Data is the new currency that unveils new trends in customer data management. Data is more effective as it can multiply its importance by the ability of being usable for various sectors at the same time, such as security and consumer services. The economic value of data is much more than currency if organizations truly manage data as a corporate asset. This inclination is creating a customer data management strategy inviting specific customer data management trends in 2020.
Customer Data Management Trends in 2020
Customer data management (CDM) is defined by the process and structure, which supports collecting, managing, and analyzing data from different sources to form a unified view on each customer. Customer expectations are evolving, and marketers are expected to be able to deliver meaningful personalization that can engage them through their customer journey. Customer data management trends enable marketers to address the new ‘paradigm of personalization’ for real business outcomes.
Here are a few trends in customer data management, which is grabbing attention.
Hyperautomation is currently leading the customer data management trend as it deals with the application of advanced technologies, which includes AI and ML (machine learning). The new trend to include AI and ML have increased the automation process. As AI is spreading its dominance in data assessment to collect personal data, access those, and use the data for upgrading customer service, it supports hyper-automation more profoundly.
2. Data Democratization
Data democratization has helped in market growth, relieving the users from the rigid rule of guarding it. The open platform has supported the collaboration of multiple organizations to work together to provide better service to the consumers. Automation plays a significant role in enhancing the quality of data democratization, and access the data scientifically for service-based use. Data democratization is one of the leading trends in 2020 that will open vistas for more powerful data support systems.
3. Memory Servers
Affordable performance, easy availability, and a more extensive database create the need for memory servers. Database vendors are supporting the server to help in the growth of real-time data and memory preservation. Gartner predicts persistent memory servers will represent more than 10% of GB memory consumption of in-memory computing.
4. Data Valuation
Today data is acknowledged as a real asset that has the actual monetary value assigned to it. Data has gained importance just as physical assets and intellectual property. It is powerful enough to identify, track, or address various activities that can help in the security sector as well as consumer service sectors. The ability of data to discover, support AI govern, and socialize the assets, creates scope for the latest customer data management trends. Data valuation helps in the process of ensuring data quality, especially in convincing, data-dependent service cases.
5. Data Modelling
As the continuous growth in AI and machine learning (ML) adoption, a variety of data gets stored every second. Dealing with rapid growth in the volume of data, at times, needs more clarity and compartmentalization and which leads to data modeling. Data usually being stored in the cloud across functional sections to support quick search in the most scientific manner. The well-expanded areas for complex data support and automated design show the importance of data modelling, and predictions made by the use of data will grow at a rapid scale.
Blockchain has come to light for its influence in bitcoin and other cryptocurrencies through verifiable transactions globally. Blockchain technology is the base of trusted information management. It helps government agencies to access and use critical public-sector data without risking the security of this information. Controlling the trusted news and using them productively enhances the use of blockchain technology, making it one of the leading data management trends of 2020.
7. Continuous Intelligence
Continuous intelligence is the latest trend in customer data management. It makes the tracking process simpler. With time it’s becoming faster, more accurate, and minute in its details. Mobile apps such as maps or courier services or health trackers are getting support from continuous intelligence. Real-time data and advanced analytics support in intelligent, automated, and outcome-focused data. Continuous intelligence helps to improve customer database management software creating more data for other upgraded services as well.
8. AI and ML Support
Support from AI and ML are encouraging the companies to turn the focus towards the improved and speeding data support. The accuracy of fetching the perfect data and the time it takes for inventory, profile, and classify decentralized data helps the service sector to improve at a quick pace. According to Gartner, “By 2022, 90% of corporate strategies will explicitly mention information as a critical enterprise asset and analytics as an essential competency.”
9. Augmented Analytics
The influence of AI and ML prompted the traditional IT-led data catalog projects that do not use ML or AI to assist in finding and inventorying data distributed across a hybrid or multi-cloud ecosystem to take the help of it. The traditional process is bound to fail as it is a time taking method, and eventually will not be possible to deliver the data to support the services at the exact time. The need for super-fast data support is creating a path for augmented analytics for comprehensive data management, analytics, and data scienceprojects. The data and its augmented analytics’ strategies are becoming an inevitable trend for the data management process.
10. More Security for Data and its Access
In the current scenario of data democratization, data collecting has become easier. AI and ML are helping the process to reach its zenith. But easy accessibility and different sources of getting data, creating a concern for data security. The data access should be more protected, which can be used only in providing better security and services. The trend of cyber hacking is a real concern and has become the trend of saving data from any theft activity.
Today the organizations have an excellent opportunity to collect and use data to improve their decision-making. The process has created the opportunity to support the decision-making process with the help of millions of data. Access to more time-bound and accurate data can enable organizations to come up with more significant material, and prominent insights about their customers, products, and operations to make “better” decisions.