All Collections
Mixpanel Integration
Mixpanel Integration
Noa Lembersky avatar
Written by Noa Lembersky
Updated over a week ago

In this article, you will learn how to connect Mixpanel to Forwrd and how to use it as a source when creating a scoring model.

Introduction to this integration

Adding Mixpanel 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 Mixpanel, you are encouraged to add more data sources to develop a holistic, unbiased scoring model that considers ALL relevant user touchpoints.

What you need to get started:

  • A account

  • A Mixpanel account

Setting up the integration

First we want to create a Mixpanel service-account:

1. Open Mixpanel and press the 'Settings' button.


2. Choose 'Project Settings'.


3. The 'Overview' screen will pop up- take note of the 'Project ID' number.


4. Go to 'service Accounts'.


5. Click 'Add Service Account'.


6. Choose a name, for instance- 'Forwrd Integration' and press the PLUS button (create new service account).


7. Copy the credentials for the 'Service Account Username' and 'Service Account Secret'.

VERY IMPORTANT: Make sure you save the service account secret. You will never be able to access it again.


8. Add Mixpanel as a source in Forwrd.

Open the Forwrd app, and navigate to the 'sources' layer.


9. Click new and then choose 'Mixpanel'.


10. The default name 'Mixpanel integration' is created. You can keep it or change it, and then press 'Next'.


11. Enter the credentials collected for the 'Service Account Username', 'Service Account Secret, and 'Project ID'.


12. Define a decision base (microdata warehouse).

Next, you must define a ‘decision base’, a micro data warehouse that Forwrd can analyze to generate predictions.


A decision base can combine data from multiple sources. For instance, you can combine data from BigQuery, 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. Alternatively, you can also write your own SQL query that retrieves the objects and columns you require. However, when using this method, it is not possible to join the Mixpanel data with other data sources.

Once the decision base is created, you can see its size, 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, etc.

3. 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 12) 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.

4. 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 a number of factors that impact your business objective, and, by how much.

You can drill down to any of the factors that Forwrd detected to gain a deeper understanding of what drives conversions and what does more damage than good.

5. Build a scoring model.

Now you can build a model that will help you predict whether your open leads will convert or not. To do that, we’ll click ‘build model’.

Forwrd will display the result and classify your leads into four buckets based on their likelihood to convert.

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!

Did this answer your question?