How LinkedIn's New Saves and Sends Metrics Should Change What Your Team Tracks

LinkedIn added saves and sends as native analytics metrics in early 2026, giving teams two new data points that were previously invisible. Before this change, the only engagement signals available were likes, comments, and impressions. Saves and sends capture something different, though. A save means someone found the content worth returning to. A send means someone thought it was worth passing along privately. Both actions happen quietly, which is why they matter for teams that report on content performance.

What changes operationally

Most team reporting templates are built around likes, comments, shares, and impressions. Those metrics are easy to count and easy to compare week over week. Saves and sends do not fit neatly into that existing structure, because they measure a different kind of value.

A post with low likes but high saves is performing well for a different reason than a post with high likes but zero saves. If your reporting template treats all engagement as one number, saves and sends will get buried. Teams need a separate line for each metric, or at minimum a distinct category that separates visible engagement from private engagement.

LinkedIn introduced these metrics to give creators better visibility into how content circulates beyond the feed. For teams, the operational consequence is that content review meetings now need to account for two new dimensions. A post that looked average in last week's report might actually be one of your best performers once saves and sends are factored in.

What teams need to consider

Reporting templates need updating: If your team uses a weekly or monthly reporting spreadsheet, add columns for saves and sends. Do not fold them into a combined engagement number. These metrics reveal behavior that likes and comments miss, and combining them defeats the purpose.

Content scoring models shift: Many teams rank posts by total engagement or engagement rate. Saves and sends should carry weight in that ranking, but how much weight depends on your goals. A team focused on thought leadership might weight saves heavily, since saving indicates reference value. A team focused on reach might weight sends more, since sending extends distribution through DMs.

Review frequency may need adjusting: Saves and sends tend to accumulate more slowly than likes. A post might get most of its likes within the first few hours, but saves can trickle in over days. If your team reviews content performance 24 hours after publishing, you may be evaluating saves too early. Consider a secondary review at the 72-hour mark for a more complete picture.

Historical baselines do not exist yet: Because these metrics are new, teams have no baseline to compare against. The first two to three months of data should be treated as a calibration period. Set expectations with stakeholders that early numbers are directional, not definitive.

Where coordination is required

Content and analytics teams need to agree on definitions before reporting starts. What counts as a "good" save rate? How do you compare sends across post types? These questions do not have universal answers, but each team needs internal alignment so that reporting stays consistent.

If your organization publishes LinkedIn content across multiple accounts or departments, coordination becomes even more relevant. A company page, an executive account, and a regional account will each generate different save and send patterns. Teams managing multiple LinkedIn presences should decide whether to report these metrics per account or in aggregate, and document that decision so it does not get revisited every reporting cycle.

There is also a cross-platform angle. If your team manages both LinkedIn and Instagram, saves on LinkedIn can inform your Stories strategy. Content that gets saved likely has reference value that translates well into multi-slide Story sequences. Tools like Storrito make it straightforward to schedule and auto-post those Stories with link stickers, polls, and other interactive elements, so the team managing Instagram does not need to rebuild the workflow from scratch.

Implementation impact

1. Update your reporting template to include saves and sends as separate columns. Do not merge them into existing engagement totals.
2. Agree on weighting. Decide how saves and sends factor into your content scoring model. Write it down and share it with anyone who touches the reporting process.
3. Adjust your review timeline. Add a second review window at 72 hours for posts where save and send data is still accumulating.
4. Set a calibration period. Flag the first 8 to 12 weeks of data as baseline-building. Use that window to establish internal benchmarks before making strategic decisions based on these metrics.