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Grow Beyond Historical Data Using Real-Time Data Analytics

Customers expect you to use their information to better understand them. In fact, around 50 percent of U.S. consumers will share personal data, but they will expect better experiences in return for sharing that data with you.

So, if consumers are willing to share this data, expect better experiences and will pay more for those experiences, then the solution is simple: businesses need to use analytics to understand and act on that customer data. The key is using that knowledge to deliver great experiences every time a customer interacts with their brand.


To deliver those valued experiences, marketers need to determine how to change the business for the better. This has to start with data analysis, usually in the form of a data project. These projects have taken different forms across time, but generally, they rely on marketing technologists or data analysts to conduct a comprehensive review of performance data related to incoming audiences or potential customers for a brand.

Traditionally, marketers have primarily used historic analysis to look at year-over-year trends. This lets them identify successful patterns and create an experience that fits a model of customer behavior.  This is still a highly useful strategy, because historical data helps companies compare year-over-year success and look at longitudinal performance.

Understanding this slice of data is critical to understand changes in your business across time. Analytics tools have made it easier to view this data and make sense of it in a way that helps your business make decisions. More recently, however, many brands have sought out a newer technique: real-time data analytics.

We know that customer behavior and buying trends change fast. Real-time analytics solves for the challenge of ever-evolving data. To have the most immediate business impact you need to be personalizing experiences to each individual. This means being able to perform analytics in real time. Doing analytics in real time goes hand-in-hand with the ability to orchestrate those experiences in real time. Together, the combination of historical and real-time analytics help guide customers down an ideal journey.


Marketers use historical customer data to help create a complete picture of their customers. This serves as a starting point for personalization because it includes everything from purchase history to unchanging demographic information. This static data such as customer demographics (e.g., age, gender, location) should also be used in an initial analysis to determine trends among customers. Once they’ve accomplished this first pass of the analysis, marketers can use it to understand and map the customer experience as it is today.

Unfortunately, data silos persist throughout most businesses, especially within marketing organizations, and this makes data hard to connect. For example, in a retail environment, online and offline purchase data may be kept in separate locations. This usually means that these preliminary historical slices of customer data are incomplete.

To overcome this challenge, marketers should avoid relying solely on historical data, but not totally abandon it either. For example, if a customer changes addresses, it’s crucial to update your records to provide more relevant content streams. Similarly, evolving customers tastes are not always reflected in historic purchasing behavior. What’s happening in their current queries is crucial for appropriate retargeting efforts, and in the long term, increased sales.

This doesn’t mean that patterns between past and present do not arise. The challenge is that it is often more impactful to look across a single customer’s lifecycle, rather than at all people across time. Most importantly for delivering great experiences, as customers age or even as they have experiences with entirely different brands, their preferred contact method may change. Only using a historical view misses this crucial, up-to-the-moment information.


As useful as traditional historical analytics approaches have proven, real-time analytics has seen tremendous growth in a short time. In fact, 84 percent of CX decision makers said that being able to use data in real-time is a high priority. The challenge with real-time data is that it’s extremely granular, with updates every second or minute. This means it takes a truly comprehensive change to analytics processes for brands to clearly understand what these changes in behavior mean and how to change experiences to better suit their customers.

One place you can begin is by actioning online data for in-store experiences. In a retail environment especially, there are many opportunities to show customers that you know them—without being creepy. If you’re able to pull their on-site search history with their permission, in-store staff can direct them to the most relevant parts of the store, provide additional suggestions and lay the groundwork for that person to become a loyal customer. Leveraging this data can prevent customer frustration or confusing differences between the online and in-store experience that so often occur.


When marketers leverage real-time and historical data together, they can create a better customer journey than either approach alone could produce. Historical data can help build models for behavior while real-time data ensures maximum relevancy in the present. Leveraging both of these analytics approaches can deliver positive experiences. Not only that. Together the two can also prevent or mitigate negative experiences, which can drive a valued customer away for good. Using the online to offline data example, if the brand knows what a customer has purchased in the past and is able to connect online and offline activities in real time, they can suppress advertisements for products that have already been purchased, deliver ads for add-on products, and generally deliver a better experience. If the customer has a negative experience with their purchase, real-time decisioning can pick up the pieces to direct them down the most relevant path to service.

Want to learn more about the customer journey analytics marketplace? Download the 2021 SPARK Matrix™: Customer Journey Analytics (CJA) report to discover which technologies are becoming essential for CJA.

Grow Beyond Historical Data Using Real-Time Data Analytics