Learn about real-time analytics and bring customer data to life
Building customer trust is a key ingredient to maintaining a competitive edge in today’s world of work, but with accelerating changes in the customer experience landscape, gaining this level of trust is getting tougher. The responsiveness needed to create seamless, delightful experiences that help to win loyalty requires a rich, clear, up-to-the-minute picture of each customer.
Real-time analytics provides a powerful snapshot that enables fast and informed decision-making when every second counts. This kind of customer and data visibility allows teams to be agile and proactive, embrace opportunities, meet changing customer needs, and anticipate issues to react without delay. For modern teams working at the speed of business, real-time analytics is a must.
In this blog, you’ll learn:
- What is real-time analytics?
- Benefits of real-time analytics
- Real-time data analytics use cases
- Challenges of real-time data and analytics
- How to get started with real-time analytics
What is real-time analytics?
Real-time analytics is the process of viewing, analyzing, and measuring data as soon as it’s collected in order to inform and guide rapid decision making. This process enables speed and accuracy that is unavailable with traditional or batch-style approaches to data analysis.
With multiple datasets from various channels, you need to be able to stitch it all together and solve for identity. That’s known as omnichannel analytics, and it’s requisite for doing real-time analytics at a customer level.
Real-time analytics is often used in a wide variety of applications, like personalizing customer experiences across multiple touchpoints, detecting and responding to threats in the security industry, managing sophisticated logistical operations, and aggregating data from edge devices like drones or vehicles to inform emergency response efforts.
Because the value of critical data can have a short life — think of time-sensitive reports on machinery wear or the latest data about market fluctuations — getting and using data in a real-time window is paramount.
Benefits of real-time analytics
From optimizing ad inventory and web traffic to predicting significant manufacturing failures, real-time analytics enables fast, agile responses.
Real-time analytics helps brands understand how customers are engaging — and to deliver relevant customer experiences and personalization, brands must move quickly from insights to action. Customer experience personalization is a huge win for businesses and consumers alike. Time-sensitive analytics enables teams to understand when, why, and how customers make choices and what brand actions can take their satisfaction to higher levels, such as advocacy.
Real-time insights can make processes significantly more efficient — saving time, money, and effort across an organization. This could include screening customers who've already purchased from promotions, optimizing personalized experiences based on recent behaviors, qualifying audiences for new audience membership as they engage with the brand, and more. There’s also a positive multiplier effect — if you can get insights and take action faster, you’ll take action more often, compounding the optimization.
Real-time data analytics use cases
There are a variety of ways real-time analytics provides essential clarity for business objectives:
- Real-time content personalization, blending browsing and transactional data, can help businesses provide just-in-time recommendations or customized promotions for these customers when they’re poised to purchase.
- Smart deals and offers are easy to deliver when customer profiles and needs are clear and unified.
- Streamlined digital sales funnels are enhanced and enabled as detailed, dynamic data about how an approach or product is performing at that exact moment can help quickly direct teams toward crucial pivots or adjustments.
Challenges of real-time data and analytics
Real-time analytics offers many benefits, but there are still some challenges to obtaining high-quality insights. The good news is they can be overcome by taking the right steps.
First, using analytics to gain a 360-degree view of the customer means pulling data from as many different sources as possible. Each data source can have its own specifications, formats, and processing demands, and changes in any of the contributing data can have downstream effects when processing in real time. Structuring the data processing pipeline to account for this variability, standardizing the different data sources across a common ID, and then stitching it to a user profile allows you to capture that 360-degree view of the customer in real time.
Delivering real-time analytics without the right infrastructure can also be expensive and time consuming. In the past, this meant that real-time analytics were reserved for a limited number of use cases. But advances in cloud computing and developments in real-time data processing mean that real-time analytics is now easily achievable for even small organizations.
Finally, data quality is integral to generating reliable insights. Poor data quality can negatively impact every step in the analytics workflow, directly affecting process time and revenue. Quality assurance from the start — verifying the integrity of the data source — and at every step of the process can ensure valid, valuable results through the end.
Get started with real-time analytics
Real-time analytics provides clear, actionable guidance for businesses when time is of the essence. Having critical insights at the right time is a huge advantage in making high-impact decisions. From delighting customers through personalization to optimizing web traffic, real-time analytics should be a vital part of every organization’s toolbox.
Watch the Customer Journey Analytics overview videoto learn how your organization can activate and enhance engagement throughout the customer journey.