The surface mechanics of lead generation — the forms and follow-ups — haven’t changed much in years, but the volume, velocity, and complexity of data interactions have changed dramatically.
But modern lead gen is built on automated nurture sequences, AI scoring models, and predictive analytics, making the infrastructure behind the data more vital than ever.
In this episode of Conversations with MarTech, Jason Gladu, chief operating officer at Convertr, discusses why successful modern lead generation strategies must treat data quality as a precondition rather than an afterthought.
The costs of neglecting your data are too high, and include significant risks, including compliance issues like GDPR violations and “media waste,” where sales teams waste expensive time pursuing non-existent leads.
You don’t want to learn the hard way what happens if AI tools pick up unverified or synthetic data or your company targets individuals without proper consent.
Episode guide
1:04: Meet Jason Gladu
1:46: What’s changed about lead generation in the past 15–20 years?
4:21: What does a successful modern lead gen strategy looks like, and what prevents businesses from reaching it?
8:47: The risks and rewards of AI in lead generation
13:12: Where to start if you’re unsure of your data quality
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