Selecting and interpreting the most relevant information from the sea of data is both a science and an art form. Many organizations have an existing analytics strategy in place. But most of them lack the expertise required to identify trends and understand the key drivers that impact the customer’s experience.
First, you need to understand the impact of the data you collect today, map what you are going to use for your experience projects, and understand what other data is missing.
Four types of common customer data collected today:
Data stacks need to be carefully managed. Customer data architecture reveals customer profile information, transactions, operations, history usage, and what customers like and dislike from their past interactions with your organization, as well as other behavior that customers share with your brand. While you want, and in some places legally need, to have your customers’ permission to collect their data, let them have control, adjusting according to their preferences when they want to. This allows you to know when it's appropriate to use the information on their experiences with your organization.
You also must understand what type of analysis you want to perform in each scenario or case in which you want to gather in-depth insights and trends.
Here are the four data analytics types:
Descriptive and diagnostic analytics go hand in hand, and they involve past events, whereas predictive and prescriptive analytics involve the future.
When you have impact data and apply analytics using artificial intelligence (AI) and machine learning (ML), these features enable your organization to generate intelligence, highlight insights, and predict the next action.
In the not-so-distant future, the data analytics role won't just be about collecting data and analyzing customer feedback in order to create appealing metrics and data correlations. Rather, it will be a combination of data science and psychology. Teams will be expected to use AI to analyze a complex and large set of data and then correlate it with a set of personalized habits and behaviors, which feed into the personalized experience design.
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