Let your AI feed on the data to create more accurate predictions

Like the world Revenue teams are being reopened and unleashed to achieve growth goals, and many B2B sellers and marketers are wondering how best to prioritize potential client accounts. Ultimately everyone wants to achieve predictable revenue growth, but in turbulent times – and with shrinking budgets – it may seem like a distant dream.

Lower budgets likely mean that you will need more accurate targeting and higher win rates. The good news is that your revenue team will likely already collect tons of lead data to help you improve account targeting, so it is time to put this data to work with AI. Using big data and four basic AI-based models, you can understand what your prospects want and successfully forecast revenue opportunities.

Big data and CDPs are the first steps to obtaining account insights

Capturing and manipulating big data is essential to know everything about the forecast and the best positioning of your solution. Accurately targeting your campaigns and buyer trips requires more data than ever before.

Today’s marketers rely on Customer Data Platforms (CDPs) to handle this massive amount of information from various sources. CDPs allow us to mix data together and clean it up to have a single source of natural data. We can then use AI to extract meaningful insights and trends to drive revenue planning.

This single source of truth also allows marketers to dive into the ocean of accounts and split them with similar traits. You can break it down into industry, location, buying stage, intent, and engagement – any combination of factors. When the time comes to bring prospects to your beat, you’ll have segment-specific insights to guide your campaigns.

The AI ​​realizes data-driven insights

You may find that your data ocean is much deeper than you expected. While converting all of this data into a single source to gain actionable insights, you will also need the right resources and solutions to convert raw data into highly targeted potential outreach.

This is where AI shines. Artificial intelligence and machine learning enable revenue teams to analyze data for historical and behavioral patterns, and choose the ones that are most relevant Statements of intentPredict what will drive a potential customer during the buyer’s journey.