Using AI, data analytics, and machine learning to anticipate customer behavior and thus optimize sales and marketing campaigns?
It doesn’t sound like something out of a sci-fi movie anymore. It’s a real, effective way to improve your marketing strategy and is reflected in the term predictive marketing. The term is relatively new, but the concept has been around for decades.
Businesses that use predictive marketing enjoy increased sales and more efficient spending. But if we dig deeper, predictive marketing is a powerful tool for companies to stay a step ahead of customer trends and desires. And with the tough competition we see today, this is probably the only way to remain competitive in the market.
Here’s a brief overview of predictive marketing, how it works, and how it can take your business further.
Predictive marketing: definition
Predictive marketing is used to anticipate the likely behavior of customers based on their past buying behavior and demographic data. It helps businesses target customers with relevant, personalized ads, leading to optimized conversion rates and improved ROI.
Let’s say you own a company and have a customer list. With predictive marketing, you take all that data and crunch it to determine which customers will most likely buy from you again. Then you target them with specific offers.
But predictive marketing doesn’t just stop there. You can also use it to determine which customers are most likely to churn, so you can take steps to prevent that from happening and improve your retention rate.
The early days of predictive marketing and how it has changed
Predictive marketing has emerged in response to the increasing use of data. It’s a powerful tool, but it’s also a complex one as it requires sophisticated algorithms and data-mining techniques.
However, if we look back into history, we’d see the concept of predictive marketing has existed for years.
The first form of predictive marketing was called market segmentation. This technique was used to identify different groups of people who share common characteristics and can be targeted with similar messages.
Over time, marketers began to use more sophisticated techniques, such as data mining and customer profiling based on customer lifecycle marketing. This allowed them to predict what customers might want or need before they even knew themselves.
As technology has advanced, so has predictive marketing. Today, you can use predictive analytics based on past data to identify patterns in customer data and make predictions about their future behavior.
Advantages of predictive marketing for your business
The benefits of predictive marketing are clear: increased sales and growth. But it can take businesses further by helping them understand their customers more deeply.
For example, with predictive marketing, you can:
- Make more informed decisions about media planning and buying, which results in more efficient use of marketing resources.
- Have greater accuracy in predicting customer needs, which leads to improved customer retention rates. Using this data, you can target your customers with relevant messages, make specific offers that complement their purchase history and interests, and explore cross-selling and upselling opportunities.
- Improve customer service by providing faster insight into your customer’s needs.
- Create a more individual experience for your customers, leading to a substantial, loyal customer base.
- Know your customers’ mood by surveying social media and checking out tendencies that allow you to get ahead of potential backlash before it gets out of hand.
- Timely and proactive optimize your websites.
- Enhance targeting capabilities by better qualifying and prioritizing leads, which helps segment the leads based on the likeability of them making a purchase.
All these benefits underscore the importance of predictive marketing in achieving increased sales and overall success for your business. This explains why 91% of top marketers are either already using predictive marketing or are committed to doing so.
How does predictive marketing work?
Predictive marketing is done by analyzing data sets, which can be either internal or external. Internal data sets are generated by the company itself, while external data sets are collected by outside agencies.
Predictive marketing uses past customer data to create models that can predict future customer behavior by analyzing factors such as purchase history, demographics, and a bulk of other valuable data. Every time customers interact with campaigns, move down the sales funnel, and convert, marketers need to track their engagement and create a predictive model:
- The cluster model is designed to segment the audience based on past brand engagement, purchases, and demographic data.
- The propensity model evaluates the customer’s likelihood to convert, act on an offer, or disengage.
- The recommendations filtering model evaluates past purchase history to understand where there might be additional sales opportunities.
Once the predictive model is created, it can be used to identify which customers are most likely to churn, buy a particular product, or respond to a specific campaign. With predictive marketing analytics, you can harness Big Data’s power to understand your customers better and predict future trends. It can help you identify opportunities you may not have otherwise been aware of.
Predictive marketing is the next step in the evolution of marketing. It uses data analytics to predict customer behavior and target them with personalized offers.
As technology evolves, predictive marketing will likely become essential to any business’s marketing strategy. By predicting what customers want or need in the future, companies can create products and services tailored to their needs that will help drive sales and establish long-term customer relationships.