How can Predictive Analytics Improve B2B Marketing

September 29, 2022, Comment off

How can Predictive Analytics Improve B2B Marketing

A rapidly changing marketplace creates ambitious imperatives for stakeholders. Over one-third of senior decision-makers, especially marketers, rank the changing market environment as one of their top challenges. It is because the data collected in their system becomes outdated with growing customer needs.

Further, there’s already a missing connection between metrics and business goals. It is where predictive analytics comes into play.

What is predictive analytics marketing

Predictive analytics in b2b marketing uses data, data-backed algorithms, and machine learning to identify the likelihood of prospects, leads, and eventual conversion. B2B marketing analytics enables brands to study user persona, purchase history, etc., to assess the likelihood of them becoming prospects and customers. Predictive marketing is not just about gathering information but also using the data to understand the things that are yet to happen.

Let’s look at nine ways how predictive analytics helps boost B2B marketing and practices.

Nine ways predictive analytics boosts B2B marketing

Predictive analytics is useful in multiple ways. From optimizing landing pages to running personalized ads, predictive marketing holds multiple capabilities and uses cases. We took the liberty to list a few for you.

1. Identify what buyers want

Knowing where your prospects are will help you determine where to go next with your content strategy, what events to participate in, and how to improve your digital marketing results. Predictive marketing and data analytics can help you figure out the latest trends in of the buyer group’s browsing habits, purchase habits, etc.

2. Lead prioritization

Predictive marketing empowers sales conversion. The algorithms understand emerging needs and buyers’ interests from how they consume content and data from various websites. This helps marketers determine their buying stage to prioritize them using a scoring method.

3. Net new leads

Predictive analytics can help you understand the common attributes associated with your existing (or high-value) leads.

Your automated campaign analytics can identify the same attributes in any new audience and engage with them using your marketing message. It helps you import new leads from an external customer data supplier.

4. Customer churn prevention

Predictive analytics helps prevent the churn caused by dissatisfaction. It can help identify the customer segment on the verge of leaving. Marketers can thus make necessary modifications to tweak their offerings after addressing the customer’s pain points. It leads to keeping customers happy and eventually protects the revenue.

5. Augmented customer data

The more you know about the buyers, the more you’ll be able to tailor your messages to meet their needs. Predictive analytics couples the known information about the buyers and uncovers customer traits. It can further reveal emerging interests.

6. Real-time CRM segmentation

Predictive analytics can help you segment your growing customer data with minimum effort. It allows you to target the right leads with the right message. It results in more successful campaigns focused on prospects who are more likely to make a purchase.

7. Define the next-best action

Predictive marketing helps you determine what your future marketing approach should be. It helps you plan the course of action for the coming week, month, or quarter. It gives a complete picture of your short-term and long-term marketing goals.

8. Content recommendation

By tracking multiple content metrics like bounce rates, click rates, etc., predictive analytics can help you figure out what type of content works and what doesn’t. Marketers can plan their upcoming content accordingly. Besides, predictive analytics can also help you deliver personalized content recommendations to your prospects and customers.

9. Retargeting buyers

Retargeting allows brands to remarket their offerings based on multiple aspects such as purchase intent, trends, customer needs, etc. Brands can repurpose your content, ad copy, etc., based on your previous campaign data.

Unlock actionable insights through predictive analytics

Predictive analytics is a savior for marketers. You lose a competitive advantage if you keep dodging its adoption. Predictive analytics in B2B marketing is very different from B2C. It requires a more nuanced approach. Which is why data collection, joining and analysis is so crucial in B2B marketing, but it is useless if you don’t take action. Therefore, make sure you do it right.