We are living in a time of data explosion. Enabled by development in technology, today's business organizations have the best opportunity to build on this huge cache of information that is both readily available and inexpensive. 

Google, Amazon or Netflix are considered innovators in the B2C economy because of their use of analytics knowledge and application to understand buyer needs and offer customer requirements. If B2C companies can do it, why can't B2B marketers develop analytics-based strategies? 

Every business professional in the modern age knows the importance of data. But though there is a flood of customer data, companies are not using it for business reasons as much as they should be. They dwell on past experiences and their own business knowledge to make decisions. Analytics is being applied, but this is not yet a full-fledged business practice as it's still evolving. As a marketing process, its total application will take time because new forms of media, channels, and devices are constantly emerging. Most of all, human behaviour itself is unpredictable. 

The case for predictive analytics has never been stronger

Predictive analytics is the science of making forecasts about the future. Its components are data mining, machine learning, and artificial intelligence that help analyze current data to make predictions about future buyer behavior. It charts out patterns of behavior that show buyers' next steps while making purchase decisions. In any business, predictive analytics helps to learn the entire customer lifecycle journey and unearth important information about them. Through predictive analytics, marketers gain hitherto concealed and great insights to make precise, effective business strategies. Buyers have high service-level expectations and look for compelling customer experience in their buying process. 

Predictive analytics is different from buyer segmentation analysis because assembling customers' buying information is complicated. Buyer segments are relatively constant over time, but an individual buyer's purchase behaviour keeps shifting. As the reasons for purchase by customers change, businesses should align their offers that best suit the customers' requirements. But though there is wide acceptance that data is important to organizations, most business decisions still do not leverage the information about customer data when it comes to engage buyers. Here lies the importance of predictive analytics. 

The data is all there, so why not use it?

To discern buyer behaviour, predictive analytics employs data that will provide information at the level of an individual customer. In fact, the granularity of information is so compelling for business that it undermines all forms of conventional business strategies. The insights that predictive analytics reveals about buyers are so different from existing business knowledge that marketers will be forced to apply new engagement strategies to improve results. 

Modern business thrives, and will survive, on its capacity to conduct a digital dialogue with all stakeholders, especially customers. In the digital world, companies listen with data and respond through a variety of digital interactions, especially social media. It's well established that modern marketers should understand the importance of data, but not enough importance has been assigned to the role of predictive analytics. 

It is specifically in predictive analytics that marketing should make headway, not only for ROI but also other priorities such as staying ahead of the competition. Research shows that businesses should typically start with data from interactive systems such as click streams, video views, or search. Businesses of today have more than 40 categories of interaction technology to utilize. By incorporating data from other systems like CRM, logistics, and finance, you can stay well ahead of the pack.

The prediction is simple - Use analytics or perish

Look around, and you will find top companies and analytics vendors merging their minds to develop algorithms and develop new business insights. Why are top-end companies like Amazon or Netflix ahead of the pack? Because they build their business capabilities through combining deep, diverse, and extremely granular data that is derived from predictive algorithms. Data marketplaces then target buyers and send data real time to advertising exchanges or Twitter to place ads and content. 

Buyer expectations for better customer experience have increased manifold. Predictive analytics is ideally suited to address complex business situations. It discovers, identifies and finds the signals that provide notice of buyer behavior as well as key events. It uses behavioral data that we already have, to predict the data that we do not and likely cannot know from other methods. It's not an investment in the real sense of the term, but simply a smarter way to use existing information and improving business. 

Read more at: https://economictimes.indiatimes.com/small-biz/security-tech/technology/predictive-analytics-using-technology-to-get-information-at-the-level-of-an-individual-customer/articleshow/64283429.cms