Journey Predictions uses a machine learning model to surface the accounts most likely to become an open opportunity/deal. The model is trained using accounts past or present in an open opportunity/deal in your CRM, and analyzes the fit, intent, and engagement signals in the time leading up to becoming an open opportunity to find accounts that look like and are acting like those accounts that became an open opportunity. The model scores accounts into high and medium bins, these Prediction Scores are refreshed daily providing a reliable view of account potential.

We make Journey Predictions available in the Command Center, Account List Building, Contact List Building, Workflows, and we sync the data to Salesforce or HubSpot.

Journey Predictions takes the guesswork out of how to combine various in-market and fit signals so that your marketing and sales team improves their efficiency by focusing on the accounts most likely to become an open opportunity.

Who can access

Access to Journey Predictions depends on your package.

To find your current subscription, log in to RollWorks and navigate to Settings > Billing > Plans & Usage.

In addition to having a RollWorks package that includes Journey Predictions, you must meet the technical and data requirements below. After these requirements are met and the training data set is available, it may take up to 24 hours to calculate Journey Predictions. 

Technical Requirements

1. RollWorks integrated with Salesforce or HubSpot:
   • • Salesforce Initial Installation Guide
     • HubSpot Initial Installation Guide
2. A minimum of one Journey Stage customized using the Salesforce Opportunity object or HubSpot Deal object.  

   

   

Data Requirements

1. A minimum of 3 months of historical opportunity/deal activity data in your CRM. 
2. A minimum of 10 accounts in your CRM that are currently in, or have been in the Open Opportunity/Deal Journey Stage, based on your Journey Stage configuration. This data is needed as your training data set.

How does Journey Predictions work

Our predictive Machine Learning model scores accounts in a few different ways:

1. The training data set is derived from your Journey Stage configuration in the RollWorks App. We use the first Journey Stage that uses your Salesforce Opportunity or HubSpot Deal objects as a way to infer what you consider an open opportunity. We will consider all accounts in that Journey Stage, and stages further in the funnel.
2. The prediction model looks at the fit, intent, and engagement of the accounts in your training data set prior to those accounts having an open opportunity or deal opened. The prediction model uses the following signals:
   • • Firmographic Company Attributes (Fit):
       • • Industry
         • Company Size
         • Company Revenue
         • Technologies
     • Engagement:
       • • Website Page Views
         • Form Fills
         • Salesforce, HubSpot, and Marketo Activities, including event type and Inbound/Outbound designations
     • Intent:
       • • RollWorks Keyword Intent
         • Bombora Company Surge Intent
     • Other variables:
       • • Count of intent and engagement over a time frame
         • Cumulative intent and engagement
         • Recency of intent and engagement
3. We look at accounts that are not yet in the first opportunity stage and assess how closely these accounts look and are behaving like the accounts that became an open opportunity. In order to make sure that the accounts that are receiving Journey Predictions are relevant we assign the prediction scores to only a subset of accounts.
   • • The model will produce Journey Predictions for accounts that meet at least one of the following criteria:
       • • The account is on an Account List in RollWorks
         • The account has shown intent or engagement activity in the last 90 days
     • The model will not produce Journey Predictions for accounts that meet any of the following criteria:
       • • The account is currently part of the training data set (have an open Opportunity or Deal)
         • The account has been part of the training data set in the last year
         • The account is a current customer
         • The account was a customer but churned in the last year

Journey Predictions Score: High vs Medium

Journey Predictions will score accounts either as High or Medium:

• High: top 5% of positively predicted accounts – on average, High accounts are 25x more likely to become an open opportunity than an average account
• Medium: top 40% of positively predicted accounts – on average, Medium accounts are 5x more likely to become an open opportunity than an average account

Some accounts will have a blank Journey Prediction score. Click here to learn the minimum conditions that must be met for an account to receive a Journey Prediction score.

Where to access Journey Predictions

Journey Predictions is available in the following areas of the RollWorks platform:

• In the RollWorks Command Center as a filter and a data column
• In the Enhanced Contact List Builder as a filter
• As a filter when creating an Account List through the RollWorks Command Center
• As a trigger in RollWorks Workflows which enables custom actions
• Synced to your CRM Salesforce Custom Objects 
• Synced to your CRM HubSpot Custom Properties

How to use Journey Predictions

Journey Predictions FAQs

Why do some accounts have a blank Journey Prediction?

In order to make sure that the accounts that are receiving Journey Predictions are relevant we assign the prediction scores to only a subset of accounts.

• • The model will produce Journey Predictions for accounts that meet at least one of the following criteria:
    • • The account is on an Account List in RollWorks
      • The account has shown intent or engagement activity in the last 90 days
  • The model will not produce Journey Predictions for accounts that meet any of the following criteria:
    • • The account is currently part of the training data set (have an open Opportunity or Deal)
      • The account has been part of the training data set in the last year
      • The account is a current customer
      • The account was a customer but churned in the last year

What attributes and signals does the model take into account?

The predictions model looks at the fit, intent, and engagement of the accounts in the positive training data set prior to those accounts having an opportunity opened. We then look at accounts that are not yet in the open opportunity stage and assess how closely these accounts look like and are behaving like the accounts that became an open opportunity. 

The Data / Features in the predictions model include:

• Company Attributes (Fit): industry, company size, company revenue, technologies, etc.  We consider all account attributes that are part of the RollWorks ICP Fit Grade Account Scoring model.
• Engagement: Website Page Views, Form Fills, Salesforce, HubSpot, and Marketo Activities including event type, and inbound/outbound designations.
• Intent: Keyword Intent and Bombora Company Surge Intent.
• Other Variables: The model considers other variables like the count of intent/engagement over a given time frame, the cumulative intent/engagement, and recency of the intent/engagement.

What is the duration it takes to generate predictions?

Once the eligibility requirements are met, customers can expect prediction scores within 24 hrs

How do you determine which accounts were in an open opportunity/deal?

RollWorks uses your customized Journey Stages to determine which accounts are currently in an open opportunity/deal or were previously in an open opportunity/deal.

RollWorks uses the first stage that uses an Opportunity (Salesforce) or Deal (HubSpot) rule to infer which stage represents an open opportunity.

What happens if I change my Journey Stage definitions?

Predictions are versioned to the stage changes, so it’s likely the accounts with a High and Medium Prediction Score will change. After updating your Journey Stage Definitions using Salesforce Opportunity or HubSpot Deals it may take up to 24 hours to recalculate Journey Predictions.