In this article, you will learn how to connect Salesforce to Forwrd and how to use it as a source when creating a scoring model.
Introduction to this integration
Adding Pardot to Forwrd makes it easy to analyze and score your leads and customers by matching historical data (i.e., engagement, firmographics, demographics) against a business objective, to ultimately predict who will convert and why.
Here are some examples of use cases:
- Predict which leads will become MQLs
- Predict which MQLs will become Opportunities
- Predict which Opportunities will become Paying customer
- Predict which Customers will Expand
- Predict which Customers will Churn
In addition to Salesforce, you are encouraged to add more data sources, in order to develop a holistic, unbiased scoring model that takes into account ALL relevant user touch points.
What you need to get started:
- A Forwrd.ai account
- A Pardot account
Setting up the integration
1. Click the 'Sources' icon on the Forwrd back office.
2. Click the '+NEW' button to create a new source.
3. Choose Pardot from the integration source menu.
4. A 'Pardot connect' will pop open, click NEXT.
5. Set up a 'Business Unit ID'
5. Name your 'Enviroment' and click next
5. Choose the Pardot Integration from the 'Sources' menu
You can click the 'three dots' icon to see more functions you can perform with this source. For example, you can share this source with another team member who uses Forwrd, and you can also test the connection to this source.
6. Define a decision base (micro data warehouse).
Next, you will need to define a ‘decision base’, which is a microdata warehouse that Forwrd can analyze to generate predictions.
A decision base can combine data from multiple sources. For instance, you can combine data from Pardot, HubSpot, and Mixpanel. The types of sources you would combine would depend on your use case.
Click 'Create New', name your decision base, and select the data sources and the respective objects you'd like to join together.
Once the decision base is created, you can see its size, its date range, and when it was last synced – and you can even set it to sync to ensure your data is always fresh and up-to-date.
After creating your decision base, you can apply filters to hone in on specific segments, user groups, and so on.
7. Define a metric (business objective).
Next, you should define your Metric, which stands for the business objective and business logic, to guide your prediction.
Click 'Create New' and name your metric. Next, add the decision base you have just created (in step 2) and define an expression to teach Forwrd what a successful conversion looks like.
Next, you will teach Forwrd what an ‘open’ record looks like, so it will make predictions on these open leads.
Lastly, to generate the most accurate predictions, you must tell Forwrd how to recognize ‘lost’ leads that didn’t convert into opportunities.
8. Run an analysis.
At this point, we can run an analysis. Go to the 'Projects' tab, create a new project, and within it, create a new analysis that includes your ‘Decision base’ and ‘Metric’.
Once done, click 'Create'. This will run your analysis.
At this point, you can review your analysis – As you can see on the left side of the screen, Forwrd identified several factors that impact your business objective and by how much.
You can drill down to any of the factors that Forwrd detected to better understand what drives conversions and what does more damage than good.
9. Build a scoring model.
Now you can build a model that will help you predict whether your open leads will convert. To do that, we’ll click ‘build model’.
Forwrd will display the result and classify your leads into four buckets based on their conversion likelihood.
You can hover over each of the records and see a clear explanation of WHY Forwrd decided to give the lead its score.
Thanks for taking the time to review these instructions.
If you need further help setting things up, or if you’d like to see a personalized, in-depth demo of Forwrd –book a demo with us. We'd love to help!