Aman Naimat is SVP of Technology at ABM solutions vendor Demandbase, and former co-founder and CTO of Spiderbook, the AI-for-B2B specialists Spiderbook, acquired by Demandbase last year.
What are the main ways AI/machine learning will impact marketers and their work in the next year or two?
Over the course of the next few years, AI/machine learning will allow for a more complete view of the customer, smarter budget allocation, and a hyper-personalized approach to marketing/sales conversations with prospective buyers. AI will be able to provide and create unique content in context to each buyer, their pain points, preferences, interests, and goals.
In summary, what will be the long-term impact of AI/machine learning on marketing?
Long term, we will see AI reduce wasted marketing spend (e.g. spam and irrelevant ads), and create the opportunity for marketers to have one-to-one hyper-personalized conversations with buyers at scale.
How is AI/machine learning incorporated in the work you’re doing?
Demandbase recently launched the industry’s first AI-based B2B website personalization solution: Site Optimization. It automatically recommends specific content and high-value pages to each visitor based on AI-driven insights. By combining AI and an Account-Based Marketing focus, Site Optimization delivers hyper-personalized content based on the individual and the company.
In your experience, is AI/machine learning already affecting what brands do, or are awareness and adoption still very limited?
AI is an area where B2C is leading B2B by a decade, but there is some B2B website personalization technology that is bridging that gap. Today’s AI technology can provide next best action, and recommend and create new personalized content online and offline. What’s lagging behind, are AI technologies that can provide more transparency and the data science talent required for mass adoption of this technology.
