This past Dreamforce Salesforce released its artificial cloud (AI) embedded into the core sales and service CRM. Missing from the discussion was how AI will play an ever increasing role in marketing, specifically Pardot—Salesforce’s B2B marketing automation platform. AI is slow to come to marketing space, but will change the nature of the work that the armies of email campaign specialists, demand generators, and content producers do. Marketing automation was the first revolution in marketing; AI is the second.
Before we begin it is really important to define AI as it relates to marketing. It’s also important to define marketing automation. Often, I think we confuse AI with automation. AI is not automation. The lines blur here, but there is a distinction. In a recent e-book from Salesforce I believe an incorrect example of AI is used.
Marketing Automation: A “bot” is used to automatically send an communication to further a prospect’s journey toward becoming a customer (or repeat customer).
Artificial Intelligence: Marketing automation is leveraged. Based on results of communication messaging content (wording of emails, subject lines, personalization), and time of sends are predictively altered and optimized. From a larger perspective AI will also optimize the entire journey including the number of emails sent, and handoff point to a sales rep.
I believe AI as it relates to marketing is best described as,
“Market research” once relied on taking the temperature of broad chunks of society. AI enables marketers to focus at a granular, individual level. This depth of audience insight will allow marketers to create and test campaigns virtually, ensuring the ability to target and convert audiences more effectively by surfacing the right offer to the right person at the right time.
In the context of Pardot email campaigns in Engagement Studio AI can be applied in a variety of ways. There are triggers in Engagement Studio that listen to certain prospect actions including email opens, link clicks, file downloads, and form fills. In the future, I envision Pardot predictively suggesting which listeners to use depending on the goal/type of email campaign, and where the prospect is in the funnel. For example, an email open may all that may be needed to advance a prospect early in the funnel, whereas a file download may be necessary later in the funnel to handoff the prospect to sales. In addition, Pardot could also predictively take actions in an Engagement Campaign which include sending an email, adjusting a prospect score, or handing off to sales.
The core problem AI seeks to solve is to take away a lot of the guess work and need to optimize, and instead provide insights. In 2012 I worked at InsideSales.com helping build the predictive Neuralytics product, which took anonymized data from our customers’ data (such as when a prospect answered their phone) to predict the best time to call a prospect. For marketing, there is a great opportunity for Pardot to aggregate engagement studio campaign data to predictively help marketers improve their campaigns and recommend a next best action based on previous successes.
Because Pardot is integrated so tightly with Salesforce CRM Opportunity data, marketers are truly able to market to achieve profitability and sales results via AI. What’s really great is that you don’t have to repeat a campaign mistake that another marketer made (who works at a different company who also happens to use Pardot). I often think of the Markstrat simulation course I took in college where you would add product features (differentiation), and define your market segment to successfully position your product. Each step in this simulation you would receive the sales results determining how successful your product positioning performed, and then decide what changes you would make for the next round. There were a lot of random variables that affected the results too (at InsideSales.com we learned that weather, sporting events, and traffic had large effects of contactability over the phone). In the past, marketing occurred within the confines of your company and there was a lot of trial-and-error, which resulted in missed opportunities. AI really lets you hit the ground running with the accumulated knowledge of the platform.
In Pardot, AI will be specific to buyer personas. As marketers we know that some campaigns and messaging work better than others for different list segments. AI will take this personalization to the next level at the per person level, not list segment. In Pardot we use Prospect Grade to indicate fit for our offering and Prospect Score to indicate readiness and intent to buy. I imagine Pardot will begin to build and aggregate their Prospect Profiles in mass and and enable AI as a competitive advantage against other competing marketing platforms. Building an aggregate of prospect profiles with recommended prescriptive actions will be a first step for AI. The second step will be much more individual. Might I be so bold to say that list email marketing and segmentation is dying in b2b marketing. Segmentation size is moving to a list size of 1 as we already experience in our shopping with Amazon.
The future of marketing is bright and exciting, albeit different! Happy marketing!