How Einstein brings more intelligence to marketing automation

Posted On by Brian Coles

Ever since Salesforce brought the Einstein Artificial Intelligence (AI) engine to marketing, I have been amazed by the genius level you can now take Pardot and Marketing Cloud to. The volume of data that Einstein can chew on is almost limitless, and the extra intelligence Einstein brings to your marketing toolset is extremely powerful.

Pardot Einstein guides your sales and marketing people in making smarter decisions on who to market to, who to sell to and who to engage with, and when. This last recommendation is very important: if you talk to prospects or customers at the wrong time about your products and services, then the conversation is not going to go down very well. Pardot Einstein is the ability to talk to your prospects at the best time, so when they’re ready for the conversation. That makes conversion much easier, of course.

There are four amazing plug-and-play features in Einstein Pardot that I want to highlight to you: Einstein Behaviour Score, Einstein Lead Score, Einstein Campaign Analytics and Einstein Attribution. But before we go there, let me point out a couple of conditions you will need to fulfil to benefit from the true power of Einstein: you’ll need Pardot advanced edition, we recommend having Pardot Lightning and you’ll also need to have connected campaigns and engagement history. Important to know is that Einstein resides within Salesforce, not in Pardot: all the number crunching happens in Salesforce, so you should have your leads set up in Salesforce.

Einstein Behaviour Score

Einstein Behaviour Score measures the strength of a prospect’s buying intent. The tool does that by taking behavioural data from engagement history, for instance how active a prospect has been in engaging with content on your site, how they participated in webinars, how they clicked on emails, etc. These engagement activities show that a prospect is engaged and is looking for information. This really makes it the right time to connect with the prospect and make the sale. A key factor in influencing this behaviour score is the ‘recency’ of the engagement, which makes this truly interesting. Are you critical of these scores? Remember: Einstein uses ‘normalised scoring’. The beauty of using AI is that it learns and gets smarter over time. The more data you feed Einstein, the smarter it gets.

Einstein Lead Score

Einstein Lead Score does not look at the behaviour of people, it looks at the value of fields. What is most interesting here is that Einstein determines which current leads have the most in common with leads that have converted in the past. The higher the score, the more these leads have in common with leads that converted previously. The nice thing here is that you could set up an automation that sends these prospects emails or other assets to propel them on a journey, as soon as they get an Einstein lead score of 80, for instance. And here too, Einstein Lead Scoring uses normalised scoring with ranges between 0 and 100.

Einstein Campaign Insights

Einstein Insights does exactly what its name says: it helps you analyse the campaigns you have running and it picks up wisdom from these campaigns that would otherwise take you hours or days to find back in your regular campaign reporting. I promise you it will surface insights that you’ve never even considered. That’s the power of AI, of course. This feature answers the question of what’s exceptional about the prospect activity in this campaign versus all the other campaigns you have done previously. Of course, to make these comparisons, you’ll need to feed the AI engine with data to learn from. Fifty connected marketing campaigns is the minimum here to get the engine running and to get this tool rocking and rolling.

Einstein Attribution

Released just this summer, Einstein Attribution provides you the answer to the eternal question that gets bandied between Sales and Marketing: what marketing efforts led to what sales opportunities? Einstein Attribution takes away the effort we traditionally asked from Sales in adding contact roles and opportunities. It uses historical data to look at the actual journeys prospects go on and it tells you which campaigns attributed to which opportunities. Can you imagine doing that without the date-driven model of Einstein Attribution?

All these new features are plug-and-play, which means they are really easy to switch on and get working. The common ground in all these features is their ability to find patterns that are buried deep in engagement data. They recognise themes, and can take action, for instance making recommendations to users. Believe me, this is truly amazing.

If you want to dig deeper in this matter, listen to a recent podcast with Salesforce Pardot Einstein guru Alon Shvo. It’s part of the ‘Dear Marketing Automation’ podcast series that my colleague Dan Elman and I host, and I can only recommend you subscribe to the podcast.

This blog is based on a Wipro webinar. You can replay the webinar here.