Table of Contents

Insights - Attribution Terminology and Key Concepts

Camela Thompson Updated by Camela Thompson

General Dashboard Functionality

For more information on the following topics, click on the linked topic:

An Explanation of the Attribution 2.0 Dashboard

attribution 2.0 dashboard numbered

On the right-hand side of the dashboard, you'll see several options that control what data is displayed and how it is displayed.

  1. The Date Selector allows you to view a specified period of time. This works well if you have a fiscal calendar and want to see pipeline generation by month or bookings for a specific quarter.
  2. The Cohort Date is how the chart (item 7 above) is organized. The bottom or x-axis is a timeline, and the Cohort Date determines which date this data is organized by. The following offers an explanation for each category:
    1. Opp Created: Organizes the data by the date the opportunity was created. This may also be your pipeline-generated date (if you've arranged this with customer support or used the object manager to map a custom field to the Created Date field in CaliberMind). If you use this cohort, your dollar amounts should tie out to pipeline generated in your CRM.
    2. Opp Closed: Organizes the data by the date the opportunity has or is scheduled to close. For open opportunities, this should reflect a date in the future. This cohort is often paired with an Additional Filter (item 6 above) of Opp Status = Won to match bookings reported in your CRM.
    3. Touch Date: Organizes the data by when the interaction with your brand occurred. Please be aware that this view can't be reproduced in your CRM. Opportunity dollars divided over touch points will be summed by the date the touch point happened, so an opportunity will show up in multiple time periods.
  3. Chart Date Aggregator determines which increments the chart is broken out into. You may select weeks, months, quarters, or years. Note that the chart will still reflect the total impact across the time period in your Time Selector (item 1 above).
  4. This allows users to change the Attribution Model on the fly because different attribution models answer different questions. For more details on that, check out the section of the KB labeled "Which Attribution Model Should I Use?"
  5. Group By allows you to independently change how your data is broken out in your chart or table. For example, you may want to visualize how campaign types are performing month to month in the chart and then look at how different industries are performing in the table. If you want to impact both the chart and the table, you will need to click on both the Chart and Table buttons.
  6. Additional Filters will apply a filter to all of the items displaying on the dashboard. For example, if you want to look only at Opportunity Type = New Business, you can apply an Additional Filter. Other great use cases are looking at different Company Tiers, Account Regions, or other custom field your business uses to divide its business units.
To add a custom field to your Attribution 2.0 dashboard in Insights, email help@calibermind.com or use your dedicated CaliberMind Slack channel.
  1. The Chart is a stacked bar chart that visualizes your attribution data according to the Cohort Date (Item 2) along the x-axis in increments specified by the Chart Date Aggregator (Item 3) and is stacked by the Group By (Item 5) selected with the "Chart" button. The attribution model applied to the chart will be the same model you select in the Attribution Model (Item 4) section.
  2. The Table operates just like a Pivot table in Excel. Your results are for the time period you indicated in your Time Selector (Item 1) and will be broken into rows by the Group By (Item 5) selected with the "Table" button.
  3. The KPI section will display high-level metrics for the Attribution Model (Item 4) and Date Selector (Item 1) time frame. The metrics are defined as follows:
    1. Pre-Opp Attribution: In any attribution model, this will be the sum of all touch values associated with events that take place between the first touch and opportunity create date. This term is synonymous with "Source" in our legacy app reports.
    2. Post-Opp Attribution: In any attribution model, this will be the sum of all touch values associated with events that take place after the opportunity create date until the opportunity close date. This term is synonymous with "Influence" in our legacy app reports.
    3. Total Attribution: The sum of Pre-Opp Attribution and Post-Opp Attribution.
    4. Total Pipeline: The sum of dollars associated with opportunities in the given period, regardless of whether or not we can find brand interactions or events to allocate attribution to. If the pipeline number does not match total attribution, there is a gap in events, likely caused by a salesperson creating an opportunity without relevant events being logged.

Which Attribution Model Should I Use?

Customers with access to Insights now can change which attribution model they are viewing on the dashboard level. On the Attribution 2.0 and all legacy Attribution dashboards, there is an Attribution Model dropdown:

Choosing a CaliberMind Attribution Model

Selecting a model and clicking apply will trigger the dashboard to immediately update and display the numbers associated with that model.

By default, customers will see:

  • Even-Weighted
  • First Touch
  • Middle Touch
  • W-Shaped

Customers who have purchased the Machine Learning add-on will also see the Chain-Based model.

The reason why we allow customers to choose from many models is that each of them answers a different question. For a deep dive into which model you should use when, check out this article.

In short:

  • First Touch - Shows 100% opportunity amount allocation given to the very first logged response event (inbound activity) in our system and is not limited to the primary contact on the opportunity. This is meant to help companies see which activities are building awareness among new prospects.
  • Middle Touch - Allocates 100% of the opportunity amount to the response event (inbound activity) that happened immediately before an opportunity was created and is not limited to the primary contact on the opportunity. This model is often used to demonstrate "Opportunity Source" in companies that are trying to understand which department(s) were responsible for turning an interesting prospect into a real opportunity.
  • Even-Weighted - Even-weighted models evenly divide the opportunity amount across all response events (inbound activities) from well before an opportunity was created to when the opportunity was closed. We then divide those activities into Pre-Opportunity and Post-Opportunity touches - or inbound events that happened before the opportunity was opened and those that happened between the time it was opened and the time it was marked Closed. Activities with more people engaged will naturally be weighted heavier. Otherwise, activities are assumed to be of equal value.
  • W-Shaped - The “W” shape model is an attribution model that gives different weights to activities that include the following criteria: An activity that is flagged as the primary campaign, the activity is associated with a primary contact, or the activity happened prior to the opportunity. For more on how the model works, go here.
  • Chain-Based - The chain-based model uses machine learning to understand which activities in which order are most likely to lead to a Closed Won opportunity. We use training data - or activities associated with Closed Won opportunities - to come up with an ideal sequence of events. Events that happen in an ideal sequence will be weighted heavier than those that are not associated with Won opportunities. Customers who have purchased the machine learning package have access to this model.

A Couple Cool Features

Did you know that by clicking on any row in the Table, you can view all of the opportunities and events associated with the selected break out or group?

Try it out!

You can even click from there to view the Account in CaliberMind. And when you click on the Account's Account Detail, you can see exactly how the math works for attribution:

How did we do?

Insights - Attribution - Start Here!

Insights - Attribution Overview Dashboard 2.0

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