AI Personalization for Campaigns

Most outreach tools personalize from a business card.

They know a lead's name, title, company, maybe industry. Sometimes a headline. That is not real context. That is identity data.

getsignals works differently.

Our AI Personalization is built around the full context of why the lead was surfaced in the first place and what that person is actually saying, posting, commenting on, and engaging with.

That is the foundation of a Signal-first system.

What makes AI Personalization different in getsignals

In getsignals, personalization is not just about filling in {{first_name}}.

It is about carrying the full context of the lead into every action, including:

• the Signal that surfaced them

• the post or comment that put them on your radar

• their recent social posts

• the posts they have commented on and what they said

• the saved comment thread on that post

• their full social profile footprint (65+ insights like work history, education, bio and more)

• their company context (what do they do, who do they serve, what problems do they solve?)

• their company social post history (hiring, launches, fundraising and other key moments)

• your own firmographics, including value proposition and ICP.

That means outreach can be written from:

• what they are thinking

• what they are reacting to

• what problem they seem to be experiencing

• what kind of timing signal they are giving off

That is very different from generic AI outreach.

Think of personalization as 4 layers

In getsignals, campaign copy usually comes from four layers:

1. Merge variables

These are the {{...}} values that fill in real data from the lead, Signal, sender, workspace, or campaign.

Example:

• {{first_name}}

• {{company}}

• {{signal_post_snippet}}

• {{target_comment_history}}

• {{list_post_comments}}

2. AI Writer

These are [[AI:...]] instructions that tell the model how to write based on the context available.

This is where getsignals becomes much more powerful than simple merge-field personalization.

3. Mentions

These are special mention tags such as:

• {{mention:author}}

• company page mention variants

Mentions matter most in comments, where the goal is to join a live public conversation naturally. These can be easily added to your comment templates through our Personalization options in the UI.

4. Spintax

This is controlled variation using: [[Spin: option A | option B | option C]]

Spintax helps create small copy variations. While it does not replace context, it does make it an incredible option for testing angles and positioning - while also not looking like a templated spam to social networks.

What context AI can use

Depending on the step, AI can work from:

Lead identity and profile context

• first name

• full name

• company

• title

• headline

• location

• industry

Signal context

• signal name

• post snippet

• full post text

• post URL

• topic

• keyword

• post reaction count

• post comment count

• post repost count

• the lead's own comment on the signal post

• the post author's name and headline

• the saved list of comments on the signal post

Social intelligence and context

• the lead's recent posts

• the posts the lead has commented on

• recent posts from the lead's company page

• a structured prospect research brief generated for AI

Sender and campaign context

• sender name

• sender company

• sender title

• campaign name

• workspace firmographics

This is what allows the AI to write from real buyer intelligence instead of generic profile data.

Variable availability depends on the step

This part matters.

The same broad context system powers the campaign, but different steps are better suited to different kinds of variables.

Connection Notes

Connection notes are the most constrained copy surface.

They are short, high-pressure, and should stay focused.

Best-fit variables for notes

Use compact variables such as:

• {{first_name}}

• {{company}}

• {{title}}

• {{headline}}

• {{signal_post_snippet}}

• {{post_topic}}

Best use of AI in notes

AI works well here when you want one short, natural sentence written from:

• a post idea

• a headline

• a role/company combination

• the specific Signal context

Important limitation

Connection notes have a 300-character limit after merge and AI output.

That means you should treat notes as a compact personalization surface, not a place for long research-heavy prompts.

Best practice

For notes, use the Signal to create relevance, not to cram in detail.

Messages

Messages are the richest standard copy surface in the campaign builder.

This is usually where the full getsignals methodology shines the most.

Best-fit variables for messages

Messages can support:

• lead identity variables

• Signal variables

• sender variables

• workspace firmographics

• social intelligence variables like:

  • {{target_post_history}}

  • {{target_comment_history}}

  • {{company_post_history}}

  • {{prospect_analysis_brief_json}}

Why messages matter most

Messages give AI enough space to actually reason with the Signal and continue the same thread.

This is where you can go beyond:

• "Saw your role at X"

and instead write from:

• what they posted

• what they said in comments

• the pattern in their recent activity

• the problem signal that surfaced them

Best practice

If your Signal is strong, the first message should feel like a continuation of the same context, not a fresh cold open.

InMail

InMail has two separate personalization surfaces:

1. Subject line

2. Message body

That distinction matters.

InMail subject line

The subject line supports:

• merge variables

• spintax

But AI Writer is not allowed in the subject line.

That means the subject should stay simple, human, and direct.

Best-fit variables:

• {{first_name}}

• {{company}}

• other short identity/context tags when useful

InMail message body

The body works much more like a standard message.

It supports:

• merge variables

• AI Writer

• spintax

This is where you can use richer Signal context and deeper AI prompting.

Best practice

Keep the subject line tight and let the body carry the real context.

Comments

Comments are different from every other surface because they are post-centric.

A note or message is mainly about the lead. A comment is about entering an existing public conversation with the right context and the right angle.

That makes comment quality heavily dependent on what the system can understand about:

• the post itself

• the author

• what other people are saying in the thread

Best-fit variables for comments

Comments are best for:

• {{mention:author}}

• company page mention variants

• {{signal_post_snippet}}

• {{signal_post_full}}

• {{post_topic}}

• {{post_author_first_name}}

• {{post_author_full_name}}

• {{post_author_headline}}

• {{contact_post_comment}} when the lead came from comment context

• {{list_post_comments}}

• {{signal.post_comments_list}}

• {{prospect_analysis_brief_json}}

Why {{list_post_comments}} matters

This is one of the most important context tags for AI-written comments.

It gives the writer a saved list of comments from the same signal post, so the model can understand not just what the author said, but also how the thread is developing and what other people are reacting to.

When you combine:

• {{signal_post_full}}

• {{list_post_comments}}

the AI can read both:

• the original post

• the surrounding discussion

That gives it much stronger context to choose the right angle for the comment.

Instead of producing a generic reply, it can write something that feels aware of the conversation already happening in public.

How mention tags work in comments

Mentions are especially important for comment steps.

{{mention:author}}

Use this when you want to tag the author of the post you are commenting on.

This helps the comment feel native to the thread and clearly directed at the person who started the conversation.

Company page mention tags

Use the company page mention variant when you want to tag one of your own company pages in the comment.

This is useful because it adds brand visibility into the thread while still keeping the comment tied to the original post discussion.

That means comments can do two things at once:

• engage the author directly

• expose your brand more visibly in the public conversation

This is one of the strongest examples of how getsignals blends Signal-first outreach with public brand presence.

Best practice for comment generation

For AI-written comments, think in this order:

1. Read the post

2. Read the thread

3. Decide the angle

4. Mention the author when appropriate

5. Tag your own page when added visibility helps

6. Write one strong, native comment

That is what makes comment automation feel credible instead of templated.

Special note: the AI Research Brief

Some of the strongest AI personalization in getsignals uses a two-step process.

When you place {{prospect_analysis_brief_json}} inside an [[AI:...]] block, the system does not treat it like a normal merge tag.

Instead, it works like this:

1. A server-side research step compiles a structured brief

2. The writer step uses that brief to generate the final output

That research brief can pull together:

• the Signal that surfaced the lead

• the lead's LI profile context

• their recent posts

• the posts they commented on

• what they said in those comments

• the full signal post

• the saved signal-post comment thread

• their company context

• sender context

• workspace firmographics

This is important because it lets AI reason before it writes.

So instead of asking the model to generate copy directly from a few variables, you can first give it a compiled research layer and then ask it to action that brief into:

• a note

• a message

• an InMail body

• or a comment

Why this matters

This is not just better prompting. It is a different architecture.

Normal merge tags insert data.
AI Writer writes from that data.
The AI Research Brief compiles the research first, then has the writer act on that research.

That is one of the clearest examples of what makes getsignals different from thin personalization tools.

Use AI for meaning, not just decoration

The best AI prompts in getsignals do not ask the model to "make this sound personalized."

They ask it to:

• understand the Signal

• read the post or comment context

• infer what the buyer actually cares about

• continue that thread naturally

That is what separates context-aware outreach from generic AI copy.

Good AI use cases

• writing a note from the idea in a signal post

• writing a message from the lead's post/comment history

• writing a comment that responds to the post itself and the comment thread

• writing a follow-up that still reflects the original Signal

• writing from the AI Research Brief when deep context matters most

Weak AI use cases

• rewriting generic outreach without real context

• stuffing too many facts into a note

• using AI when a simple merge field would do the job

• asking AI to sound personalized when the source context is thin

Use spintax for controlled variation

Spintax is useful, but it should play a supporting role.

Format: [[Spin: option A | option B | option C]]

One option is selected at send time.

Where spintax works well

Spintax is best for:

• opening lines

• transition phrases

• soft closes

• light subject-line variation

• small phrasing differences in notes, messages, InMail body, or comments

Where spintax should not lead

Do not use spintax as a substitute for context.

Spintax creates variation.
Signals create relevance.

The strongest combination is:

• Signal for timing and context

• variables for factual grounding

• AI for reasoning and message generation

• spintax for light controlled variation

Important rule

Do not nest spintax inside AI blocks or AI inside spintax blocks.

Keep them separate.

How to choose between variables, AI, mentions, and spintax

Use plain variables when:

• you just need factual insertion

• the message is already strong without generation

• you want tight control over the final wording

Use AI when:

• the message should respond to what the lead actually said

• you want the Signal context to shape the copy

• you need nuance, interpretation, or angle selection

Use mentions when:

• you are commenting on a post

• you want to tag the author directly

• you want to tag your own company page for added visibility

• you want the comment to feel native to the thread rather than detached from it

Use spintax when:

• you want light variation in otherwise stable copy

• you want repeated steps to feel less repetitive

• you want to vary subject lines, openings, or closes without changing the message strategy

The strongest pattern in getsignals

The strongest campaigns usually follow this structure:

• A Signal surfaces the lead

• Warm-up engages on that Signal context

• AI writes from the original Signal and broader buyer intelligence

• comments use post + thread context, with mentions when useful

• follow-up messages continue the same thread

• spintax adds small controlled variation around the edges

• the AI Research Brief deepens reasoning when the situation calls for it

That is how personalization stays coherent from the first touch through the inbox.

Common mistakes to avoid

Treating AI as a fancier merge field

AI should reason from context, not just restate profile facts.

Using the same prompt style for every step

Notes, messages, InMail, and comments are different surfaces. They need different prompt shapes and different variables.

Overloading connection notes

Notes should be tight. Do not try to force deep research into a 300-character space.

Writing comments like private outreach

Comments are public, post-centric, and should feel native to the thread.

Forgetting thread context on comments

If you use {{signal_post_full}} without {{list_post_comments}}, the AI sees the post but not the surrounding discussion. That can weaken the angle.

Ignoring mention strategy

{{mention:author}} is for mentioning the author of the post you are commenting on. Company page mention tags let you tag your own page to add brand visibility. Both should be used intentionally.

Relying on spintax instead of context

Variation is helpful, but it does not create relevance on its own.

Final advice

If you remember one thing, make it this:

The Signal is the reason the message should exist.

Everything else supports that:

• variables ground it

• comments add thread context

• mentions shape public visibility

• AI interprets it

• the research brief deepens it

• spintax varies it

That is why getsignals personalization feels different.

It is not writing from who the buyer is on paper.

It is writing from what the buyer is actually saying, thinking, and signaling in public.