One of the sales and marketing technologies I’m most excited about (along with account-based sales and marketing) is the whole predictive area. At a simple level, predictive takes existing contacts and opportunities and scores them against a dynamic model based on other contacts and opportunities that became customers. Put another way: find great-fit companies that look like our existing customers so we can target them.
Account-based sales and marketing platforms (see SalesLoft and Terminus) solve the major problem of running programs in a scalable manner against hundreds (or thousands) of target accounts. Traditional marketing, and sales as the opportunity progresses through the funnel, casts a net, sees what is caught, and then works the qualified leads. Now, as a more modern approach, account-based sales and marketing goes spear fishing and proactively seeks out best-fit accounts based on a number of dimensions. Only, there’s often not an easy way to find and refine best-fit accounts — enter predictive technologies.
Here are a few thoughts on predictive sales and marketing technologies:
- As more companies implement account-based sales and marketing platforms, predictive systems become more important to find and analyze best-fit accounts.
- Predictive sales and marketing systems are clearly in the path of revenue.
- Machine learning, a subset of artificial intelligence, is now more accessible with the advent of systems like AWS Machine Learning, making predictive systems more powerful.
- Finding lookalike companies requires technology. Combing through billions of records by hand simply isn’t possible.
Look for the category of predictive sales and marketing systems to grow fast as the technology crosses the chasm and becomes more well known.
What else? What are some more thoughts on predictive sales and marketing technologies?