In this special episode of B2BNation live from the 2017 RevenueSummit in San Francisco, we talk with Bastiaan Janmaat, CEO of DataFox, about artificial intelligence (AI) and account-based marketing (ABM):
- How to practice data-driven ABM
- The role of Artificial Intelligence in ABM
- The real difference between AI and machine learning
Below are a few highlights from our conversation:
Start Using Data in Your ABM Campaigns
- “Make sure your CRM is clean. Make sure your data is correct and the business data is up to date. A quarterly refresh is advisable.
- “Try to find a couple of unique factors to describe your best customers. Start simple, and ask the sales rep what signals get them excited when an account is near to close.
- “Signals or events that show timing is right. While customers might not be interested right now, they may show signals that they’re ready to buy in a couple of months.
“You don’t have to do really complicated things here. We went to our salespeople and asked what got them excited. They said that when the customers featured a bunch of logos that matched with our data accounts, they used that as a signal that we could close with them. We went through different levels of sophistication, from manual searches to freelance networks to finally building a data tool that scrapes customer websites for logos. It doesn’t have to be complicated at first, but you can use the signals to build your processes.”
Artificial Intelligence in ABM
“AI isn’t a silver bullet. You can harness it to run some processes more efficiently, but you have to start out with a roadmap of a specific problem you want to solve.
“We’ve used AI to look at a company’s customer base and compare that with other companies that reflect a similar landscape and the deals they’ve closed in the past. We use AI rather than just a statistical model, because we need to keep adding more information to the model. So when an account isn’t a good fit, we use that information to give us more exact suggestions in the future. And this can apply to both inbound and outbound.”
The Difference Between AI and Machine Learning
“Machine learning is a type of AI that uses a statistical model that improves over time and can be shaped in various ways. Supervised machine learning involves providing new input and data points that improve the model over time.
“What’s funny is that the definition of AI and machine learning changes with the level of technology. At one point, it involved scanning a document and recognizing text and making a Word document out of that, but now we just call that scanning, not AI.”
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B2B Nation is a podcast for B2B sales and marketing professionals, featuring expert opinions and advice on the most important topics in the industry. Check out our other episodes on SoundCloud, or follow us on Twitter: @Technology_Adv.