Why your website is failing ABM (and how to fix it with behavioral signals & data lakes)

Shownotes

Account-based marketing is not a LinkedIn campaign. It is not gated content. And it is not a list of MQAs flooding sales every week.

In this episode of the OnBase Podcast, Chris Moody sits down with Radoj Glisik, SVP of Digital Strategy & Design at Altudo, to rethink ABM through the lens of customer experience, behavioral psychology, and digital infrastructure.

Radoj explains why most organizations approach ABM too late, after brand redesigns, after websites are built, and without a unified data strategy. He introduces the concept of “evaluation patterns,” shows how digital experience platforms (DXPs) can detect buying group behavior long before sales gets involved, and explains why intent data without behavioral grounding is incomplete.

They also explore:

• Why ungating content increases success rates 
• How to structure a marketing data lake for ABM 
• The shift from persona-based marketing to buying-group experiences 
• Focal and temporal personalization 
• How LLMs are changing traffic patterns and reference content strategy
  

If you want to move beyond campaigns and build a true account-based experience engine, this episode is essential listening.

Best Moments

• 02:03
  Why most companies misunderstand what ABM actually means
• 05:04
  The biggest mistake companies make when building websites without ABM in mind
• 07:54
  A website’s first responsibility in ABM: listening for engagement patterns
• 17:40
  What an “evaluation pattern” looks like before an RFP is issued
• 22:09
  Why intent data alone doesn’t work
• 23:40
  How to avoid overwhelming sales with meaningless MQAs
• 25:08
  The AWS evaluation pattern discovered during a training session
• 27:38
  Why GA4 is wildly underutilized for ABM hypothesis testing

Key insights from this episode

• ABM should be embedded into digital experience from day one, not “plugged in” after a redesign. 
• Websites must listen for behavioral patterns, not just collect leads. 
• Evaluation patterns (compressed, multi-IP research bursts) often signal late-stage buying activity. 
• Intent data works best when validated against first-party behavioral signals. 
• A lightweight marketing data lake is often more practical than a full enterprise data overhaul. 
• Focal personalization removes unnecessary content to guide buying groups down clear paths. 
• Temporal personalization reduces over-automation and improves engagement quality. 
• Ungating content often increases engagement and conversion rates significantly.

Quotes

“Most websites have too much information for too many people.”

Tech recommendations

• n8n
• Google Analytics 4 (GA4)
• Google Notebook LM

Resource recommendations

Books:

• The Visual Display of Quantitative Information by Edward Tufte
• Visual Explanations by Edward Tufte

Shout-outs

• Gurjot Sidhu, Chief Customer Insights & Analytics Officer at M&T Bank
• Varun Nehra, Head of Value Engineering at Netlify

About the Guest

Radoj Glisik is a battle-tested CX, branding, marketing, and content strategy executive. He has delivered significant results in market research, new market entry, digital product strategy, information architecture, advertising, operational and process design, customer experience, and user testing. Radoj specializes in advanced personalization using behavioural psychology and the JTBD framework.

Connect with Radoj.