20 Reasons Why B2B Marketers Need Predictive Marketing

Predictive Analytics is the next frontier for marketers and here are 20 reasons why. The most cutting edge companies are spending more on analytics and using it to drive more revenue. With only limited data at hand, are B2B marketers ready?
 
 
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CMOs Answer Challenging Questions with Analytics

Today CMOs are realizing the value of data-driven marketing and are putting their money where the data is. Here are some statistics you might want to share with your marketing team.

  • 58% – The predicted increase in Marketing Analytics budgets in the next three years
  • 60% – The share of CMOs that are using analytics some of the time or more to answer their most challenging questions
  • 4.3% – The share of CMOs who use data and analytics all the time to solve their most challenging questions

 

Traditional Lead Scoring: Too Complex

Traditional lead scoring was supposed to be the solution to find sales-ready leads in theory, but does not really work as intended in practice.

  • 57% – The share of Marketing Automation users who use lead scoring, to find those sales-ready leads
  • 40% – The share of marketers who think that lead scoring is the hardest marketing tactic to execute

 

B2B: Too Many Leads, Too Few Deals

B2B marketers are struggling to find the needle in the haystack to find buyers. Here’s what B2B marketers are currently struggling with in their database.

  • 95% – The share of leads that are not sales-ready
  • 8% – The share of leads in a company’s database with high likelihood to convert
  • 32% – The percentage of the database that contains great companies, but the wrong prospect
  • 46% – Proportion of database with companies that have low probability to convert
  • 13% – The share of the database that contains old and bad data

 

Predictive Analytics Leads to Higher Engagement

By relying only on CRM data, B2B marketers are not taking advantage of the wealth of data from the web—which can increase their performance 5X.

  • 10 – The average number of data points on every lead in a company’s traditional lead scoring model.
  • 1,600 – The number of data points on every lead that you can find online
  • 200-400 – The number of data points used in a Predictive Scoring model
  • 5X – The average lift in engagement from using B2B predictive marketing

 

Ways B2C are Already Winning with Predictive Marketing

Companies like Amazon and Netflix are already using Predictive Marketing to drive more revenue. Here are some use cases that has probably touched your life in one way or another.

  • 35% – The share of Amazon’s revenues generated by its recommendation engine
  • 1,000,000,000 – The number of product recommendations delivered daily in six out of ten top US online retailers
  • 75% – Share of users who select movies based on Netflix’s recommendations
  • $1,000,000 – The prize for the team of engineers who managed to boost the performance of Netflix’s recommendation engine by 10%
  • 33,000,000 – The number of viewers whose data was analyzed to create the hit series “House of Cards” by Netflix
  • 3 – The number of Emmy awards won by “House of Cards”
Jacob Shama

 

Dr. Jacob Shama is Co-Founder and CEO of Mintigo, which provides customer intelligence to the world's leading B2B companies. Dr. Shama has more than 20 years of executive experience in the fields of Information Technology and Communications, specializing in big data.