How to Message Someone on LinkedIn: A Data-Driven Guide

Messaging is one of LinkedIn‘s most popular and powerful features – but data reveals users often squander its potential. Without an analytical approach, the time investment seems unlikely to pay dividends.

In this research-backed guide, we’ll demystify data around optimal messaging strategies to position you for networking success. Follow our statistics-supported game plan for crafting attention-grabbing messages, contacting passive candidates, and more.

Let the data guide your decisions as you leverage LinkedIn conversations to propel your career.

LinkedIn Messaging by the Numbers

Before strategizing your outreach, let’s examine baseline data reported by LinkedIn around usage and engagement:

Active monthly users on messaging100M+
Average monthly messages sent per user9.6
Monthly message opens per user26
Avg click-through rate on messages2.8%

With over 100 million monthly active messaging users sending 950+ million messages in total each month, the competition for attention is fierce.

Crafting content that cuts through the noise depends enormously on data-savvy strategies. Let‘s analyze tactics to boost visibility, response rates, and real career connections.

Anatomy of a Quality Message

We‘ll break down quantitative insights around optimal message structure and phrasing. Follow these statistics-backed best practices as your framework.


The right word count balances brevity with personalization. According to social media scientists Buffer, the optimal message length is:

121 to 150 words

Messages within this range have the highest interaction rates. Under 120 words prevents personalization while over 160 words risks the recipient losing interest while scrolling.

Visually, messages in the 121-150 word count tend to look roughly like this example:


Subject Line

For recipients inundated with unread messages, an analytical subject line is crucial for standing out.

According to marketing experiments by CoSchedule, subject lines demonstrating these traits convert best:

SpecificityQuick question about optimizing Twitter ad targeting
UrgencyTime-sensitive open data scientist position
PersonalizationFollowing up on the MongoDB discussion, Sara

Subject lines should instantly communicate relevance to compel opening compared to 200+ other messages competing for attention.

Optimal Messaging Cadence

Beyond individual message quality, you need to determine an effective messaging cadence based on response rate data.

Testing by LinkedIn revealed typical response timeframe patterns:


Key analysis:

  • 21% of all responses occur within 6 hours
  • 49% of cumulative responses within 3 days
  • 74% within 2 weeks

Therefore, following up within 7 days captures half of total respondents while still respecting recipients‘ availability.

Then, the 2nd and 3rd follow-up should happen:

  • 2nd: 11-14 days after original message
  • 3rd: 18-21 days after original message

Adhering to this system optimizes your chance of a response before persistence risks becoming annoyance.

Premium Account Impact

Upgrading to premium grants more messaging capabilities – but is the ROI measurable?

According to data aggregated by SocialPilot:

MetricWith Free AccountWith Premium Account
InMail Credits per Month025
Characters per InMailOnly 1st degree connections1,700
Attachments per InMailN/AUp to 5 files or links

This expanded word count for elaborate outreach combined with multimedia attachments to showcase work samples measurably boosts impressions. Premium also removes network constraints.

But perhaps the biggest benefit data reveals is 65% higher InMail response rates compared to basic messages. Recipients perceive the premium signal as an indicator of your professional credibility.

Considering these quantitative messaging advantages that directly bolster networking opportunities, premium easily provides a positive ROI for power users.

Crafting Effective Outreach Messages

Now that we‘ve used statistical analysis to inform messaging frequency, channel targeting, and volume, let‘s discuss qualitative factors that data still underscores as crucial.

Follow this rubric for guaranteed message quality:

Goal Strategies
  • Address them by first name
  • Mention a specific project or accomplishment
  • No templates—write each message individually
Conversational Tone
  • Use natural phrasing as if speaking
  • Ask open-ended questions
  • Share a related experience from your career
  • Introduce yourself and company
  • Explain common goals or interests
  • Include a specific ask or favor

Data proves each principle tangibly leads to elevated open and response rates. Combine them cohesively, and your messages will spark conversations and opportunities.

While the numerical focuses thus far address networking outreach, recruiting through LinkedIn messaging carries equal data-driven imperatives…

Beyond networking, tapping LinkedIn conversations for hiring provides another channel to engage elusive yet qualified talent.

The statistics again reveal precise messaging strategies yield the highest ROI of resources invested:

Data-Based TacticResult
Target passive candidates open to new rolesReduces competition as 59% of professionals are passive candidates [[1]](
Spotlight company culture in messages92% of candidates rank culture above compensation [[2]](
Highlight leadership development programsDraws Gen Z/Millennials as 93% prioritize learning opportunities [[3]](

As demonstrated, the data doesn’t lie. Tactical messaging outreach expediting results.

Thus far, we’ve quantified ideal messaging strategies – now let’s showcase built-in LinkedIn tools to further supplement effectiveness:

Utilize Saved Messages

Rather than manually rewriting recurring messages, create saved message templates to save hours:


Standardize templates for:

  • Initial Outreach
  • Follow-Up Reminders
  • Job Descriptions
  • Coordinate Interviews

Then paste these templates into new messages, customizing names/details. This batch processes communication.

According to social media scientists OkDork, saved messages can cut composition time down by over 90%. That translates to 10x more messages sent or hours regained.

Install the LinkedIn Messaging Plugin

Further enhancing efficiency, browser extensions like Reply for LinkedIn auto-populate templates and tracking:


Core features:

  • Pre-built industry/role-specific messaging templates
  • One-click responses and follow-ups
  • Read receipts for message tracking
  • Enables bulk targeted outreach

Implementing this tool allows focusing efforts on high-value personalization rather than rote responses.

Review Message Performance Analytics

Finally, consistently review messaging metrics to pinpoint areas for continued optimization:


Analyze trends in:

  • Open rates
  • Click-through rates
  • Reply rates

Compare the performance of different message types and testing new subject line phrasing, call-to-action (CTAs), etcetera. Let the data guide your strategy.

The more you actively apply learnings, the better your results compound over time.

Messaging on LinkedIn without context or planning wastes valuable effort. But our analysis demonstrates targeted, data-driven techniques maximize your networking and recruiting ROI.

In summary:

  • Craft 121-150 word messages for prime engagement
  • Personally address recipients and demonstrate common interests/goals
  • Follow up respectfully after 7 and 15 days
  • Consider premium for increased visibility
  • Save time using canned responses and browser extensions
  • Continuously track analytics around message performance

Now you have both statistical foundations and actionable best practices for elevating your LinkedIn conversations. Identify your outreach objectives, leverage the right messaging tools for the job, and let the data propel your professional community growth.

The connections made through applying this analytical approach will enrich your career and reinforce the power of data-driven decisions.

So next time you message someone on LinkedIn, do so strategically and confidently. The numbers show tangible returns await.

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