Is There One AI to Unite Them All?

by | Oct 12, 2017 | ABM, Artificial Intelligence, Business, Deep Learning, How To

You may have an extensive marketing stack, glammed to the max with multiple platforms and the shiniest new tools. Or you may have a relatively simple stack where you want to simply add ABM capabilities as a complement to an inbound marketing platform like Pardot.

In either case, there may be some hesitation on your part about adding a Deep Learning engagement platform to your martech stack. You’re not alone, of course. Some of the questions darting through marketers’ minds apparently include…

“Will I have to do a rip-and-replace of some kind to integrate AI into my tech toolset?”

“Will an AI even work within my stack, what with all the products and platforms involved?”

“Am I going to need to hire a team of data scientists to operate it?”

“Is the cost really going to work for me?”

“Am I going to need a Ph.D. to decipher the results I get from an AI?”

“Will it want its own office? Will it want my office?”

The best answer to all these questions? Doing your due diligence, and posing them to every prospective vendor to find out exactly what their machine learning product delivers.

Answering the big questions

With that in mind, here’s what you should be looking for from a best-in-class AI engagement platform.

Easy integration: A best-in-class AI solution will be SaaS-based, and shouldn’t have any problem sliding into any of the four marketing stack “topologies” broadly identified by Scott Brinker:

Four Topographies

It shouldn’t require extensive and disruptive jury-rigging to work with existing systems, shouldn’t displace existing tools, and can run separately from other platforms “atop the stack” but with clean, seamless integration with your other tools.

No brainiacs required: It’s always a good idea to have a data scientist on board, but your AI tool shouldn’t need constant care-and-feeding; a best-in-class solution will be a truly plug-and-play, “set it and forget it” SaaS solution you can implement almost immediately, and uses intuitive dashboards and simplified UIs to take the burden off the user.

Proven ROI: AI engagement tools have been around long enough that the bluest of blue chips among them should have a track record to demonstrate what you’ll get for your spend, whether in more and better quality leads, more conversions, and other KPIs.

Useful output: The right AI platform will be able to generate reports and visualizations you won’t need a degree from Caltech or MIT to interpret, with insights and results you’ll be able to put to use immediately.

No office necessary: Though you may want to keep Watson from IBM away from the team. There’s a little too much HAL 9000 in that guy, if you ask us.

Is there an AI like this? You know it…

Yes, we’re self-promoting a bit, but the game isn’t rigged: The filters we’ve suggested are legitimate, and a best-of-breed AI engagement platform should be designed from the ground up to satisfy every one of them.

Check out our own solution, which ticks off every box on the list above. Whatever you choose to bring AI capabilities to your ABM efforts, it’ll soon be the price of entry in digital ABM. So you should put your AI evaluation process at the very top of your to-do list for 2018.