Metrics that Matter | Outbound Sales Development

Performance optimization discussions in the world of Sales Development typically focus on vanity metrics – surface-level metrics that are good for comparison, but don't necessarily lead to action. Using Looker, our team is able to view and analyze data beyond simple vanity comparisons, and instead focuses on clarity metrics – those that drive behavior, growth, and learning.

Here's a rundown of some metrics we use to evaluate our Outbound Sales Development (SDR) team at Looker, starting with simple activity counts for comparison purposes and moving into more complex efficiency rates that impact behavior.

For a bit more context, our Outbound team is primarily responsible for generating their own leads, creating messaging for those leads & companies, informing them about Looker, and passing them off to our Sales team to initiate the sales cycle. (Related: Here's a rundown of our Inbound SDR metrics.)

Leads ID'd

One of the most important and most time-consuming elements of an Outbound SDR's day-to-day is finding people who, based on their title or background, would be interested in evaluating Looker as an analytics solution. So it's important to track how many Leads each SDR is sourcing for themselves and adding to our CRM. This can help set benchmarks and expectations, and can be a decent indicator of level of effort.

But stopping analysis there is a mistake – like any vanity metric, this is really only useful for comparison purposes and doesn't really tell much on its own. Is SDR 1 twice as "good" as SDR 9? It's impossible to tell just from this.

Companies ID'd

This view shows both number of Leads and number of unique Companies identified by the SDR and added to our CRM. Again, good for comparison and okay for certain expectation-setting exercises. But tough to say if and how this analysis can or should influence an SDRs behavior.

Leads ID'd per Company

Using Looker, we can add a custom metric for Leads ID's per Company. This gives a more readable view of the previous visualization, and tells us a bit about why SDR 1's Lead count is so much higher than SDR 9's.

And it starts to paint a picture around efficiency – is SDR 1 casting too wide a net? How is that going to affect her ability to effectively process the leads she creates? Is SDR 9 ignoring good-fit leads that he should otherwise be pursuing? These are good questions to raise in team or 1:1 settings for discussion, but fall a bit short of dictating or influencing behavior of SDRs.

Put a pin in this line of thinking, we'll revisit it momentarily.

Emails Sent

Another important element of the Outbound SDR's workflow is creating messaging and contacting the Leads they've ID'd. The visualization above shows a simple count of emails sent over a particular timeframe. Just as the Leads ID'd chart above this really only serves for comparison purposes, it doesn't truly tell us anything about SDR efficacy.

Email Replies Received

This is starting to get interesting. In addition to the number of emails sent, this viz shows the number of times someone has replied to those emails. I'm of the mind that optimizing Outbound workflows to maximize replies is the key to success – it's a much better indicator of messaging quality and prospect engagement than Email Opens. What is SDR 2 doing differently from a messaging and outreach standpoint to create so many replies?

But don't get too carried away with this view. As before, these raw counts are good to know but adding in a calculation makes it easier to interpret.

Email Reply Rate

The black line for Reply Rate is a custom calculation of Replies ÷ Emails, and is a truer measure of efficiency. So now, we can start asking questions that will influence SDR's behavior. How is SDR 2 maintaining such a high email volume and reply rate simultaneously? What can SDRs 1, 8, and 9 learn from 2, 5, and 6 about increasing replies?

Look back at the Leads ID'd per Company visualization above. It seems like SDR 1 is spending too much time ID'ing a suboptimal number of leads per company, as time could be better spent on crafting personalized messaging to increase responses. Combining these modes of thinking and analysis is a powerful way to impact the team's behavior.

There are a whole slew of factors to optimize around: departmental messaging, industry-based messaging, company size, time of day and day of week, etc. Teasing out these best practices is a great topic for 1:1s or for team meetings.

Results & Efficiencies

The main success metric for Outbound SDRs is the number of Opportunities they are creating for the Sales team. Coupled with the activity-based metrics, we use the Opp metric as the basis to truly understand SDR efficiency, as you can see above. Emails per Opp is simply Email Count ÷ Opportunity Count.

SDR 3's Email efficiency needs work – let's understand what SDRs 2 & 7 are doing differently to keep that rate low. SDR 8 is making the most of the Replies he's getting, and turning those interactions into Sales Opportunities at the best clip – how is he positioning & describing Looker compared to his peers?

You're not going to find all the answers simply by doing this analysis. The real insights come from asking questions, challenging assumptions, and constantly working together to find ways to improve individual and team process.

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The world of Outbound prospecting is complex, and any insights that help mitigate that complexity is worth pursuing. Data and quantitative analysis is a great starting point, but meaningful conversations and ideas that impact behavior is the end-goal. I'm proud of how our team continues to push themselves to higher levels, and it's all powered by this kind of analysis and thinking.