Technology January 24, 2017 Last updated January 23rd, 2017 2,487 Reads share

How to Use Predictive Analytics for Business Success

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Customer requirements and expectations play major roles in business strategies. Businesses are required to orient their decisions in a way that provides maximum customer satisfaction. This helps in making the business more relevant to the existing customers, thus increasing retention and paving a way to bring in more conversions.

Personalization is the new tool that businesses have included in their army of strategies to optimize sales and enable quick growth. The only way to stand out from your competition is by understanding your target consumers’ present and future needs. While the current requirements are quite obvious, the future needs aren’t so easy to grasp. This is where predictive analysis becomes relevant.

Predictive analytics is quickly becoming more popular in the marketing world owing to the various benefits that it has to offer.

What is Predictive Analytics?

In simple words, predictive analytics utilizes past and recent data to predict the future activity, trends, behavior etc. The process includes machine learning, data mining, modelings, artificial intelligence and so on. Based on the forecast, businesses can design strategies and solutions to serve their customers better. In addition to that, predictive analytics can also be used to identify the possible risks in the future, fraud detection etc.

At the very core of predictive analysis lies valuable data that is measured and analyzed to forecast the possibilities involving customers, staff, machinery and so on. By uncovering relationships between both, unstructured and structured data, business owners can create predictive intelligence.

The data used for predictive analysis may include age, marital status, gender, total earnings, social media interaction, purchase history and so on.

Effective Ways to Use Predictive Analytics

Numerous businesses have already started implementing predictive analytics in their business decisions. Let’s take a look at some of the most effective ways to integrate predictive analytics in your business strategies.

#1. Create a Data Science Team

The job of a data science team is to extract value from the data collected and design the most effective solutions based on this insight. A dedicated team will have all the expertise necessary to make the most of the information from the data for an impactful predictive analysis. Professionals from a variety of backgrounds can bring valuable insights to the team from a series of domains.

#2. Profile Your Best Customers

With easy access to valuable data, you can start profiling your best customers. Find out the journey of the customer by going through the purchase history, find out their activities and so on. You can also find out whether they have participated in any product trial, their reviews, the reasons why they have purchased a product etc. Once you have this profile ready, you can easily identify what your customers want and predict their next activities. Additionally, profiling will also help you identify your target consumers easily.

#3. Optimize Marketing Campaigns and Activities

With predictive analytics, your team can dig deep into the previous marketing campaigns and their results, present trends, customer preferences and other important factors to create an effective marketing campaign. Instead of creating one based on the benefits of the products and services that you are promoting, it is important to understand and analyze the market well, identify what works and create a campaign accordingly.

#4. Choose the Right Price and Discount

Prediction analytics will help in accelerating the creation of the sales pipeline by enabling you to set the price of your products and services appropriately. Valuable data can help you predict the prices that would attract the maximum number of buyers while generating profit for your business.

Data enables you to understand your customers well, thus enabling you to promote the products and services by giving out well-planned and customized discounts.

“There is no sector that won’t benefit from predictive analytics. And not just predictive but prescriptive, too,” Jason Gordon, partner at Deloitte pointed out, “Millions of decisions get made every year that would benefit from a predictive modeling capability. It can help optimise pricing processes and promotions. Often it’s impossible for a human to keep on top of all of this, so averages get applied and specificity gets lost.” He also went on to say, “Rather than starting with a list of coupons, you can start instead with the customer and deliver really compelling offers.”

#5. Calculate the Lifetime Value of a Customer

An extensive collection of data can help you determine customers’ contribution margin accurately. Data regarding your customers’ browsing history, present profitability etc. can be quite helpful in calculating the future revenue of a customer. This will also help immensely in designing your future products and services in a way that is aligned with the requirements of your valued customers.

Giving your customers what they want every time they visit your website will help in retaining them. Additionally, they would also recommend your business to their friends and family, thus increasing revenue generation prospects.

#6. Promote Cross Selling

With the help of the advanced methods of predictive analysis, you would be able to identify what your customers are looking for online. This information can be used to reach out to your prospective clients with the best deals. You can also send them reminders about the products they have chosen but have not made the purchase.

In addition to that, you can notify your customers about attractive offers that are aligned with their requirements. For example, if your customers like a winter coat, you can recommend matching boots based on the customer’s preference and browsing history to go with it. You can also consider providing a special discount on the boot to increase the prospect of a sale.

Collecting Data for Predictive Analysis

The most important part of predictive analysis is collecting data that will help in understanding customer preferences. For this, you would need to identify the most effective methods of data collection that are aligned with your business requirements and the comfort level of your customers. One of the best ways is by providing free WiFi to customers who visit your business premises. This will enable you to accumulate customer data without losing their trust.

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Steven Scheck

Steven Scheck

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