Is a 10% reply rate worse than a 22% reply rate? The answer depends on what earned a place in the denominator. Three recent LinkedIn outreach reports measure different populations and different kinds of reply. Their figures are useful reference points, but none supplies a universal target. Compare rates only after naming the event counted, the group eligible to produce it, and how long that group had to respond.
What the 2026 reports actually measure
HeyReach analyzed 96,051 campaigns run through its platform during its stated previous 12 months. It calls 20.75% the typical campaign connection-acceptance rate and 22.22% the typical campaign reply rate. The second figure divides replies by conversations started, not by invitations sent.
Expandi reports 13,218,869 connection requests and 6,730,447 outbound messages from May 2025 through April 2026. Its platform-wide figures are 28.5% connection acceptance, 3.0% connection-note reply, and 10.4% outbound-message reply. Those are three separate measurements, not stages of one denominator.
Reachium looks at 180,155 connection requests that had at least 30 days to mature. Of those requests, 27.11% were accepted; 27.55% of accepted connections produced a reply; and 7.47% of all matured requests produced a reply. The last two figures describe the same funnel from different starting points.
Sources: HeyReach 2026 benchmark report, Expandi 2026 benchmark report, Reachium 2026 benchmark study
Why the reply percentages cannot be ranked against one another
HeyReach's 22.22% is replies per started conversation for a typical campaign. Expandi's 10.4% is replies per outbound message across welcome and follow-up messages, group and event messages, InMails, and emails. Reachium's 27.55% is replies per accepted connection. A message, a conversation, and an accepted person are different units. Putting their percentages in a league table would compare measurement choices as much as outreach performance.
Even the acceptance rates need context. HeyReach describes a typical campaign; Expandi publishes a platform-wide figure; Reachium filters for request age. The reports cover customers of three vendors across different periods. Outreach Benchmarks did not run these studies or pool their underlying data.
Sources: HeyReach 2026 benchmark report, Expandi 2026 benchmark report, Reachium 2026 benchmark study
Calculate rates from one campaign cohort
Suppose you sent 500 connection requests at least 30 days ago. In this hypothetical cohort, 140 people accepted, you started 130 conversations, and 26 distinct people replied. Acceptance is 140 / 500 = 28%. Replies per started conversation are 26 / 130 = 20%. Replies per accepted connection are 26 / 140 = 18.6%. Replies per request sent are 26 / 500 = 5.2%. The same 26 replies yield four defensible percentages; the labels determine what each one means.
Record one row per prospect with request date, acceptance date, first conversation date, first reply date, channel, and campaign. Count people who replied once, even if they sent several messages. Keep connection-note replies separate from replies after acceptance, and decide in advance where a person who never accepted belongs. Otherwise a change in tagging or message volume can look like a change in performance.
Wait long enough, then compare like with like
Reachium's 30-day filter shows why campaign age matters. Its acceptance rate is 27.11% for matured requests and 26.34% across unrestricted requests. A batch sent yesterday has had less time to receive an acceptance or reply than a batch sent last month. Compare cohorts at the same age before deciding that a new campaign improved or declined.
Keep audience, offer, sender, and message type visible next to the rate. A change in any of them can explain a movement that the headline percentage alone cannot. When a rate falls, inspect the underlying counts first: a small denominator can swing sharply after a few responses. Then check whether the issue starts with accepted requests, started conversations, or replies. Each points to a different part of the workflow.
Sources: Reachium 2026 benchmark study
Use vendor studies as reference points, not promises
These reports observe people using each vendor's platform. Their customers, campaign setups, and reporting rules need not represent all LinkedIn outreach. Reachium discloses that its ten largest customer workspaces generated 76.19% of all requests, a concrete reason to avoid treating even a large request count as a random market sample. HeyReach excludes campaigns without a started conversation from its reply-rate distribution. Both choices affect what a published typical result can mean for your own list.
Pick the metric that answers your decision, then measure it consistently in your own cohorts. If you are choosing software, acceptance and reply rates alone cannot show whether a tool caused the outcome. The shortlist still needs evidence about workflow, cost, data handling, and account policy. No reported percentage here proves a particular tool is safer or more effective for your team.
Sources: Reachium 2026 benchmark study, HeyReach 2026 benchmark report
Have your own campaign counts? Enter them in the LinkedIn outreach response rate calculator to see each rate with its denominator.