind. McKinsey terms these successful businesses as digital haves and those who are being left behind as digital have-nots.

Late last year, McKinsey went even further, indicating that there is an additional separation in the have segment and broke out a subset of digital have-mores, the future economic elite. These are businesses that have gone further than simply implementing technology to augment their business processes. They are participating in an economy of digital business making technology the basis for their success, even monetizing their digital assets and driving revenue from them.

Paramount to their success is their full understanding of their customer base and integration of analytics into each touchpoint along the customer life cycle.

To accomplish this, they dissect the customer life cycle into a set of stages. During each stage, the customer interacts in different ways with the business. Once the business understands these points of engagement, they can identify what information is needed to optimize that interaction. Armed with an understanding of the critical information, they can employ technology to expedite the delivery of this information as an integral part of the transaction. With these organizations, information is not an afterthought. It is the fundamental basis of the customer experience.

Another key characteristic of these organizations is that they use information as a basis for personalization. They combine what is known about all of the parties in the transaction to optimize the transaction. This often includes information that is gathered as part of the transaction.

One popular mechanism to accomplish the personalization is user segmentation. By identifying the characteristics of each segment, it is possible to create an experience where the customer feels comfortable and secure with the organization and desires to continue with this business relationship. These digital have-mores do more than simply classify customers based on their past spending. They develop a full customer demographic profile and deliver an experience based specifically on that profile.

One of the leaders in this space is Amazon. They learn from past purchases to provide a highly optimized and personal experience for each customer. As customers enter Amazon's site, they are met with products and categories that reflect their individual interests. Amazon values this information so much and feels that it is so vital to its customer retention model that it developed Amazon Prime, which reportedly lost between $1 and $2 billion in 2015. On the surface, Amazon Prime is a subscription model for free shipping, but looking at the complete package, it is apparent that it is a mechanism to get customers to come back repeatedly to their site and browse their product catalog. Each time that a user visits, Amazon is building up a demographic profile of the customer. From that, Amazon can create highly targeted ads that follow the customer through the Web promoting items that fit with their area of interest. They have identified that the customer life cycle goes far beyond the customers visits to their domain, but extends across the internet. By leveraging information, they can enhance every customer touchpoint and have determined that they are willing to take a huge loss to build out an extreme level of customer intimacy.

Another technique used by these digital have-mores is prediction. Predictive analytics has come a long way in the recent past. With new tools and platforms, companies can utilize more and different types of information not previously possible to estimate the likelihood of a future event happening.

Companies such as Facebook rely on bringing back users to engage with their platform day after day. By ingesting attributes of past behavior, Facebook can leverage analytics to provide a predictive score representing the applicability of each new post on each individual's feed and prioritize those posts accordingly. The more relevant the stories on a user's feed are, the more likely the user base will return day after day. With Facebook's paid advertising revenue model, more eyes on their pages equates to higher revenues.

As the economy continues to evolve and this digital divide continues to widen between the haves and have-nots and even between the haves and have-mores, analytics will continue to be critical in powering the optimization of customer processes. Those organizations that harness the power of their information will have staying power, while those who fail to leverage it will be left behind and struggle to continue to find profitability in a turbulent and changing world.