Skip to content
Imagine
Book a demo

LinkedIn for Customer Support AI companies

The median Customer Support AI founder or executive's typical LinkedIn post gets about 45 reactions, 1.16x the benchmark-wide median of 39. The best performing post type in Customer Support AI is personal story at 1.95x the author's own typical post, while the most posted type, industry insight, earns 0.73x.

Last updated
Oct 19, 2026
Written by
Sky Yang, Co-founder and CEO
How we wrote this
Public aggregates for Customer Support AI from the Imagine AI benchmark of 1,000+ B2B companies.
Book a DemoCustomer Support AI on the benchmark

Customer support AI is a crowded, fast-moving category sold to support and CX leaders. The founders who post about what they are seeing in real deployments get noticed.

Founders and execs45Median typical post, reactions, 90 accounts. All industries: 39.
Company pages25Median typical post, reactions, 16 pages.
At or above YC median31.4%Of fitted Customer Support AI accounts, against the median YC founder (49 reactions).

Source: Imagine AI Benchmark (benchmark.useimagine.ai), public aggregates, data through Oct 19, 2026. Lift = a post type's reactions as a multiple of each author's own typical post (geometric mean), so big accounts do not skew it. CC BY 4.0. Full dataset.

What works in Customer Support AI

Reactions as a multiple of each author's own typical post. Industry Insight is the most posted type here, at 23% of posts.

  • Personal Story7.1% of posts1.95x
  • Company Update4.7% of posts1.47x
  • Celebratory Announcement6.7% of posts1.38x
  • Hiring / Recruiting9.3% of posts1.33x
  • Event19.7% of posts0.92x
  • Meme / Humor1.7% of posts0.9x
  • Customer Highlight8% of posts0.86x
  • Product Update19.7% of posts0.79x
  • Industry Insight23% of posts0.73x
Fig. 01: Post types in Customer Support AI, dashed line at 1x. Source: Imagine AI Benchmark (benchmark.useimagine.ai), public aggregates, data through Oct 19, 2026. Lift = a post type's reactions as a multiple of each author's own typical post (geometric mean), so big accounts do not skew it. CC BY 4.0.

Which formats to use

Across the whole benchmark, as a multiple of the account's own typical post.

  • Multi-image1,115 posts2.1x
  • Image2,984 posts1.43x
  • Video1,603 posts1.18x
  • Document324 posts0.89x
  • Text Only3,192 posts0.71x
Fig. 02: Formats, dashed line at 1x. Source: Imagine AI Benchmark (benchmark.useimagine.ai), public aggregates, data through Oct 20, 2026. Lift = a post type's reactions as a multiple of each author's own typical post (geometric mean), so big accounts do not skew it. CC BY 4.0.

Three posts to try in Customer Support AI

What the agent can do.

The agent has its own computer and browser, so it finds the people and the news itself, then drafts every post, comment, connection note and message for you to approve.

[01]On

Writes in each person's voice

Drafts for the company page, founders, executives and employees from each person's best posts. Imagine AI started as the operating system for ghostwriting teams, so sounding like you is the core of the product.

[02]On

Designs the graphics

Multi-image posts, infographics and visuals from your brand kit, made in its own sandbox, with the right people and companies tagged.

[03]On

Has its own computer and browser

It does the legwork itself: finds the people, checks job changes, launches and funding news, reads the sources and fact-checks claims before anything ships.

[04]On

Engages for you

Comments, connection requests and messages on LinkedIn, aimed at the people your posts pull in who match your ICP.

[05]On

Runs one calendar for the team

Plan launches, sequence posts, schedule comments and edit together. Approvals sit with each person or route through one owner.

[06]On

Works from your content filesystem

Positioning, brand kit, decks, campaigns and compliance rules in one place it reads before every draft, remembered across threads.

[07]On

Turns what you have into posts

Events, podcast episodes, videos, decks and call notes become a week of posts across the team.

[08]On

Knows what works

Reads the public benchmark of 1,000+ B2B companies and tracks your competitors, so post types and formats follow your industry's data.

[09]On

Finds the buyers in your audience

Matches everyone who engages to your ICP and hands sales a worked list every week.

[10]On

Maps content to revenue

Connects to HubSpot or Salesforce and traces each closed deal back to its first content touch: post, person, deal stage moves.

[11]On

Plugs into your stack

Engager data over API and webhooks, and the benchmark over MCP for your own agents.

One agent. It starts with LinkedIn.

Always-on publishing

It drafts the post and the graphic

Ask once. It researches, writes in each person's voice, designs the graphic and puts it on the calendar for review.

See it draft a post
Autonomous creation
Fig. 03A: The agent drafts the post and its graphic from Sky's best posts.
Engagement

It comments, connects and messages

It finds the engagers who match your ICP, comments on their posts, sends connection requests and drafts a note. You approve.

See it engage
Engagement
Fig. 04: The agent comments, connects and messages the engagers who match your ICP. You approve.
Team orchestration

One calendar for the whole team

The company page, founders, executives and employees in one plan.

Plan our week
Team calendar
Fig. 03C: One month for the whole team. Add a post, move it, it is scheduled.
Institutional knowledge

It works from your filesystem

Positioning, brand kit, decks and campaigns it reads before every draft.

Open file
Content Filesystem
Fig. 03D: Strategy, positioning and brand files the agent reads before every draft.
Research intelligence

It knows what works

It reads the benchmark of 1,000+ B2B companies before it writes.

See our research
Growth research
Fig. 03E: The agent answers from our YC founder study.

Questions teams ask first.

Method: benchmark methodology