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Predictive Analytics in Machine Learning: Benefits of Predictive Analytics for Businesses

We are in the midst of the digital economy, where business data is generated at a very enormous volume on a daily basis (2.5 quintillion bytes of data a day), and deriving insights out of such data is one key challenge that business organizations in all industries are facing. Successfully analyzing data and derive insights can help companies to have a better understanding of customers behaviors and their spending habits, adequately respond to the increasing in demand by consumers. Additionally, this also allows marketing and sales team to create better and more effective marketing campaign, executing cross-selling and up-selling more efficiently, etc.

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In this article, we explore how adopting the new technologies of machine learning and predictive analytics can help businesses gain greater insight into their business and customers as well as the market, making a more accurate business predictions and guide business to greater success.  

The Importance of Predictive Analytics

Today, one of the pre-requisite and most effective way for business to stay competitive in the market is to provide their customers with a highly personalized experience, custom tailored to customers' shopping behaviors and meeting their demand. Adopting a data-driven strategy and advanced analytics tools enable businesses to determine and effectively understand their buyers’ persona. Businesses that successfully adopted Predictive Analytics together Machine Learning technology understand that only capturing and storing data wouldn’t produce any actionable insights for effective sales and marketing. It’s critical that companies able to discover and predict customer insights to drive tangible business value and profitability.

This is where predictive analytics and machine learning technologies become necessary and can help business make an impact. Predictive analytics use  historical data and Machine Learning algorithm to predict future outcomes. Predictive analytics also take into account different factors such trends, cycle, and fluctuations etc. in the business data to make prediction. For example, sales team may use predictive analytics to project sales revenue in the upcoming period, or forecast the likelihood of conversion from the monthly trial subscription users and take appropriate actions to improve the results. Predictive Analytics and Machine Learning technologies is superior to some other traditional technologies in a sense that it is designed to take care of businesses activities in both the present and future.

Not only actionable business insights allow organizations to understand exactly what their customers really want and give them just that, Predictive Analytics and other machine learning technologies can also discover hidden pattern, telling data-driven story and provide recommendations to customers on the products/services that they are very likely to be interested in.  Hence, instead of delivering irrelevant or generic information, adopting machine learning together with predictive analytics can help companies to determine that best type of marketing activities and content that resonate with their customers, which in turn deliver a highly personalized experience to customers as needed.

Benefits of Predictive Analytics for Businesses.

In the new digital economy, one customer may engage with brands via multi-channels at various touch-points throughout their shopping journey. While each of the channel (e.g. Social Media, Website, In-Store, Call Center etc.) provides opportunities for business to serve and attract customers as well as prospect, the need for businesses to consistently offer better and better experience to their customers also increases. In order to have a complete 360 degree view of customers and deriving insights from customers’ data, no doubt businesses will need a data-driven approach so that they can generate more precise insights, improving their planning process.

Here are some of the areas where machine learning and predictive analytics will prove to have major impacts:

  • Budgeting – Companies can use predictive analytics to forecast more accurately their budgeting needs, instead of having to speculate and rely on the old models of "what-if". As a result, collaborations between departments can be improved for better team-works.
  • Customers’ insight– as mentioned above, advanced analytics can help business produce actionable customer insights predicting future actions by consumers. Companies can use this information to create better products/services tailored specifically to their customers. Similarly, companies can also apply this principle to increase conversion rate as well as improve customers’ royalty, reward program and more.
  • Cost reduction - With customer lifecycle becoming shorter and getting more complex, adopting predictive analytics and machine learning technology will help companies to have more effective marketing campaigns, resulting in the reduction of expenses while generating more revenue.
  • Gaining perspective – Business organizations can implement predictive analytics to gain insights into the future success of their new products and/or services. This is especially helpful when there is insufficient historical data available to make forecast or when the past is not indicative of future. Predictive analytics assist companies in making informed decision in the absence of past experience..
  • Etc.

Conclusion 

Predictive Analytics provide immense benefits and help companies generate more accurate forecast for business outcomes. However, each business is different and, will require different tools for different areas of analytics. Additionally, many companies also currently encounter other difficulties when it comes to applying machine learning and predictive analytics across their businesses. This is particularly due to some are still operating from the old silo models of legacy systems - with no central place for users to access business data, together with a limited technical capacity to thoroughly analyze and make sense of those data.

Building a successful data-driven business approach requires buy-in and participations from all levels within organization, including management and staffs across departments. All level participations will help companies internally assess their current business conditions, identifying the biggest weaknesses and opportunities for growth - in order to determine if predictive analytics can help solving those business challenges and drive growth. Once business understand their exact needs for advanced analytics, they can start evaluating options to implement Predictive Analytics for their businesses.

Contact TP&P Technology today to find out how we can help your organization's Predictive Analytics & Machine Learning requirements.

References:

1. https://www.forbes.com/sites/bernardmarr/2018/05/21/how-much-data-do-we-create-every-day-the-mind-blowing-stats-everyone-should-read/#3ec9d5f860ba