Create a data-driven ICP and learn which of your contacts' activities indicate a stronger buying intent in just a few steps with Breadcrumbs Reveal.
|Free, Pro, and Enterprise Plans|
Use Breadcrumbs Reveal to make data-driven decisions around the attributes that make up your data-driven ICP based on your best customers (or any customer segments) and the actions that predict a higher buying intent (or any conversions, such as upsell or cross-sell.)
Connect your data
2. Navigate to Workspace Settings and click Connections.
a. Click Connect Data Source to connect your primary data source.
b. Click Edit Primary Data Source to edit the two lists to analyze.
3. Choose the two lists to analyze:
a. Scoring list: this is the list that contains the contacts you want Reveal to analyze. Plus, if you are on a Free, Pro, or Enterprise plan, this list will be used in all the scoring models you create in the workspace you're currently on.
b. Objective list: this is the list you are analyzing your scoring list against. It contains the contacts used to define success (i.e., paying customers.) ML will use it to surface the properties that are the best predictors of revenue.
Note: create additional workspaces directly from the drop-down located on the top left-hand side of the page.
4. Click Apply Changes to confirm your edits.
5. Sit back and relax; we'll notify you when we have analyzed your data.
Analyze your data: Fit
Fit refers to firmographic data such as Industry, Job Title, and Company Revenue. Reveal measures Fit impact by surfacing the properties with the most positive lift rate. You can use these properties to define your ICP and create laser-focused fit scoring models.
6. In your Breadcrumbs account, navigate to Analytics, and locate the Contacts Reveal widget below the main graph. The widget contains useful information such as the Scoring list size (called Initial list) and the objective list size (called Training list) you chose during setup, the number of properties analyzed, and the average fill rate. It also includes:
a. Properties fill rate. This graph shows the distribution of your primary data source properties based on fill rate. In particular, it shows how many of your properties are filled in and at which percentage.
Protip: Low fill rate may indicate gaps in the collection and enrichment of your data.
b. Top 5 properties by type. This chart shows the distribution of your primary data source properties by type, such as text, dropdown, number, or date.
Protip: Dropdowns are usually the most actionable properties you can use to understand your customers since the number of options to choose from is pre-defined.
c. Number of unique values in each property. This graph shows the distribution of your primary data source properties based on the number of unique values.
Protip: Properties with high diversity (i.e., free text input from the user) are very tricky to use for data analysis and scoring purposes. Properties with a low number of unique values (i.e., checkboxes or dropdowns) are more actionable.
d. Top 6 properties by impact. Reveal measures impact by surfacing the properties with the most positive lift rate. You can use these properties to define your ICP and create laser-focused scoring models.
What is lift? At its core, lift is directional data. It helps you validate your assumptions that certain properties of your contacts (that is, firmographics, demographics, actions, or behavior) increase (or decrease) the chance of a conversion.
It is calculated as objective list fill rate/scoring list fill rate.
A positive lift indicates that the property correlates with a conversion, while a negative lift indicates anti-correlation. Furthermore, a low lift (positive or negative) indicates a poor correlation with a conversion.
What does it mean in practice? If 50% of your leads live in the US and 50% of your leads live in Europe, but 80% of your customers live in the US and only 20% in Europe, this means that a US lead has a higher likelihood to convert and will have a higher lift.
7. Navigate to Tools > Reveal > Fit for a complete index of all the properties analyzed in your list. On this page, you can also view:
- the number of contacts in your Scoring List that have a specific property filled in, and what is the percentage fill rate.
- the number of contacts in your Objective List that have a specific property filled in, and what is the percentage fill rate.
Analyze your data: Activity
Activity refers to behavioral data such as email clicks, page visits, and trial sign-ups. Reveal measures Activity impact by surfacing the events that occurred most frequently for contacts in your ICP. You can use these events to uncover the actions that are the best revenue indicators and create laser-focused activity scoring models.
8. Navigate to Tools > Reveal > Activity for a complete index of all the events analyzed in your list. On this page, you can also view:
- the number of contacts in your Scoring List that have performed an event at least once and the average event per contact.
- all events properties related to an event and whether an event was triggered (and if so, how many times) in the last 60 days.
- the trend for each event in the last four weeks.
Create better scoring models
9. If you are on a Free, Pro, or Enterprise plan, you can create data-driven scoring categories and use them for an existing or new scoring model in two ways:
a. Click the Actions icon located on the right-hand side of the "Top 6 Impactful Properties" table.
b. Click the Actions icon located on the right-hand side of the Reveal Fit page, accessible from Tools > Reveal > Fit.