SDR metrics to track across email, LinkedIn and calls

Open your SDR dashboard right now. You’ll see emails sent, calls made, LinkedIn invites fired off. Activity everywhere. Pipeline nowhere in sight.

That gap is the problem with most SDR metrics. Counting effort feels productive, but it tells you nothing about whether that effort turns into a meeting, let alone revenue. I’ve watched teams celebrate a rep who sent 400 emails in a week, only to find zero of them replied with real interest.

In this guide, I’ll walk through the SDR metrics that actually matter, split across email, LinkedIn and calls, with the formulas to calculate each one and real benchmarks pulled from lemlist internal data across 412.6M messages and 1.9M calls. You’ll see where your numbers stand against the average, the median and the top 10%.

The goal is to link effort to outcomes, channel by channel, so you stop managing activity and start managing results.

The three layers of SDR metrics

SDR metrics fall into three layers: activity, conversion and outcome. Activity metrics measure effort (emails sent, calls made, LinkedIn invites). Conversion metrics measure effectiveness (reply rates, connect rates, acceptance rates). Outcome metrics measure what the business actually cares about (meetings held, pipeline created).

Activity is a floor. If a rep sends zero emails, nothing else matters. But activity alone tells you nothing about quality. The real signal lives in conversion and outcome metrics, which show whether that effort turns into conversations and revenue.

The sections below walk through each layer, channel by channel, with benchmarks from lemlist internal data so you can compare your numbers to what we see across 412.6M messages and 1.9M calls.

Activity metrics

Activity metrics are inputs. They answer “did the rep do the work?” and nothing more.

Track these five:

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  New leads contacted per day or week

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  Touches per lead (emails, calls, LinkedIn messages combined)

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  Calls made

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  LinkedIn invites sent

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  Active sequences running

The reason to track them is simple: you need a baseline before you can diagnose conversion problems. A rep with a low reply rate and a handful of emails sent last week has a volume problem. A rep with a low reply rate and hundreds of emails sent has a targeting or messaging problem. Activity data separates the two.

One number worth knowing: leads who replied positively needed 5.8 touches on average in email-only sequences, compared to 3.6 touches in sequences combining email, LinkedIn and calls. Multichannel sequences get to “yes” faster because each channel reinforces the others.

Track activity as a floor, then shift your coaching conversations to conversion and outcomes.

Email metrics

Four email metrics matter for SDRs:

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  Reply rate. Total replies divided by emails delivered. This is your primary email signal.

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  Positive reply rate. Replies marked “Interested” divided by emails delivered. This filters out auto-replies, “not interested” and out-of-office messages.

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  Bounce rate. Hard bounces divided by emails sent. Keep this low to protect your sender reputation.

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  Unsubscribe rate. Unsubscribes divided by emails delivered. A rising unsubscribe rate usually means your targeting is off.

Open rate is not on this list. Privacy features in Apple Mail and Outlook now pre-load tracking pixels, which inflates open numbers. You can read more about why open rates mislead in our breakdown. Use replies as your engagement signal instead.

Where do you stand? Email reply rate averages 2.72% across lemlist campaigns, with a median campaign at 1.13%. That gap between average and median tells you a small number of high-performing campaigns pull the average up. If you’re at 1%, you’re roughly at the midpoint. For a deeper look at what drives replies, see our guide to cold email response rate.

LinkedIn metrics

LinkedIn outreach produces three metrics worth tracking:

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  Invite acceptance rate. Connection requests accepted divided by invites sent.

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  Reply rate. Replies to LinkedIn messages divided by messages delivered.

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  Positive reply rate. Same filter as email. Count only replies that signal genuine interest.

The benchmarks here are stronger than email. LinkedIn invite acceptance has a median of 27.3%, an average of 29.4%, and the top 10% of campaigns hit 53.9% or higher. LinkedIn reply rate averages 6.6%, with the top 10% reaching 19.9% or higher.

The channel works because a connection request is a softer ask than a cold email, and a LinkedIn message lands in a less crowded inbox. If you’re building a LinkedIn outreach strategy, these numbers give you a realistic target range.

Call metrics

Calls generate four metrics:

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  Dials. Total call attempts.

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  Connect rate. Calls where a human picks up, divided by dials.

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  Conversations. Connects that turn into a real back-and-forth.

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  Meetings from calls. Conversations that end with a booked meeting.

Call connect rate averages 13.8%, with a median campaign at 9.1% and the top 10% hitting 34.1% or higher. The variance is huge, and two factors explain most of it.

First, data quality. Verified phone numbers connect around 20%, while scraped lists connect around 10%. Second, timing and context. A warm call placed after a LinkedIn connection accept connects at 21.4%, compared to 9.6% for a cold first-touch call. That is more than double the connect rate just by sequencing LinkedIn before the dial.

What does this mean for daily math? An average rep working a 5.4% connect rate needs about 386 dials to book one meeting. Switch to verified, high-intent numbers at a 22% connect rate (holding conversation rate at 58% and meeting rate at 12%), and that drops to about 65 dials per meeting. Parallel dialer beta teams inside lemlist have gone from 2 to 6 conversations per hour.

For a full breakdown of calling benchmarks, see our cold calling metrics guide.

Channel benchmarks in one table

All figures below come from lemlist internal data, October 2025 to November 2026.

One more data point that belongs here: adding LinkedIn to an email-only sequence multiplies replies by 2.6x in France, 3x in the rest of the world and 3.9x in the US. If you’re running email only, that is the single biggest lever you can pull.

For more channel-level data, see our cold email benchmarks page.

Outcome metrics

Outcome metrics are the reason the other layers exist. Track these six:

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  Meetings booked. Calendar invites sent after a positive conversation.

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  Meetings held. Meetings that actually happened. This is the number that matters.

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  Show rate. Meetings held divided by meetings booked. A low show rate means your qualification or confirmation process is broken.

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  Opportunities created. Meetings that convert to a qualified pipeline opportunity in your CRM.

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  Pipeline generated. Total dollar value of those opportunities.

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  Pipeline per SDR. Pipeline generated divided by number of SDRs. This is your efficiency metric at the team level.

Count meetings held, not meetings booked. A booked meeting that no-shows creates zero pipeline. That distinction changes how you set targets.

The efficiency metric that ties effort to outcomes is touches sent per meeting booked. Email-only campaigns average 312 touches per meeting. Multichannel campaigns average 118. The top 10% of campaigns get there in 41 touches. That gap shows why multichannel sequences outperform single-channel outreach on efficiency.

We don’t have meeting-to-opportunity conversion data in lemlist, so I won’t invent a benchmark. Track it in your CRM and build your own baseline. For a framework on how pipeline stages connect, see our guide to building a sales pipeline.

How to build an SDR scorecard

A scorecard puts all three layers on one page. Here is a template:

Leave the “Target” column blank in this template. Your targets depend on your ACV, sales cycle and market. Fill them in with your team, not from a blog post.

Review weekly, but look at trends over rolling four-week windows. A single bad week is noise. Two or three in a row is a pattern. And when you coach, coach on conversion metrics. Telling a rep to “make more calls” when their connect rate is low misses the real problem, which might be data quality, call timing, or the opener they’re using.

Metrics that mislead

Four metrics look useful but distort your view:

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  Open rate. Privacy pixels inflate it. You cannot tell who actually read your email.

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  Total replies. This includes out-of-office, “remove me” and “not interested.” If most of your replies are negative, your reply rate is a vanity number.

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  Dials without connects. A rep who logs many dials and reaches few humans has a data or timing problem. Dials alone reward button-pressing.

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  Meetings booked without show rate. A rep who books many meetings but holds few is less productive than a rep who books fewer and holds more.

Every metric on this list can be gamed or inflated without moving pipeline. Strip them from your primary dashboard or pair each one with the conversion metric that gives it context.

How to track SDR metrics in lemlist

lemlist consolidates email, LinkedIn and call steps into one sequence, so all channel data feeds a single workflow. Here is how each metric gets captured:

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  Call statuses. After each call, log the outcome (connected, voicemail, no answer, meeting booked). This feeds your connect rate and conversations metric.

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  Reply sentiment. Mark replies as Interested or Not interested. You can turn on AI auto-marking to do this automatically, which gives you a clean positive reply rate without manual tagging.

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  A/B testing. Test different steps or copy variants within a sequence. Reply rate decides the winner.

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  CRM and BI sync. Send activity events to your CRM or BI tool via webhooks or the API. Or use the bi-directional field sync with HubSpot, or sync with Salesforce or Pipedrive, to keep lead statuses and activity data flowing both ways.

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  Open tracking. If you don’t use open rate (and after reading this article, you probably shouldn’t), disable open tracking per campaign to avoid inflating your data and to improve deliverability.

Final takeaway

Good SDR metrics connect effort to pipeline across every channel. Track conversion rates per channel, benchmark against real campaign data, and coach on the ratios that actually move meetings held. Strip out vanity metrics that reward volume over results.

Build your first signal-based sequence in lemlist.