"You can't manage what you don't measure." Depending on whom you ask, that sentence may be attributed to W. Edwards Demining or Peter Drucker, but the premise is the same. You need data to manage well, but you also need to be mindful about the quantities of data you accumulate to avoid analysis paralysis. The more meaningful data sets you have, the better you can maintain your performance and improve customer experience as a whole. However, before you can understand how big data influences the customer experience, let's start by explaining exactly what we mean by "big data."
What is Big Data?
Big data is the collecting and analysis of data, but that definition pales in comparison to what "big data" is in practice. The term can mean many things. It is the massive amounts of data collected as well as a marketing term, a buzzword, Big Brother, and, according to the New York Times, "shorthand for advancing trends in technology that open the door to a new approach to understanding the world and making decisions." Big data can include outside information such as the weather in your local area, your behavior on other websites, social media posts (both by you and amongst your friends), and the behavior of others.
What Does it Have to Do with Customer Experience?
The information companies can cull from the massive amount of information big data collects can be used to offer your clients a better customer experience. For instance, every time you get a recommendation from a website, you are experiencing big data in practice. From Netflix to Amazon, many corporations collect information about you as you shop and they use this data to offer a better shopping experience, presenting more relevant items to you first and offering targeted promotions. By consistently driving the right products and services to your customer, the more your customer loyalty increases.
However, big data is the subject of many debates with privacy as a major concern. Many consumers will only provide personal information when there is a clear benefit as well as fair value. However, many people have become accustomed to having businesses anticipate their needs, and they become frustrated when they don't receive a personalized shopping experience.
Big data, and the personalization it empowers, can increase loyalty as well as impulse purchases while the number of returns declines. Companies that use big data successfully are also more likely to develop a better customer-centric strategy. They can target their intended audience better, improve multi-channel efforts, and clearly identify what has the most impact on customer satisfaction metrics. As a result, this creates more revenue for companies that ante up and invest in providing the type of big data-enabled insights that customers crave.
Customer surveys and feedback tools are a staple in any modern CX strategy. They provide invaluable insight into how to improve the level of support and experience you provide to customers. However, centralizing this information to understand the big picture can be difficult and as a result, it can leave you with fragmented sets of data. Big data technology can unite these feedback mechanisms to help you better understand what impacts negative responses from customers, where to improve performance, and how to maximize your sweet spots. Although it’s important to understand what happened within each of these areas, make sure to also focus on the causes that impacted those areas so that you can make better-informed predictions.
The Dangers of Analysis Paralysis
Big data is a "big deal" - it has so many applications and advantages that it can be dizzying. "Big data seems to have a paralyzing effect on many companies," explains Deloitte for the Wall Street Journal. "As much as they may want to exploit it to improve decision-making or uncover ways to monetize it, many organizations' initial big data efforts flounder and fail to realize desired value." Companies may become mired in technical concepts, like how the data will be stored and which technologies are best to analyze the information. Most do not understand data sampling or fail to collect the right pieces of data. More often than not, these shortcomings make the data no better than a guess and negatively impact the organization. This problem often impacts organizations in the early stages of digital transformation as they have realized that data is essential to proactive innovation. The challenge arises when the data is collected for the sake of having it, and not for the sake of improvement. Eventually, this leads to an excess of data that when put together, is incomprehensible and stifles their ability to be innovative.
A good "best practice" is to start with a single problem you are trying to solve. Then, assemble a team that knows the complexities of big data in order to help you select the right components to measure and analyze. You don't need many people-- just a few subject matter experts (like us) will do.
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