At the PreSales Leadership Collective Virtual Roundtable on December 8, we had a deep discussion about a hot topic right now: metrics and KPIs in PreSales. Our host was Greg Holmes, Regional VP of PreSales at Apptio.

Why Metrics Matter

PreSales leaders want to make data-driven and informed decisions. But there’s so much data out there these days that it can be difficult to know what, exactly, you should use, where you should use it, and what you should be tracking.

What Metrics Help You Make Decisions

Finding the right metrics means starting by finding which ones would help you as a PreSales leader make decisions. Here are a few potential ways to look at metrics, depending on what decisions and choices you need to make:

• Activity and effort - Data such as how many demos you did last week.
• Individual and team - How many people you have doing certain activities.
• Outcomes - The end result (vs. how did you get to the outcome) such as win/loss success rate.
• Measuring value - How much value was caused by a given thing happening during the sales process or from a product feature.
• Tool-based data - Metrics that come from tools like Salesforce/CRM, PreSales tooling, or product telemetry. These might be more accurate bc doesn’t depend on humans to log it

What You Want to Know in an Ideal World

If you could know any real facts about your business, what would you want to know? Of course, we don’t live in an ideal world, so these dream metrics might not be actually possible or effective. But thinking about them can help us determine what we really need to know.

• What deals are worth a certain amount of effort - i.e. this deal is worth three days of PreSales effort based on the potential revenue, as this data would help you run your organization effectively.
• Which sales motions require more PreSales effort - knowing this would allow you to staff them differently, as well as not lumping stats in together for disparate sales motions to increase your planning accuracy.  
• What activities work best at certain stages of the opportunity cycle - this ideal metric could help improve understanding the technical lifecycle of deals, and it connects with sales too.  

Leading Indicators

Leading indicators tell you something that is going to happen, so they can help you change and adjust for the future. Trailing indicators, on the other hand, tell you something that has already happened - they don’t help you avoid something, but can tell you how you did retrospectively.

Leading indicators are used a lot in marketing to compare the quality of leads coming into the pipeline. If we can extend this down to PreSales, we can help determine if we will meet future targets, and maybe even predict if you will have enough people in three months from today. These indicators can help with forecasting, capacity planning, and resource allocation.

Can Metrics Steer Us Wrong?

Sometimes it seems like data is the answer to all our problems. But can metrics actually drive the wrong behavior? Yes, depending on how they get collected.

Some Leaders mentioned that their senior Sales Engineers disliked logging their activity. They don't feel the need to tell people how they do stuff because they know they are effective, while newer Sales Engineers tend to be better at logging. But that difference makes it hard to get accurate metrics that help behavior.

It’s also helpful to remember that the act of collection affects what people do. If you tell your Sales Engineers they will be flagged if they do less than five demos per week, they’ll record that they do five demos per week - but it doesn’t tell you about the quality or effectiveness of those demos.

There’s always a push-pull going on between manually logging vs. automated data collection. It’s good to remember that not everyone works in the same way - one Sales Engineers might demo in the product while another uses slides. If they’re both equally effective, don’t force them to demo in the same way just for the sake of metrics.  

It’s also vital to avoid rewarding effort over outcomes because you might end up rewarding the wrong behavior. You want to reward outcomes like bringing in business, not a certain number of activities, even if you track those activities for other purposes.  

Breakout Sessions Findings

In our roundtable breakout sessions, we also heard some informative findings about how PreSales teams across the world are using metrics and KPIs in their orgs. Here are a few of our favorite takeaways.

Many PreSales teams look at commercial targets only for compensation - and they mostly use only team targets, not individual targets. Tracking quantitative data (like running five demos per week) isn't usually used for compensation because it leads to wrong behaviour, but can be very useful to analyze which deal stages Sales Engineers are active in to inform sales enablement or to improve processes.

One leader also wanted to measure how his Sales Engineers give back to the team by sharing their knowledge, and so he was incentivizing the team to write blogs about their knowledge.

Not everyone reports their activities as expected, so a good data sample is obtained when 60-80% of the team members are effectively reporting.

Attachment rate is an interesting data point as well - this metric shows the % of opportunities over a certain amount ($) in which you engage a Sales Engineers

Some of our members used more traditional ways to measure KPIs and metrics, such as:

• # of demos/POC per deal type/Sales Engineer
• # hours spent per deal type
• # opportunities worked/ won/lost
• # remote/onsite customer meetings

The other members reported using a criterion called the “technical win” to measure success. One example used was on tenders where many bidders are involved. Once the company is qualified for the last round of negotiations, the Sales Engineer has done their part successfully. If the account is ultimately not won due to commercial reasons, the Sales Engineers were not held accountable. In other words, the technical win is the successful handover of a qualified lead after it has passed the PIC/POC stage to the sales reps for the final negotiation stage.

And a few members shared that they use a Salesforce CRM add-on to capture the data and track activities without people feeling monitored about how many demos they do and if they actually put in eight hours daily at their desks, etc.

Key Takeaways

Data is a valuable tool in PreSales - but only if you know where and when to use the metrics you have access to.

Mindmap created and provided by Virgile Delecolle, PSC Ambassador.

‍

At the PreSales Leadership Collective Virtual Roundtable on December 8, we had a deep discussion about a hot topic right now: metrics and KPIs in PreSales. Our host was Greg Holmes, Regional VP of PreSales at Apptio.

Why Metrics Matter

PreSales leaders want to make data-driven and informed decisions. But there’s so much data out there these days that it can be difficult to know what, exactly, you should use, where you should use it, and what you should be tracking.

What Metrics Help You Make Decisions

Finding the right metrics means starting by finding which ones would help you as a PreSales leader make decisions. Here are a few potential ways to look at metrics, depending on what decisions and choices you need to make:

• Activity and effort - Data such as how many demos you did last week.
• Individual and team - How many people you have doing certain activities.
• Outcomes - The end result (vs. how did you get to the outcome) such as win/loss success rate.
• Measuring value - How much value was caused by a given thing happening during the sales process or from a product feature.
• Tool-based data - Metrics that come from tools like Salesforce/CRM, PreSales tooling, or product telemetry. These might be more accurate bc doesn’t depend on humans to log it

What You Want to Know in an Ideal World

If you could know any real facts about your business, what would you want to know? Of course, we don’t live in an ideal world, so these dream metrics might not be actually possible or effective. But thinking about them can help us determine what we really need to know.

• What deals are worth a certain amount of effort - i.e. this deal is worth three days of PreSales effort based on the potential revenue, as this data would help you run your organization effectively.
• Which sales motions require more PreSales effort - knowing this would allow you to staff them differently, as well as not lumping stats in together for disparate sales motions to increase your planning accuracy.  
• What activities work best at certain stages of the opportunity cycle - this ideal metric could help improve understanding the technical lifecycle of deals, and it connects with sales too.  

Leading Indicators

Leading indicators tell you something that is going to happen, so they can help you change and adjust for the future. Trailing indicators, on the other hand, tell you something that has already happened - they don’t help you avoid something, but can tell you how you did retrospectively.

Leading indicators are used a lot in marketing to compare the quality of leads coming into the pipeline. If we can extend this down to PreSales, we can help determine if we will meet future targets, and maybe even predict if you will have enough people in three months from today. These indicators can help with forecasting, capacity planning, and resource allocation.

Can Metrics Steer Us Wrong?

Sometimes it seems like data is the answer to all our problems. But can metrics actually drive the wrong behavior? Yes, depending on how they get collected.

Some Leaders mentioned that their senior Sales Engineers disliked logging their activity. They don't feel the need to tell people how they do stuff because they know they are effective, while newer Sales Engineers tend to be better at logging. But that difference makes it hard to get accurate metrics that help behavior.

It’s also helpful to remember that the act of collection affects what people do. If you tell your Sales Engineers they will be flagged if they do less than five demos per week, they’ll record that they do five demos per week - but it doesn’t tell you about the quality or effectiveness of those demos.

There’s always a push-pull going on between manually logging vs. automated data collection. It’s good to remember that not everyone works in the same way - one Sales Engineers might demo in the product while another uses slides. If they’re both equally effective, don’t force them to demo in the same way just for the sake of metrics.  

It’s also vital to avoid rewarding effort over outcomes because you might end up rewarding the wrong behavior. You want to reward outcomes like bringing in business, not a certain number of activities, even if you track those activities for other purposes.  

Breakout Sessions Findings

In our roundtable breakout sessions, we also heard some informative findings about how PreSales teams across the world are using metrics and KPIs in their orgs. Here are a few of our favorite takeaways.

Many PreSales teams look at commercial targets only for compensation - and they mostly use only team targets, not individual targets. Tracking quantitative data (like running five demos per week) isn't usually used for compensation because it leads to wrong behaviour, but can be very useful to analyze which deal stages Sales Engineers are active in to inform sales enablement or to improve processes.

One leader also wanted to measure how his Sales Engineers give back to the team by sharing their knowledge, and so he was incentivizing the team to write blogs about their knowledge.

Not everyone reports their activities as expected, so a good data sample is obtained when 60-80% of the team members are effectively reporting.

Attachment rate is an interesting data point as well - this metric shows the % of opportunities over a certain amount ($) in which you engage a Sales Engineers

Some of our members used more traditional ways to measure KPIs and metrics, such as:

• # of demos/POC per deal type/Sales Engineer
• # hours spent per deal type
• # opportunities worked/ won/lost
• # remote/onsite customer meetings

The other members reported using a criterion called the “technical win” to measure success. One example used was on tenders where many bidders are involved. Once the company is qualified for the last round of negotiations, the Sales Engineer has done their part successfully. If the account is ultimately not won due to commercial reasons, the Sales Engineers were not held accountable. In other words, the technical win is the successful handover of a qualified lead after it has passed the PIC/POC stage to the sales reps for the final negotiation stage.

And a few members shared that they use a Salesforce CRM add-on to capture the data and track activities without people feeling monitored about how many demos they do and if they actually put in eight hours daily at their desks, etc.

Key Takeaways

Data is a valuable tool in PreSales - but only if you know where and when to use the metrics you have access to.

Mindmap created and provided by Virgile Delecolle, PSC Ambassador.

‍