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Marketers collect data, conduct analytics, and make decisions based on it. That’s a great start but how can you get even more value out of your data? The solution is predictive analytics which allows you to anticipate future events and not just analyze the past ones.
Why Use Predictive Analytics in Marketing?
Marketing has become highly personalized and dynamic. Its goal is not just to attract customers but to understand each user, their desires, and consumer behavior. Predictive analytics in this case helps to predict the context of the needs and desires of customers and determine the best way to deliver information while building a unique personalized approach.
Today, numerous companies are already leveraging predictive analytics marketing solutions and growing business by leaps and bounds.
Benefits of Predictive Analytics Marketing
Customer social norms have certainly changed and as a result, expectations have escalated. This is where forecast models come into play helping marketers get insights into the future development and understand what channels work and how their numbers evolve.
We’ve highlighted some of the ways businesses can benefit from leveraging predictive analytics in e-commerce:
Individual Approach to Potential Customers
In the fight for leads, those companies that can offer their audience a customized approach and real benefits win. Through lead scoring, you can make a targeted and the most relevant offer for a selected group of customers.
Improved Customer Experience
Using ML and predictive analytics for business enables you to classify your customers based on any number of variables. With this data, you get more opportunities for cross-selling and upselling, thereby improving customer experience and increasing company profits.
Predicting Ad Effectiveness
If marketers know how a particular advertising event will pay off, it’s easier to plan the budget, turn off ineffective advertising channels or campaigns and launch new ones.
Implementation of these advanced algorithms will help companies run more effective marketing campaigns, leading to lower costs and higher revenues.
Application of Predictive Analytics in Marketing
Understanding customers and making data-driven decisions will help provide personalized offers, advanced performance, and upgrade targeting. Here are the most successful ways to apply predictive analytics in modern marketing:
Predictive analytics marketing solutions can dramatically improve the performance of email marketing campaigns. AI implementation provides abandoned cart recovery, drip marketing, advanced personalization, post-sales and back-stock emails, new stock notifications, and more.
As a result, email personalization increases conversion rate and engagement, leading to 6x higher transaction rates over non-personalized messaging.
Analysis of customer behavior (recurring purchases, intervals between purchases, seasonal changes, etc.) contributes to more personalized product recommendations and successful cross-selling and upselling. This allows businesses to accurately predict when a customer is ready to buy a certain product and what else might be of interest to them.
Lead scoring is one of the main applications of predictive analytics for business. Marketers can contact the client at the right time with the right offer and close the deal by analyzing user actions and determining whether a lead is ready for conversion.
It enables marketers to understand which channels generate conversions and track their effectiveness. Using this information, they can optimize the ROI of marketing campaigns.
Customer churn is a vital metric for a subscription-based business. Customer behavior analysis reveals the signs that a customer is about to leave, which helps businesses better meet customer needs and take action to retain them.
Tips for Efficient Predictive Marketing
Getting immediate results isn’t a piece of cake – you have to consider a number of factors. Thus to speed up your mastering predictive analytics marketing, we’ve prepared a set of helpful tips:
Its algorithms require huge amounts of data to get accurate results. The more information the algorithms process, the more intuitive and accurate their predictions will be. Therefore, getting reliable results may take longer than you would like. Still, the wait is worth it.
Integrate Data from Different Channels
When building prediction models, integrate data from different channels and even departments (customer service, sales, finance, etc.). This will increase the relevance of the results and may give unexpected valuable insights.
Invest in Custom Solutions
Out-of-the-box solutions may not bring the expected results. Since the investment will be significant anyway, opt for a custom solution adapted to your needs.
Find the Happy Medium between Personalization and Privacy
This branch of advanced analytics can’t function without customer data, but obtaining it requires informed consent. To strike a balance between personalization and privacy, collect only the information you need and focus on cybersecurity. This approach will satisfy both your and your customers’ needs.
Hire Data Analysts
To use your tools to the fullest, it’s better to work with qualified specialists. They know how to properly process and analyze data.
Update Prediction Models
If you update your models regularly, you can test strategies and respond quickly to changes. In addition, it will give you an upper hand over competitors who build strategies based on historical data only.
With the development of AI and ML, predictive analytics has grown dramatically and will go on extending its power. Those savvy marketers who utilize predictive marketing solutions are more likely to outperform competitors and increase profits. Thus, companies that know their audience well, understand their needs and respond to their behavior will always be a step ahead.