A voracious appetite for data is quickly becoming one of the defining traits of modern corporations. Companies of all sizes are racing to find ways to harvest relevant data, hire data scientists and implement business intelligence tools that will help them understand their clients and markets. Without appropriate methods for interpreting it, however, data becomes little more than an expensive waste of storage.
Once you have a means for gathering high-quality data, robust analytics can reveal the true value of your data by crystalizing its meaning and informing crucial decisions. Analytics applied to your firm’s real source of revenue and primary reason for existing—your customers—can be the gateway to explosive growth. Customer analytics services are divided into three main categories: descriptive, predictive, and prescriptive. This article explores the differences between them and the benefits of each.
Descriptive analytics help you understand what has been happening in your organization.
Many customer analytics firms excel at this kind of analysis because it is based upon data that is already available to you or could easily be made available through existing systems. Here are some possible applications of descriptive analytics:
Descriptive analytics are extraordinarily useful in retrospective and post-mortem scenarios where you want to learn from past experiences, but what about when you want to be forewarned of potential future trends?
Predictive analytics help you understand what could likely happen in your organization.
Compared to descriptive analytics, there are relatively fewer customer analytics firms offering predictive analytics, but there are still some strong options. These services are based on the concept of a “what-if analysis,” and they use statistical models to project past trends into the future. Here are some examples of predictive analytics at work:
Although confidence intervals vary somewhat with predictive analytics, the insights they provide are crucial to successful customer analytics.
Prescriptive analytics help you understand possible actions you could take because of what has been happening or what could likely happen in your organization.
Whereas predictive analytics can help you understand probable outcomes, they cannot make decisions for you. Only customer analytics services providers on the cutting edge offer the option of building a course of action from your data. Here are some ways this might happen:
The real power of prescriptive analytics lies in their ability to streamline decision making and accelerate appropriate action.
Customer analytics are crucial for maintaining a competitive edge in the Digital Age, and our expertise in customer analytics consulting will help you jump to the next level. Whether your business is new and aggressively growing or mature and seeking new target markets, we can guide you through the process of adopting a strong analytics strategy.
Contact Us Today
What are the Differences? Though often used interchangeably, data pipelines and ETL are two different methodologies for managing and structuring data. ETL tools are used for data extraction, transformation, and loading. Whereas data pipelines encompass the entire set of processes applied to data as it moves from one system to another. Sometimes data pipelines involve transformation, and sometimes they do not.Explore
One Unified Dashboard In the past, most enterprises would have used a legacy business management system to track business needs and understand how IT resources can fulfill these needs. The problem with these legacy systems is the manual data collection process, which introduces the risk of human error and is much slower than newer automated solutions.Explore
Intelligent automation in the workplace is becoming more relevant in the modern market. As automation technology becomes more refined and smart business models allow business owners to optimize their workflow, more and more are turning to intelligent automation for their internal and client-facing processes alike.Explore
What is a Hybrid Data Center? A hybrid data center is a computing environment that combines on-premise and cloud-based infrastructure to enable the sharing of applications and data across physical data centers and multi-cloud environments. This allows organizations to balance the security provided by on-premise infrastructure and the agility found with a public cloud environment.Explore
Leverage Your Data to Discover Hidden Potential The amount of data in the insurance industry is exploding, and the number of opportunities to leverage this data to achieve large-scale business value has exploded along with it. Rapid integration of technology makes it possible to use advanced business analytics in insurance to discover potential markets, risks, customers, and competitors, as well as plan for natural disasters.Explore
Increased Use of Data Lakes As volumes of big data continue to explode, data lakes are becoming essential for companies to leverage their data for competitive advantage. Research by Aberdeen shows that organizations that have deployed and are using data lakes outperform similar companies by nine percent in organic revenue growth.Explore