Explore Einstein Features for Pardot
After completing this unit, you’ll be able to:
- Describe how Pardot tools differ from Einstein features.
- Describe the basic uses for other Einstein for Pardot features.
Now that you know how to enable the four components of Pardot Einstein, consider how each feature can benefit your business. Let’s dive deeper into how the features help sales users prioritize leads, optimize campaigns, and attribute revenue share.
Einstein Behavior Scoring
Einstein Behavior Scoring identifies the buying signals that your prospects exhibit, like page views and email clicks. It then scores those prospects based on their engagement patterns over the past 365 days. All of this is powered by machine learning. Algorithms translate prospect behavior data and engagement patterns into a numerical score that reflects a prospect’s real-time engagement.
Einstein uses Pardot Engagement History data to determine which prospects are most likely to become customers in the future. In determining a prospect’s score, Einstein analyzes factors including behavioral signals and recency of engagement.
Einstein uses this data to assign a score of 0 to 100 to each prospect. Add a Behavior Score column to your list views or add the Einstein Scoring component to Lightning pages. Then, sit back and watch Einstein work its magic.
Einstein Behavior Score is available in the following areas.
- Einstein Scoring component on Lead and Contact record home pages in Lightning Experience
- Lead and Contact list views in Lighting Experience
- Salesforce API
- Salesforce Reports, Process Builder and Workflow Rules
- Pardot Prospect Pages, Engagement Studio, and Automation Rules (as prospect custom fields)
Plus, B2B Marketing Analytics users can create an optional Einstein Behavior Scoring dashboard, where they can explore how the scoring model is made.
Here you see the Einstein Scoring information available directly within the lead record.
First, Einstein Behavior Scoring calculates a score from 0 to 100 based on activities from the previous 365 days. Your prospects are then ranked against each other, and Einstein Behavior Scoring highlights positive and negative insights.
The Top Positive and Top Negative Predictive Factors that appear in the Lightning component tell you which behaviors most heavily influence a particular prospect’s score positively or negatively.
Positive insights for a lead might include high email open rate and form submissions. The same lead could have a low click-through rate or no recent activity, likely noted as a negative insight. Recent activities typically score higher than older activities and a behavior score changes over time.
Here you see Einstein Behavior Score displayed in a lead list view.
How Does Pardot Prospect Score Differ from Einstein Behavior Scoring?
Regardless of your Pardot Edition or Einstein usage, all Pardot prospects are scored using Pardot’s out-of-the-box scoring model. So how is a Pardot Prospect Score different from Einstein Behavior Score?
Where Pardot’s static, rules-based prospect scoring model is a standard feature available to all customers, Einstein Behavior Scoring is a dynamic model that’s available with Pardot’s Advanced edition.
Pardot’s scoring tool tells the marketing team how interested a prospect is in marketing-tracked content. Marketers can assign a numeric value to engagement activities like form submissions, email clicks, and website page views, which boosts the Pardot score indefinitely. So a score of 100 can be high or low relative to other prospect scores.
Traditional Pardot scoring is used to qualify prospects before assigning a corresponding lead or contact to sales.
Einstein Behavior Scoring, on the other hand, applies to all prospects with activities in the past year, uses machine learning, and gets smarter over time. It clearly indicates whether a score is relatively high or low compared to other prospects: this algorithm never lets the Behavior Score exceed 100. You’ll always know that leads or contacts with a score near 100 have a high score.
Based on its analysis, Einstein automatically adjusts a prospect’s score. This score is not merely a summary of all-time activities, but a more advanced calculation that takes into account things like recency and frequency of engagement.
Einstein Behavior Score doesn’t replace the Pardot prospect score. Since the two scores are calculated differently, you may find value in using both scoring models.
Einstein Lead Scoring
If Einstein Behavior Scoring tells you how interested a lead or contact is in your business, Einstein Lead scoring tells you how interested your business should be in a lead.
Einstein Lead Scoring looks at your company’s past leads, including any custom fields, to find patterns in your successful lead conversion history. Einstein Lead Scoring then determines which of your current leads fit your success patterns best. Each lead receives a score indicating how well it fits your patterns, along with insights about which of the lead’s fields affect its score most.
Seasoned Pardot users will recognize its similarities to letter grading in Pardot. The Einstein score differs in that it’s numeric, unique to lead records, and is powered by artificial intelligence instead of manually configured automation tools. When used in tandem with Einstein Behavior Scoring, Lead Scoring prioritizes best-bet leads for sales users.
Customers with Pardot Einstein, Sales Cloud Einstein, or HVS licenses have access to Einstein Lead Scoring; it is not unique to Pardot. Learn more about it in the Prioritize Leads with Einstein Lead Scoring project.
Einstein Campaign Insights
Einstein Campaign Insights helps marketers understand the factors that drive campaign performance without having to manually sift through and cross-reference reams of data. For example, insights might showcase which personas or geographical regions are most engaged so marketers can optimize their campaigns over time by tailoring emails to those types of prospects or planning events in those regions. These insights can also highlight campaigns that aren’t successful and ultimately uncover new audiences that could be relevant for future campaigns.
Einstein Campaign Insights can be found in two places.
- The Einstein Insights component on the Lightning home page
- In the Einstein Campaign Insights page on the Campaign record home page in Lightning
Looking at past campaigns, Einstein uses data related to activity, engagement, content, and audience characteristics to provide real-time insights on currently running campaigns. If you already look to past campaigns to determine how to structure your future campaign strategy, your job just got easier! Einstein applies machine learning algorithms to generate those insights for you, determining current campaign engagement level and opportunities for boosting engagement.
The idea behind Einstein Attribution is that you take a helpful tool like Campaign Influence and apply Einstein’s intelligent modeling and analysis to it. Instead of choosing a model before you start reporting or manually entering contact roles on an opportunity, Einstein Attribution scans existing campaigns and finds the patterns that emerge.
We use your company’s historical data to generate an AI-driven campaign influence model that assigns conversion credit across the available marketing touchpoints. Einstein shows you which campaigns are most effective at generating pipeline, so that you
can make better decisions about where to invest your marketing resources.
The upshot is, Einstein Attribution can analyze more data and provide more accurate insights than the rules-based attribution models you may be using now.
Einstein Attribution results are available in the following areas.
- The Campaign Influence related list on campaign and opportunity Lightning pages
- B2B Marketing Analytics app, Multi-Touch Attribution dashboard
- Salesforce Reports
- Salesforce API
How Does Einstein Attribution Differ from Campaign Influence?
In the past, Salesforce and Pardot have offered rules-based attribution models that used predefined formulas and conversion credits. Even Customizable Campaign Influence requires sales and marketing users to make educated guesses about how influential a campaign has been.
Einstein Attribution is a sophisticated algorithmic attribution model. It uses a scientific approach that provides output predictions built on your historical data and its AI-driven models. The model determines which touchpoints are the most influential in the customer journey, so that you get more accurate conversion data.
Now you’re ready to enable any or all of the four components of Einstein for Pardot and enjoy the dynamic insights they provide for both marketing and sales users.