Editor’s Note: This post is part of a series featuring speakers from the Marketing Artificial Intelligence Conference (MAICON). For more information, visit www.MAICON.ai.
Just like marketers, sales pros are eager to start using artificial intelligence (AI) to be more effective, productive contributors.
Doug Davidoff (@dougdavidoff), Founder and CEO of Imagine Business Development, advises these savvy salespeople at high-growth companies to upgrade their sales strategies. He’s worked with more than 1500 companies ... so he gets what actually works and what does not.
In the following Q&A, we asked Doug to expand on his experience with AI in sales, including use prime use cases and best practices.
Q: Based on your experience, what are some of the most practical use cases of AI in sales?
A: AI is a part of what I refer to as the third wave of the information age.
- The first wave focused on the ability to store data and process data in highly repeatable processes (think IBM mainframes).
- The second wave, marked by the mainstreaming of the Internet, radically changed how people access information and who controls that information.
- The third wave, of which AI is a key part, is just beginning to emerge. For the first time we can utilize computers to truly synthesize, curate and, even, create.
It’s important to emphasize that we’re still in the very early stages of this third wave, so caution is prudent.
Sales is in the center of where AI can and will have tremendous impact. For most of the 20th century (when the professional discipline of sales emerged), it’s been managed from a behavioral perspective. The discipline if fraught with tremendously bad mythology created from bad observation and poor causal analysis (remember “close early and close often” anyone?).
Everyday sales organizations create terabytes of data that lay latent. Selling has always dealt with a signal vs. noise problem. Selling involves multiple complex, dynamic ecosystems that all impact each other. This makes “receiving the right signal” virtually impossible.
There’s a growing suite of AI tools that can dig into the data laying dormant and, without knowing precisely what to look for, find the signal that enables leaders and players to adjust intelligently. The promise of “optimization” is finally coming to sales.
Q: How do organizations know if an AI-based sales solution is right for them?
A: With all respect, I think this is the wrong question. It’s a question that gets sales organizations (and all others as well) in trouble. Your objective should not be to determine if an AI-based solution is the right one, but instead to define what outcomes are imperative and determine what “jobs” are the most important to move towards those outcomes.
AI is a technology and should be treated as all technology (and not just “hi-tech”) decisions should be made. The biggest cost, and risk, with technology is not the price of the tool, but the cost of implementing and managing change.
What’s more, AI is what I like to call a “good to great” technology. AI is all about taking things that are working well and making them work more optimally. But it’s not particularly effective, and can actually be quite damaging, when applied prematurely.
If an organization doesn’t have a well-engineered customer acquisition process, applying an AI solution, no matter how strong or promising, will merely create more chaos at best.
Q: What best practices do you recommend for operationalizing AI into sales processes?
A: Start with a strong process and clear intent. Know the problem you’re looking to solve and define the following:
- How is the problem manifesting itself?
- How important is the problem?
- How will you know what when the problem is solved?
From there, create a series of milestones, or waypoints. Good to great is not a straight-line journey. Never forget, or underestimate, the law of unexpected consequences. A disciplined rollout of such a solution that turns iteration into adoption has the best chance to be successful and to positively impact your business.
Q: What common hurdles do organizations face when it comes to AI and sales?
A: Lack of an effective process and bad data sets. If you have not built a fair level of predictability into your customer acquisition systems, then AI merely adds a significant level of complexity on top of what is already too complex.
The second hurdle is underestimating the level of change that will be required on the part of the organization to take advantage of the solution that AI provides. If you think you’ll add AI, keep doing things the way you did before, and better results will flow, then you will be greatly disappointed (and poorer).
Q: How can these challenges be overcome?
A: The toughest lesson I’ve learned in business is that strategy and innovation are fun and exciting, but success—real predictable success—comes from great plumbing.
Design and engineer your customer acquisition and success systems first. With a strong design, building a strong approach to leveraging the power of technology (and AI specifically) becomes much less mysterious and difficult.
Q: What are you most excited about at MAICON 2019?
A: There is so much noise and FOMO (fear of missing out) surrounding AI today that half the time I feel like I’m back in the 1920s with a bunch of snake oil salespeople (not that I was around in the 1920s). What I love about what the MAICON team has done is that you are neither a shameless promoter or a cynic. You’ve always been, what I like to call, optimistically skeptical.
There is little question that AI is going to have an impact on sales and marketing going forward (I should add there are still a lot of questions about just how that impact will manifest). I’m totally pumped to be with a group of people who are serious about understanding, iterating and improving. We’re still in the pre-game of AI and it’s exciting to share what I’ve learned with a forward-leaning, smart and serious group of people.
Q: What advice do you have for marketers just starting with AI?
A: Remember that AI doesn’t actually change anything. Don’t make the same mistakes we made when the Internet became a thing. Business is still business. Customer acquisition is still customer acquisition. AI simply adds to our toolkit (it doesn’t make the previous toolkit irrelevant). So keep the focus on what success looks like and what’s important.
Oh yeah, and there’s time. If you don’t make a decision today, you’ll have time to adjust before it becomes one of life’s regrets.
About Sandie Young
Sandie Young started at the agency during the summer of 2012, with experience in magazine journalism and a passion for content marketing. Sandie is a graduate of Ohio University, with a Bachelor of Science from the E.W. Scripps School of Journalism. Full bio.