Introduction:

Predictive marketing allows recommendation solutions to leverage machine-learning algorithms to deliver consumers highly researched, specifically targeted product recommendations, wherever they engage with a brand.

In today’s ever-changing, fast-paced marketing environment, consumer trends and behaviors can change at a moment’s notice. It’s only fitting, therefore, that the next wave of marketing technology solutions focus not on what consumers are doing, but what they will do.

The goal of using data as a marketer is simple: You want to reach the right audience, with the right message, at the right time. When it comes to sophisticated targeting, historical data can only take you so far.

What Are Some Use Cases for Predictive Marketing?

• With the help of predictive analytics, you can deliver a more personalized experience to your prospects and customers. Here are a few examples of predictive-marketing use cases:
• Telling you how interested a prospect or customer is likely to be in a specific promotional offer
• Predicting how likely it is that a new customer will become a loyal customer as a result of certain email campaigns, product promotions, or pricing incentives
• Identifying the customers with the highest potential lifetime value (e.g., those customers who will consistently spend the most money over a long period of time)
• Preventing churn in your customer base by detecting the signs of dissatisfaction among customers, identifying the customers who are at greatest risk of leaving, and providing insight into the actions that you need to take to keep them happy
• Determining the products to cross-sell and upsell that specific customers are most likely to buy
• Providing insight for the best combination of products to recommend to target prospects and convert customers
• Segmenting your email list to send messages tailored to customers’ interests and needs by using predictive analytics along with automation and customer relationship management (CRM) tools.

Fast forward to now and the tools is becoming more and more accurate, the algorithms more sophisticated, and the results both automated and improving.

Here are the three factors that has led to the accelerated growth of predictive marketing:

Massive Amounts of Data– purchase history, behavior, and demographic data are now available from a multitude of sources.

The Ubiquity of Access– access streaming data via virtually every tracked and connected resource is providing rich, real-time activity.

The Simplicity of the Cloud– immense computing power via the cloud, new bid data database technologies with rich and sophisticated algorithms are helping drive innovation in the predictive marketing field.

Why Marketers Need Predictive Marketing Technology:

As consumers become more tech-savvy and brand aware, they are also becoming more cognizant of their options. Whole new avenues, brands, and channels are now available, and traditional retail brands must be able to keep up with these changes. Predictive technology provides the tools necessary to make the leap into personalization, and fully join the next generation of marketing and consumer engagement.

Marketers can leverage predictive technology to Digital Marketing:

• Increase revenue and marketing ROI. Consumers are more likely to respond to personalized messages and content specifically tailored to their buying preferences. With predictive technology in place, marketers turn past shopping trends into future buying experiences.
• Create return customers by building a culture of brand loyalty. Customers know when they’re being treated as an individual. When marketing teams invest the time and resources into creating 1-to-1, personalized marketing experiences, the return is brand-loyal, repeat customers who are satisfied with their customer experience.
• Positively affect the customer experience across the entire buying journey. Predictive solutions rely on a huge amount of customer data, which in turn influences a myriad of other marketing strategies, from automation solutions to detailed reporting and insights. Customers are happy to provide personal data in return for the personalized shopping experiences that predictive solutions can readily provide.
• Build true multichannel customer journeys. Today’s consumers are no longer just engaging with an online brand via a website. Predictive analytics combine the various facets of web, email, and mobile to create holistic shopping experiences that are consistent no matter the channel or platform.

Final Thoughts:

To Summarize Predictive Marketing is to

• Find the Right Audience
• Optimize Conversion
• Generate More revenue.

The good news is that getting started with predictive marketing doesn’t require a huge investment in sophisticated software. Plus, companies of all sizes can take advantage of predictive technology today. It wasn’t long ago that only big-enterprise systems were the providers of predictive analytic solutions. Now, most marketing technology companies offer some level of predictive marketing among their products. In addition, there are software-as-a-service predictive solutions available that can integrate with your current CRM and marketing-automation platforms.

“Assess the requirements, Explore the opportunities and Implement the changes and Succeed – Sky is the limit”.