They do not, however, guarantee defensible barriers. These developments make data-enabled learning much more powerful than the customer insights companies produced in the past. After machine-learning algorithms analyze this “digital exhaust,” a company’s offerings can be automatically adjusted to reflect the findings and even tailored to individuals. Internet-connected products and services can now directly collect information on customers, including their personal details, search behavior, choices of content, communications, social media posts, GPS location, and usage patterns. That changed dramatically with the advent of the cloud and new technologies that allow firms to quickly process and make sense of vast amounts of data. But the sales data often wasn’t linked to individual customers, and since surveys and focus groups were expensive and time-consuming, only data from a relatively small number of customers was collected. For automakers, consumer-packaged-goods companies, and many other traditional manufacturers, it required crunching sales data, conducting customer surveys, and holding focus groups. Gathering customer information and using it to make better products and services is an age-old strategy, but the process used to be slow, limited in scope, and difficult to scale up.
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Those companies are protected by significant barriers to entry because of the economies of scale involved in acquiring and structuring huge amounts of data, but their business models don’t involve gleaning data from customers and mining it to understand how to improve offerings. Take credit bureaus and the information aggregators LexisNexis, Thomson Reuters, and Bloomberg, just to name a few. What Has Changed?Ĭompanies built on data have been around for a long time. In this article we’ll walk you through what those conditions are and explain how to evaluate whether they apply to your business. Nevertheless under the right conditions customer-generated data can help you build competitive defenses, even if network effects aren’t present. However, few companies are able to develop both.
To establish the strongest competitive position, you need them and data-enabled learning. But in practice regular network effects last longer and tend to be more powerful. The virtuous cycles generated by data-enabled learning may look similar to those of regular network effects, wherein an offering-like a social media platform-becomes more valuable as more people use it and ultimately garners a critical mass of users that shuts out competitors. In most instances people grossly overestimate the advantage that data confers. More often than not, this assumption is wrong. You can then collect even more data and eventually marginalize your competitors in the same way that businesses with sizable network effects do. The more customers you have, the more data you can gather, and that data, when analyzed with machine-learning tools, allows you to offer a better product that attracts more customers. Many executives and investors assume that it’s possible to use customer-data capabilities to gain an unbeatable competitive edge.
And when learning from one customer rapidly improves an offering for others (think Google Maps), people will care about how many other people are adopting it, and it will enjoy those sought-after network effects. Those characteristics do give firms an advantage. It all depends on whether the data offers high and lasting value, is proprietary, leads to improvements that can’t be easily imitated, or generates insights that can be quickly incorporated. Nevertheless, under the right conditions, customer data can help build competitive defenses. Though the virtuous cycles of data-enabled learning may look similar to those of network effects-wherein an offering increases in value to users as more people adopt it and ultimately garners a critical mass of users that shuts out competitors-they are not as powerful or as enduring. You can then collect even more data, repeating the cycle until you eventually marginalize your competitors. The more customers you have, the more data you can gather, and that data, when analyzed, allows you to offer a better product that attracts more customers. Many executives assume that customer data can give you an unbeatable edge.
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