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Why your Business Should be using Predictive Analysis

by | Dec 14, 2020

Why your Business Should be using Predictive Analysis

You can now predict the future.

No, it does not involve crystal balls, tarot cards or your astrological sign.

It has everything to do with data.

Data collection has become easier and more robust than ever before, thanks to the seamless integration of technology into our daily lives. By 2025, it’s estimated that there will be 41.6 billion IoT devices that will collect a total of 79.4 zettabytes (ZB) of data.

With all this available data, businesses can now make more accurate forecasts regarding what future outcomes are most likely to occur if the company takes a specific action – like investing a portion of their budget in organic SEO instead of paid marketing. This process is known as predictive analytics.

Predictive analytics uses historical and big data, combined with statistical algorithms and machine learning, to forecast trends and behaviours for both the immediate and distant futures. Because of this, Amazon can show you ads and promotions for the things you want without you even needing to search for it. This is also how Netflix hooks its viewers by recommending the next series or movies they would most likely binge-watch, based on their previous viewing history.

But, aside from marketing and customer relations, predictive analytics can also be implemented in almost all aspects of your business to better plan for the future. Here are just a few ways in which you can do this:

1. Fortify Security

Every evolution of technology requires that security protocols are updated to keep up with the pace of change. Despite having more advanced tools and solutions than ever before, IT security is finding it difficult to keep up, as threats and breaches become more complex and sophisticated with each new iteration.

A 2017 study found that hackers attack computers every 39 seconds, resulting in a whopping 2,444 attacks a day. Another study reports that 50% of these security breaches go undetected for months.

But with predictive analysis, you can prevent this from happening.

Predictive analytics uses patterns to study data. As a result, it can discover weaknesses in your assets that pose threats, determine the possibility of an attack before it happens and locate anomalies in your systems. Even more impressive is the fact that all these are accomplished in real-time, allowing your IT security team to build defences before threats have the chance to compromise your system.


2. Optimise Internal Operations

Predictive analysis has long been used to optimise internal operations – from airline companies setting their ticket prices to hotels predicting the number of guests that can be expected during a certain season.

The difference is that machine learning algorithms now have the ability to make more precise predictions with very minimal error. Additionally, it is now more easily accessible and adaptable to various kinds of businesses and different areas of company operations.

For example, businesses are now able to put a more specific number on the demand for a certain product, and know where it sells well and where it doesn’t. Thus, your supply chain can flow more efficiently by distributing the product to where it is predicted to have a high demand and decrease the supply to where it does not.

Another way modern predictive analysis optimises internal operations is by forecasting when your equipment is about to fail or breakdown. As a result, you’re able to conduct preventive maintenance without affecting productivity and causing customer friction because of machine downtime. It also plays a big factor in preventing accidents from happening.

Airlines are known for using this technology to predict mechanical failures, so they won’t endanger their passengers and employees, and so that they can reduce the number of flight delays and cancellations due to repairs.


3. Improve Marketing

91% of top marketers are already using predictive analysis in their campaigns and strategies.

Marketing campaigns come at a high price – not only in terms of budget and resources, but also when it comes to a company’s reputation. An ill-timed or ill-planned campaign can deeply affect your customer loyalty. Recent statistics report that more than 50% of customers will switch to rival brands after a bad marketing or sales experience.

Predictive algorithms help decrease this risk by accurately foretelling customer behaviour and sentiment. It allows you to understand what marketing messaging resonates best with them, when they are most active online, on which platform, and many other things. You are also able to get a comprehensive understanding of your customer’s journey and determine at which stage you are losing them (so you can find out why, and fix it).

Furthermore, predictive modelling gives you the ability to personalise the customer journey, hyper-targeting consumer segments with the right product recommendations and promotions. Because of this, you can focus on customers that are most profitable to you and learn how to attract, retain and grow revenues from them.

Tips on Choosing the Right Tool

Although machine learning technology has come a long way, and there are many tools available for businesses, 77% still struggle to implement big data and AI to make useful predictions.

One of the reasons for this is that, with the amount of options and complicated features available, choosing the right tool to use can be daunting. Here are a few short tips to guide you on choosing the right one for you:

Ask the right questions. Remember that predictive analytics only gives answers to the questions you pose. Thus, you need to be able to define what it is that you want to know from analysing the data you have.

Ease of Integration. Your analysis tool should be able to integrate data from all aspects of your business for a holistic overview of company performance.

Adjustability. Each business is unique, and cannot be fit into a single formula. Thus, you should get a tool that can be adjusted to your specific needs, and to future changes in your business model.

Understandability. Any tool is useless when its users don’t understand how to use it. Choose a tool that you and your colleagues can easily adopt and glean insights from, so you are encouraged to use it often in the decision making process.

The best predictive analysis tools come as an add-on to a business intelligence dashboard, which shows both current and projected performance. This way, you do not have to learn to use several tools and continuously switch from one to the other, and all team members can access data from a single portal to gauge progress towards a shared set of goals.

Is your organisation ready to start predicting the future?

OpenSight offers fully-personalised business intelligence dashboards, which let you automatically translate your data into an easily-digestible, visual format. Our team of data scientists can interpret the data and build predictive models for you, then provide actionable insights and recommendations based on the results.

Find out more about how our Data Science services can help your business prepare for the future here.

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