Predictive marketing analytics is gaining traction — and will continue to do so — as B2B marketers believe in the perceived benefits: increased program efficiency and returns on marketing investments.

As marketing matures, these predictive capabilities give B2B marketers insights into a company’s purchase propensity – including the individual members that comprise the purchase process.

When evaluating predictive marketing analytics vendors, be sure to ask these questions:

How does your offering turn predictions into actions?

  • How do you connect or integrate internal and external data?
  • How do you empower end-users to model?
  • What recommendations does the solution provide to B2B sales and marketers?

How does your predictive marketing analytics solution increase the effectiveness and efficiencies of marketing programs?

  • How does your solution measure results?
  • How does your solution identify buyers that are ready, willing and able to purchase?
  • Why are your solution’s segmentation capabilities unique?

How is your predictive marketing analytics solution more sophisticated than lead scoring?

  • How does your solution align and deliver more targeted messages to each persona at each stage of the buying process?
  • What firmographics, techno-graphics, business-buying activities, and social cues does your solution include and how does it internalize them?
  • How does your solution incorporate machine learning to analyze activity on my website, other sites and social media platforms?

The top three areas B2B sales and marketers look for the impact of predictive marketing analytics on their business are:

Prioritization of leads and opportunities

  • Minimize the energy spent on low-priority leads
  • Maximize the time spent on leads and opportunities with a high propensity to purchase
  • Identify and facilitate engagement into accounts that are not on the radar but should be

Hyper-segmentation – create homogeneous segments

  • Focus messaging by identifying key attributes for each persona and buying stage
  • Create relevant and meaningful sales plays for engaging dialogue
  • Drive content strategy to focus resources on content that supports sales and marketing to attract, engage and drive opportunity through the sales pipeline

Marketing and Sales Prospecting

  • Helps identify total addressable, served and target market – supports territory planning, ABM and demand generation
  • Enables new market expansion – existing products in existing markets and new products in new markets
  • Advances account-based marketing by identifying

Challenges for Predictive Marketing Analytics

  • Data accuracy, quality, and capability claims by vendors
  • Accurate, complete, timely, third party data
  • A UX for sales and marketers to truly do model development and management exists in PowerPoint but not reality
  • Perdition algorithms are still more focused on the “what and less” than on the “how”
  • Successful implementations still require professional services or customer onboarding – a customer on the phone, video conferencing or on-premise dialog to make it work

Predictive marketing analytics is not going away. Although providers of Predictive Marketing Analytics for B2B marketers have moved past their early stages, it will still take about ten years for these solutions to become common. However, B2B sales teams and marketers who leverage these tools today will elevate their sales and marketing efforts, giving them a strong edge over their competitors.

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