Topics Covered
Introduction
Today, a dissatisfied customer will not take time to switch loyalties.
It goes without saying that if a business wants to prosper, they must put their act together through data analytics by collecting and managing data at every point of the customer interaction to be able to give best-individualized experience.
In the course of interaction of an advanced customer analytics ensures that data that is unique to the user can be collected at various stages, be it usage of mobile apps, social media interaction and a lot more
The company should be able to use this information through big data analytics tools to give the best user experience, something that will go a long way to sustain clientele and to beat the competition.
Is Big Data Analytics Different from the past?
Earlier we were following the ETL model of data handling. ETL stands for Extract, Transform and Load.
The data was captured by systems primarily to obtain reports from past actions. Different methods are used to load variety of files into a huge database that generates desired actionable reports.
But this was instead a rigid system, which was unable to take care of multiple data streams especially in large volumes.
The systems were also not able to change the input info on a real-time basis and were more suited to respond to fixed queries.
But Big Data analytics has changed it all. Now by using advanced analytics, companies can decide better.
Data Analytics has enabled improved reporting interface structures, better data extraction capabilities, automatic file handling protocols, the creation of highly indexed data streams and above all, the capability of cloud hosting and blockchain technology to run and control a large system on a real-time basis.
All this boils down to better business decisions thereby improving sales and marketing effectiveness and at the same time reducing costs and eliminating wastages for all digital businesses.
The companies can derive significant benefits from data analytics services to get positive outcomes for the business and customers while ensuring a high level of data protection. The most important advantages of advanced analytics are:
1. Proactive Approach
According to a report by Compliance, Governance and Oversight Counsel, 60% of data carries little or no value. Most data lose their value if not contextualized in real-time, so it’s essential for businesses to make data available in real-time with the lowest latency possible and scalable capacity.
When sharing info, the only expectation that the customers have is to understand their requirement correctly and to give seamless interaction at all stages of interaction by doing so companies can improve the customer experience, a sure shot way to forge lasting relations.
2. Offering Right Product
Efficient data analytics and collection helps businesses to understand the changing technological demands of the market to be able to position the right product or services at the right time.
3. Customized Service
Today customer behaviors are incredibly volatile and unpredictable coupled with lots of options available for them to choose.
The only way to gain them is to offer personalized response and make them feel personally valued.
Using the Big Data analytics, it is possible to create interactions best suited to the customer type and personality.
For this, the system should be able to capture the customer attitudes, their location and preferences to offer a customized response in a multi-channel environment.
4. Improving Operation Efficiency
Data analytics helps in understanding, designing and optimizing the products at highest efficiency, that is capable of meeting customer needs and expectations.
The Big Data solutions help in improving field operations, enhancing productivity and thereby minimizing costs and improving margins.
The powerful real-time data analytics creates following operational advantages:
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- It makes it possible to capture errors and failures instantly. It helps companies to react immediately before damage is done and the customer decides to shift to the competition. It is always easier to retain business and difficult to bring them back once they are lost.
- It helps to understand competition and changing barriers instantly. Companies can use this info to stay ahead of the competition by timely capturing the actions and changing strategies of the other market players. For example, if your competitor reduces the rate, you must know it instantly before the business is lost. With data analytics, it is all possible.
- It assists in improving deliverables to have better conversions rates and increasing revenues. By monitoring the products that customers are buying, companies can respond pro-actively to any issues in product performance. For example, a motorbike company can deploy real-time sensors to inform the user to attend to any maintenance issue in advance to avoid downtime.
- It helps in detecting frauds before they are done to take the advance corrective actions. It is instrumental in the financial world. Financial companies can deploy Big Data analytics tools to instantly capture any attempt by criminal elements to hack the system before reputations are lost.
- Security systems and fraud analysis through advanced analytics help to protect all the financial and physical assets against internal and external misuse and damage. Proper data management coupled with analytics and timely reporting of frauds creates a safer operational environment for business and its users. The data across various business verticals and platforms can be combined in real time to ensure a uniform organizational view and tolerance to activities not matching with the business values and ethics.
- It helps in reducing cost by improving the efficiency of operations. A well-designed data analytics environment allows the business leaders and decision makers to capture and monitor the important variables in advance so that the corrective actions can be taken on a real-time basis. No longer waiting for reports and then doing dissection in history.
- It helps to capture real-time sales data about; What is selling? At which location is selling? How much is selling? Who is selling more? Etc.
- It helps companies to align to changing customer preferences on a real-time basis. It is done by mapping competitors’ activities and capturing the results of the sale promotion activities
