Why Predictive Analytics is Important for Marketing
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Big data and Artificial Intelligence has turned out to be the tipping point for marketers. They have access to tools that are far more insightful and powerful than ever, customer insights backed by data is pushing marketing strategies in new directions and opening new avenues of business engagement. Predictive Analytics has proven to be one of the most effective tactics in enhancing the marketing efforts at every stage of the marketing, right from the sales pitch to the point when a sale is registered.
Why is Predictive Analytics works so well with Marketing
Predictive Analytics is the branch of data science that combines the power of big data and artificial intelligence to predict a possible outcome based on the current and past data (customer data in our case). Predictive Analytics gives us the ability to measure the quality of the predictions, also room to finetune the data points and algorithms to achieve predictions of the utmost accuracy.
Predictive Analytics enhances every stage of the business pipeline. The following are the cases that enforce the notion that it is a game-changing technology for marketing.
Predictive Analytics ranks the state of a particular lead based on the possibility of turning it into a potential conversion. It allows sales and marketing teams to grab each lead as per its ranking and formulate an appropriate strategy for each one.
Targeted Content Division
Predictive Analytics can help you predict the right kind of content to engage a particular group based on various factors such as demography, social status, etc. Once marketers know the variety of content and channel, they can tailor their content creation and distribution. When the audience gets what they want to hear, it leads to higher conversion. In this scenario, a WordPress quiz plugin could be employed to gather valuable insights about audience preferences, refining the content strategy for even more targeted engagement.
Customer Lifetime Value Prediction
Customer Lifetime Value is the measure of a customer's worth to you throughout the entire span of the business relationship between you and him. Predictive Analytics using the historical data of a customer can predict how much business he will bring to you throughout his life span. This profiling helps businesses in identifying new customers who may form a long term relationship with your business.
Customer Churn Prediction
Retaining a customer is far cheaper than acquiring a new customer. Customer churn is bad for business, and predictive analytics can help you assess the churn rate. The Churn rate is the percentage of customers or subscribers who may stop doing business with you or stop using your services. Predictive Analytics can identify early signs of dissatisfaction in a customer and warn the marketing team to realign their marketing and content strategy to keep the customer engaged. Every business wants to increase its growth rate, and reducing churn rate helps them achieve it.
Using the available data, Predictive Analytics can assess the cross-selling or upselling readiness of a customer and maximize profit. For example, if a customer buys a particular product (Jeans) and has a pattern of buying an associated product (Jacket) within a period;
You can market the Jacket soon after he purchases the Jeans and maximize the profit before the opportunity fades or he forgets.
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Understanding the standing of your Product
Based on the customer's purchasing behavior, past purchases, and possible lead engagement data, businesses can assess where their product stands in the market. Brands can know if the product needs remodeling or design future products as per the customer demand to stay relevant in the market.
Using the Predictive Analytics business can avoid pitfalls, reduce risks, and maximize opportunities. With Predictive Analytics, businesses will no longer have to rely on mere instincts. You will have data-driven predictions and decisions to help your business move in the right direction.
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