How companies take advantage of big data analytics?

Big data technology made an impressive impact on nearly every industry by providing valuable information about a business. Because it allows transparent and accurate performance insights, even the leaders who are generally reserved to adopt new technology are curious about the power of big data.

Businesses of all sizes want hands-on experience in data analytics, and there’s a good reason for that. Companies that interpret insights and leverage analytics tools have nearly 20% increase in sales than those companies that don’t.

The definition behind big data

The term big data is used to describe large volumes of data that one business creates, as a part of its normal operating processes. This data is structured when detailly organised and unstructured when it’s raw and incomplete and therefore, is more difficult to process and interpret.

These are many ways businesses can use big data to stay on top of the competitors’ list:

  • Reduce costs
  • Identify and prevent hacks and frauds
  • Design new products and services
  • Improve current business decisions
  • Identify blocking points

Types of collected data

The consumer data that businesses collect is sorted into four categories:

  • Behavioural data – Data that includes transactional details such as purchase history, product
    usage info (repetitive information and movements online)
  • Engagement data – Data that shows how consumers interact with websites, mobile apps,
    social media, emails, paid ads or customer services.
  • Personal data – this is probably the most sensitive category of all. It includes personally
    identifiable info such as Social Security numbers, gender, as well as non-personal identifiable
    information including the IP address, web browser cookies and device IDs.
  • Attitudinal data – This data looks at the metrics on consumer satisfaction and feedback,
    purchase criteria, product demand and so on.

How businesses collect user data?

Companies collect and capture data in many ways. Some methods are highly technical, while others are more deductive. There are many available product platforms and tools that clean, segment and interpret business data. A robust and layered business concept needs all of the abovementioned. Businesses also dig deep into customer analysis to see how customers have interacted with their sales and support departments. Besides collecting information for business purposes, companies that legally sell personal info and other data to third-party sources have become quite common and thriving on the market.

Data analysis becomes business consultation

No manager or stakeholder can reasonably sit down and read through lines of data. Software solutions, however, scan this data more efficiently and quickly than us, while operating 24/7. As machine learning algorithms and other forms of AI have improved, data management and analytics becomes even more exciting playground for performance insights. AI programs track and flag anomalies in data or offer recommendations to teams based on the scanned and contextualised data. Without solutions like these, the captured data will be completely useless.

Industries like healthcare, pharmacy, gaming and retail prove to be quite successful with handling large amounts of data, making it work in their favour and improve their offers to specifically targeted consumers. As an example, online casino gaming providers follow, track and read customers’ online behaviour and feedback, so they can grow or keep their rating at the highest level. Make sure to check out slotswise.com for the latest updates on the casino providers and their top-rated game offers.   

It’s essential to implement a clear action plan for data collection. Only high-quality data can help in making data-driven decisions which will be of a benefit to the company. Define goals, operation and validation procedures so your insights would be adequately translated to recommendations.

With exemplary customer data handling, companies can improve customer experiences, tweak, and refine marketing strategies and even create new revenue channels. There are data privacy regulations such as the EU’s GDPR and California’s Consumer Privacy Act (CCPA) that must be adopted by any company that collects personal data. Laws change accordingly to the technological advancements, and businesses that are somehow still untouched by data privacy regulations might expect to have a greater legal obligation to protect consumers’ data.

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