This dashboard provides insights into sales and marketing activities that lead to pipeline and revenue generation.
We start this dashboard with the report showing the Net new pipeline by month, broken down by sales and marketing activities. This report gives you insight not only into month-on-month changes in the pipeline but also based on color-coded activities you can see changes in pipeline impact across them; for example, on the screenshot, you can see that since August 2023 BDRs are bringing more and more pipeline. Also, you can see that Demo Form Submits are the biggest contributor towards the pipeline figures, and it’s a reason for a decrease in the pipeline for certain months.
We start with the New New Pipeline by Activities report which shows the net new pipeline by month, broken down by sales and marketing activities. This report not only gives you insight into month-on-month changes in the pipeline but also allows you to see the impact of various activities through color-coding.
For example, you can easily identify that since August 2023, BDRs have been increasingly contributing to the pipeline. Additionally, you can see that Demo Form Submits are the biggest contributors to the pipeline figures while the AE efficiency is decreasing.
The next two reports use a look-back window (reverse funnel as Canberk calls it) for both closed-lost and closed-won opportunities to understand the steps that led to generating revenue, and steps that caused closed lost deals. This feature doesn’t only show you what’s working, but it also shows you what’s not working at scale.
In this report, we examine steps over the last 6, 9, and 12 months, side by side for both closed-won and closed-lost deals. This comparison helps us not only identify what led to these outcomes but also understand differences in touchpoints between won and lost deals.
In our example, we see that 9-12 months ago, the touchpoints were identical. However, examining the 6-9 month period reveals that exposure to more LinkedIn ads led to more deals being won, in contrast to closed-lost deals where Google Ads were more common.
Additionally, it appears that one of the most frequent steps leading to lost deals was YouTube ads. Based on this insight, you might reconsider the effectiveness of YouTube ads, as they do not seem beneficial in this context.
Next, you can observe that BDR US Outbound Calls are the most common step for winning deals, while they are less frequent in deals lost. This data suggests that calls are more likely to result in a closed-won deal compared to emails or LinkedIn DMs, which are common steps in closed-lost deals.
Next, we have two lift reports; one for pipeline, and one for revenue.
Lift Reports measure the incremental impact of an action or property on conversion rates. For example, they assess for instance, how an email influences deals going to the pipeline stage and to the revenue stage.
By creating these two reports, you can easily see which activities impacted pipeline and revenue the most, and by having them side by side, you can see the difference in activities that led to pipeline and not revenue, and vice-versa.
In our example, we can see that BDR Outbound Email is the activity that has the most uplift on creating the pipeline, followed by BDR Calls; however, partnerships, paid search, and BDR Calls have the best uplift on closing the deal.
This report shows the markeitng pipeline over time, broken down by marketing activities. By analyzing the report by activities, you can see the impact of each activity on the pipeline and observe how it changes over time. This helps you identify the most impactful activities and monitor changes in efficiency.
HockeyStack lets you change between different attribution models, so you can get a better understanding of what affected the pipeline. In this example, we are using First Touch attribution. However, you could easily change the attribution model or create your own definitions for marketing activities, allowing you to see how they affect the pipeline.
This report shows the outbound pipeline over time, broken down by sales activities. By analyzing the report by activities, you can see the impact of each activity on the pipeline and observe how it changes over time. This helps you identify the most impactful activities and monitor changes in efficiency.
It offers actionable insights in three ways:
-First, if there's a decrease in the pipeline, you can easily troubleshoot which activity led to it. -Second, by observing patterns on the chart, you can spot and address issues with the sales pipeline early.
-Finally, by understanding which activities yield the best outcomes, you can focus more on those to see if they positively affect the pipeline.
In this example, we see that from November to March, LinkedIn Outreach consistently brought in a similar amount of pipeline, yet there's up to a $300K difference in pipeline between some months. The second most impactful activity is SDR Cold Calls, while SDR Outbound Email has the least impact. Based on this information, you could investigate why Email is not as efficient or reallocate some of your outbound email efforts towards SDR Cold Calls.
This report provides a high-level overview of activities, including the number of SQLs, total pipeline, average close time, ACV, and total revenue. It's an excellent resource for sales, revenue, and marketing leaders to assess the impact of activities at a high level.
As HockeyStack is completely customizable, you can modify this report to suit your needs. For example, you could break down the report by Page URL, Company Size, Region, Date — whatever you require.
This is an excellent example of customization - you could get the same report as above, but broken down by Sales Activities.
This Sales Activities Report shows the performance of each sales team in one place, helping you with the reporting on it and analyzing their performance.
If you have that data in your CRM, you could go even more granular and have this report broken down by sales reps name.
The sales collateral report shows the impact of each piece of sales collateral sent to prospects, detailing its performance in terms of visits, leads generated, and how those leads progressed through the funnel.
By having this data, you can easily understand which collaterals work well and which ones don’t.
Finally, we have a report that shows sales collateral across the customer journey, showing what collateral contributed more to revenue.
By using the reverse funnel and configuring HockeyStack to show sales collateral properties leading to Closed Won, you can identify which collaterals have an impact on winning deals at scale, and which don’t.
This approach allows you to focus on creating collateral that actually brings revenue.
.png)
Learn more about how HockeyStack helps marketing, revenue, and sales teams surface and action insights like the ones in this template by exploring the interactive demo or booking a virtual demo.
.jpg)
What exactly is HockeyStack? How do we help marketers drive revenue more efficiently?
Jump in to uncover the ins and outs of Marketing Mix Modeling – from its mechanics to its ideal applications – with Drew.
.svg)
