B2B Audience Targeting With Intelligence Not Intuition
How confident are you in your B2B audience targeting?
Are you willing to bet your next quarter on it?
Until now, most audience targeting has relied on a combination of calculated guesses and data that could best be described as ‘incomplete’. Using job titles, NAICS and SIC codes, and company headcount are di rigueur for most B2B marketers, because that data is what’s available – not because it’s accurate. But relying on this incomplete data means that time and resources are wasted on poor-fit prospects who will never become customers, while missing good-fit targets that fall outside the scope of the targeting parameters for one reason or another.
This state of affairs is great for companies that sell ad space – in casting a wide net, you’re spending more – but it’s bad for marketers and the companies they work for. It’s wasteful – it drags down ROI and conversions, and balloons customer acquisition costs.
There is a better way to do this. Using high-quality, ‘clean’ B2B data, built for artificial intelligence computing, marketers now have access to audience targeting that accurately identifies best-fit prospects who are in-market. It’s not magic, it’s data science.
In this whitepaper, we break down why traditional targeting is a fundamentally broken process – and share the specifics of how AI is revolutionizing B2B targeting.