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How Data Analytics Help in Predicting the Market

Analytics is the most futuristic tool a company has today to gain clear customer insights. As per PCMAG, Big Data market is set to top $274 Billion by 2023.

All the big players, like Amazon, Google, and Microsoft, are investing in this future. Not only are they collecting data but they’re offering access to this data to other enterprises.

Data analytics helps marketers learn about their audience from their online activities on different platforms — from selecting a product or watching a video on Amazon to ordering their favorite dishes on Zomato. Data experts have warned that data analytics is at an inflection point. With the access to such huge amounts of data, concerns about the security risks, privacy and other regulations abound. Artificial Intelligence and Machine Learning are offering a great benefit but these concerns are bumping against all the benefits. 

Today, the pandemic has further changed users’ behavior, bringing even more challenges into the spotlight.

Neil Hoyne, Chief Measurement Strategist at Google, recently said: “What we’re seeing is a lot of chaos in terms of what is the right answer. And what we’re seeing is a change in strategy.”

Major internet providers like Google are planning to phase out third-party cookies, which will be a turning point for a lot of marketers. This will strip vast amounts of knowledge from across the web. Many proactive companies have already started working to cope with this situation so, when they will finally face this new reality, they will already have a plan in place.

“The companies that are going to win are the ones who are using data, not guessing,” said Hoyne.

Earlier, companies mainly focus on getting descriptive data about users but now they have also started harvesting both predictive and prescriptive learnings. Let’s discuss with a brief overview about these analytics types:

  • Descriptive analytics: This provides insights about what’s happening in your organization. Descriptive analytics includes all the web hit reports, campaign rates, and sales reports. With all this data you can check how your campaign is performing.
  • Predictive analytics: This pulls more complex ML & AI algorithms to determine what will happen in your company. It helps you narrow down the options of how well a product will sell, who are effective target group, and which campaign strategy could be most beneficial to sell your product.
  • Prescriptive analytics: This more advanced data set  will help you improve your strategy and give you an idea of which method works best for you. Beyond providing insights, it goes one step further to suggest optimization ideas for campaigns and how tie up loose ends even before launching.

Currently, big data companies are working on data supermarkets. As per one of the theses submitted to International Data Corporation (IDC), the data supermarket prediction will have following IT impact:

  • Setting up data supermarkets requires significant efforts from IT and data management teams. This marketplace allows for distributed access to relevant data, instantly, within security and governance parameters. The platform combines large amounts of data from multiple sources cost effectively while simultaneously building data structures and governance.
  • Data-driven organizations are exploring uses for cloud native data management platforms, DataOps strategies, and new concepts (like data lakehouse), to simplify their data infrastructure and create a supermarket-style access strategy.

The following guide will be helpful:

  • Organizations need to unify data storage, management, access, and governance capabilities to deliver a centralized marketplace for a quick and consistent data experience.
  • Many organizations are developing a vision for data-led value creation as they see the significance of real-time analytics, artificial intelligence, and big data in navigating through the current crisis.
  • For too long, challenges such as data silos; security and governance loopholes; rising costs of managing disparate systems for different data; and making data users themselves perform tasks such as combine, curate, and prepare data have hampered companies’ speed. It is time to create a new paradigm to present and consume data.
data analytcis future escape
Source: IDC

The field of Data Analytics is already vast and is continuing to expand exponent. To know the type of data and analytics your company should be investing in, you need to start asking the main question: What do you want to accomplish? The market has only seen the tip of the iceberg, lot is yet to be explored.

It’s time your company should start utilising the benefits of analytics and reshape the future of your company. Nabler is one the leading Data Analytics consultants who can help you track the activities of your customers and with this you can improvise the strategy to gain customers and enhance your customer reach.

Drive better results by understanding customer data