G2 Impact 2024 Report

HockeyStack allows for a huge level of customization - thanks to this you can go as top level, or as granular with your reports as you want.

This How-to is a great example, as we break down not only how to get the data we used in the report, but also how to get other information by simply changing a breakdown.

In order to create this report, simply go to the dashboard you want to create it in, and click on “+”.

Next, choose Table report type:

Let’s name our report (1), and choose the time range (2) for which we want to get the data.

Although you can add a breakdown now, we will explore it later in this guide to show you what’s possible beyond getting data just for G2 Impact (For example, data for different SRA Answers).

For now, let’s focus on Columns - data that we want to see. In order to add a column to the report, click “+ Add Column in the report.

The first column we will add is MQLs.

You can realistically add any data you would like. We understand that one size doesn’t fit all, so HockeyStack allows you to create your own definitions and use them in your reports.

In our case, have a definition of MQL, defined as Contact becoming MQL in the CRM.

In order to add it, we will Click on “Select the data to analyze” (1) in Definition, then go to Goals (2), and choose MQL (3).

As the report in our example will be broken down by Self-Reported Attribution (SRA) Answers, we want to see how many MQLs had that SRA - therefore, we will be analyzing “Times Done” property of MQL

Next, we want to see how many deals were created for those SRA Answers. In order to do so, we will add another column, defined as Deals Created(1)(2), Times Done(3).

If we wanted to see the pipeline generated, broken down by SRA Answers, we would create another column with Data Deal Created -> Deal Amount.

Next, let’s see what the conversion rate is from MQL to SQL (or Deal Created).

To do so, we need to add another column and define it as Deal Created (1) -> Times Done (2).

Next, in order to get % ratio of MQLs that became Deals Created, We need to divide Deals Created by MQLs. In order to do so, click on Divide By (Ratio)

Next, let’s divide by my MQLs, Times Done (1), and choose Ratio Format Percent (2).

Next, Let’s add the Number of Closed Won Deals into the report (Again, you can add whatever data you would like, however you define it - just for this How-To document, we need those specific data points).

First, we need to create a new Column.

Following that, we need to add a goal, Deal Closed Won.

Next, we want to use the property “Times Done” - to show how many times the deal was won for the SRA Answer.

In order to see Revenue associated with each lead that gave a specific SRA Answer, we need to add a new column, defined as Deal Closed Won -> Deal Amount.

If we want to add MQL:CW or SQL:CW Ratio (Our example), we can add another column, where we will use Closed Won -> Times Done(1), divided by Deal Created -> Times Done(2), displayed as a percentage (3).

Finally, if we want to see the average time duration between steps, we will create another column using a sequence of actions.

In our example, we want to learn the time between MQL to Deal Created, so let’s create a sequence of actions (1), with the first step being MQL (2), and the second/final step being Deal Created (3)

Next, we want to analyze Time between Steps.

This will allow you to see the total time between those steps.

If you want to see an average, you have to divide it by the same sequence, but this time, use Times done metric - this will show you the average duration.

You can repeat this process for SQL:CW Avg duration, just changing Steps in the sequence of actions to first step being Deal Created (or however you define it) and the final step being Deal Won

Then use the metric of Time between first and last step, and divide that over the same sequence, but with metric times done - this will show you the average time between the deal created to the deal closed won.

Now, that we have done all the columns in the report, let’s return to Breakdowns.

For this report, we used the Breakdown of Self Reported Attribution Form Answer in the CRM - it differs between companies. Click “Select a property” in “Breakdown By”. next, go to “Company Properties” and select your Self-Reported Attribution field.

This will give you data we have chosen in columns, broken down by self-reported attribution fields.

The issue is that you will see EVERY. SINGLE. SRA. ANSWER. - which leads to a lot of rows in the report.

In our case, we wanted to find out when someone mentions G2, and compare it versus someone who doesn’t mention it.

In order to do so, want to categorize it by mentions of G2 and non-mentions. We have to click on our Breakdown (1), and choose “Customize” (2).

Next, we want to two Add Grouping Definitions

The first one will be for when SRA field contains “G2”, and the second one will be for when the SRA field doesn’t contain “G2”.

Feel free to experiment with customization - you can group answers by mentioning podcast, mentioning linkedin, mentioning “friend” (Word of Mouth), mentioning Google - depending on your needs.

Once you do it, save the custom property, then save the report, and you should end up with a final result similar to below