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What does customer experience management mean to you?

The volume, velocity and variety of data is increasing by each passing day and it has become even more imperative for businesses to tap on this gold mine. Data analytics, on the big run, is helping organizations from all walks of life to monetize this data by deriving in depth analysis. The era of 2022-25 is going to be about data monetization driven by analytics. This helps directly impact the bottom line of the company while improving their operational efficiency and derive insights to enhance customer experience.

According to the Big Data Analytics Services Global Market Report 2022, the Big Data Analytics Services market is expected to grow to $121.65 billion in 2022 from $107.85 in 2021, at a compound annual growth rate (CAGR) of 12.8%. This gives companies a great deal of opportunities to expand their businesses, gather useful business intelligence and gain insights into consumer behavior. Several data and analytics trends are bound to give direction to the new age businesses in 2022.

Here are 8 data analytics trends that will rule in 2022.

  1. Cloud-Based Data Analytics

    Cloud-based data analytics allow non-technical users to easily access, apply, and analyze large volumes of information in a safe, seCustomer experience management is getting more prominent in business scenarios. To lead the competition, there is no better solution than offering a personalized experience to your customers. In your niche, hundreds of companies are there and they can win your target audience as well as existing customers at any time. But you may have seen that some brands are running with amazing customer bases and increasing their bases accordingly. How are they managing it so smoothly? They are managing it smoothly with the help of efficient customer experience management. What is this customer experience management actually? Customer experience management is basically an effective process of managing customer interactions via each physical and digital touchpoint to deliver personalized experiences. Personalized experiences ensure brand loyalty, increased revenue, branding, and so many other indirect benefits. Why is customer experience management important? Proper customer experience management with a sufficient amount of branding ensures increased sales and reputation as it directly contributes to customer perceptions and sales. It can leave both positive and negative effects. You can expect a positive effect if you are doing it well. But a lot of companies face negative consequences mainly when they enable customer experience management or CMX but do not touch all important points. A lot of startups and even some old companies are still clueless about why they should enable CXM. If you fall in the same category, this quora answer will give you the right insights. Increased customer retention- According to various business studies, just a 5% increase in customer retention rate results in up to a 25% increase in sales. A satisfied customer orders more and you don’t even need to bear the cost of acquiring a new customer. Improved satisfaction rate- a satisfied customer not only gives future orders but also acts as a brand ambassador. You can see that modern people prefer to get real-time reviews nowadays instead of listening to something from a celebrity who is simply doing promotions. A truly satisfied customer will definitely tell about you in his/her circles and you will start getting more and more customers. Easy branding- small to big- every company is in a try of improving their branding. They are trying to impress more and more people and that’s why they are leaving no stone unturned. Happy customers share their experiences in their circles and even on social media platforms. It is really effective in boosting the brand value of an organization. Cost-effective practice- Today’s marketing practices require a lot of money. For small businesses, spending a big amount of money is not always possible. On the other hand, traditional marketing practices are seeming not so effective in today’s scenario. Today’s customers are more intelligent and they check every factor before trusting a company. And that’s why customer experience management is getting prominent more and more. Improving customer experience management means you are boosting the trustability of the company. These are the top benefits or reasons for which a company should enable proper CXM right now. You have to be very much sure about your CXM plan otherwise, it may leave some negative effects. It’s always better to get expert advice and help to set the required CXM practices for a business. cure, and convenient environment. They also provide systems administrators with the ability to centralize management and improve workflow efficiency. They extract value from the disparate sources of information that comprise modern IT environments.

  2. New Privacy Laws Will Spur Innovation

    The first thing to understand about these regulations is that there are a lot of them. The ones followed globally like the General Data Protection Regulation (GDPR), which has been in force in Europe since May 2018, and its California cousin, the California Consumer Privacy Act (CCPA). In Europe, new rules are coming into force under the Privacy and Electronic Communications Regulations (PECR), and Australia's Consumer Data Right will start this month. The ePrivacy Regulation is expected to follow next year. Canada has a privacy act too: it's called the Digital Privacy Act. Further, New York has just passed something called the SHIELD Act, adding even more compliance requirements for businesses with New York customers or employees.

    What all of these laws have in common is that they require companies to think carefully about how they collect data from individuals. They also have to make sure that they have clearly defined processes around deleting data when asked by users, or if it’s no longer necessary for whatever purpose it was collected for in the first place.

  3. Streaming Analytics

    Streaming analytics is a subset of real-time analytics. In streaming analytics, the processing is in real-time rather than batch processing. It can be integral to providing insights on the go, especially for use cases such as fraud detection, supply chain optimization, and machine maintenance.

    In 2022-23 streaming technologies will have matured to a level where they will support a variety of use cases like :

    • Fraud detection
    • Supply chain optimization
    • Machine maintenance
    • Recommendations to customers or employees and more
  4. Democratized analytics

    Democratized data refers to making analytics accessible to everyone in the organization, not just data scientists. It involves a combination of advanced analytics tools and data literacy: ensuring that every employee has data skills to understand and work with data, helping them ask the right questions and solve problems.It is an essential step towards data literacy which will help less-technical employees, such as marketers or salespeople, understand, communicate with and work with data.

  5. IoT, AI, And Machine Learning Convergence

    IoT, AI, and machine learning are already changing how we live our lives. But their convergence will further transform how we work and do business. The result will be new products and services that improve our quality of life from the living room to the boardroom.

    Data analytics is critical for processing the data collected by IoT sensors. It is also used to develop and train AI algorithms, which can discover patterns in data that would otherwise be missed by humans. As IoT sensors proliferate into every corner of our lives, vast quantities of data will be collected in real-time. This data can then be analyzed using AI to learn more about what it means to us as individuals and organizations, enabling new possibilities.

  6. Predictive Maintenance Using Big Data Analytics

    Predictive maintenance is a branch of predictive analytics that forecasts when equipment will need maintenance. Predictive maintenance can identify potential equipment failures, help reduce downtime and costs, and avoid unnecessary service calls.

    Predictive maintenance uses real-time data from various sensors to determine the condition of an asset. This technology predicts when equipment will need maintenance, ensuring that it operates at peak performance while reducing downtime and costs.

  7. Automated Machine Learning and Data Science Platforms

    Automated machine learning works by automating the data science process. Therefore, instead of spending hours looking at algorithms and deciding which one is best to use, a machine learning platform can do all of the work for you. The software will analyze your data set, create different models and test them to see which works best. The software is an option for data scientists who don't want to worry about knowing all of the ins and outs of how algorithms work.

  8. Self-Serve Data Analytics

    Self-service data analytics solutions are a popular topic across industry and executive sureveys. This trend has been ongoing for a while as vendors like Tableau, Power BI, QlikView, Domo and many others have made it far easier to visualize and share insights with more people within an organization. Beyond being more user friendly, vendors are providing cloud-based offerings that make it even easier to deploy, integrate and use analytics tools. With the power of self-service data analytics solutions now available to the masses, we can expect more businesses to leverage data on their own without relying on their IT staff or external consulting companies. The advantages include greater agility through faster time to insight and reduced costs by enabling business users instead of IT pros or consultants.

Conclusion

Data is more than just a trend; it's the backbone of most organizations who are looking to monetize their data. In short, data has become more important than ever, which is bound to make a difference especially for new age businesses.The establishment and adoption of right BI tools and data governance practices would lead organizations to predict the business outcome while taking informed business decision, allowing full control on their bottom lines.