How To Use Ai In Marketing

Ai Tools
1

I recently started trying AI tools for my marketing, but I’m struggling to create content that actually brings in traffic and leads. What I’ve tried so far feels generic, and I’m not sure how to use AI for SEO, email campaigns, and social media marketing the right way. I need help figuring out a simple strategy that works.

2

Stop asking AI to write finished marketing assets from scratch. That’s why it sounds generic.

Use it for parts of the job.

  1. SEO
    Pick one keyword with buyer intent. Example, “best crm for roofing company” beats “crm tips”.
    Ask AI for:
  • search intent
  • related questions
  • content gaps from top 5 results
  • title options
  • outline

Then you write the angle. AI fills in sections, FAQs, schema ideas, meta text. You edit hard.

  1. Content
    Feed AI your real stuff.
  • sales calls
  • customer emails
  • reviews
  • support tickets

Tell it, “pull repeated pain points and objections.” That gives you content topics tied to traffic and leads, not fluff.

  1. Email
    Don’t ask for “a nurture sequence.”
    Ask for:
  • 10 subject lines for people who downloaded X
  • 3 email angles, fear, ROI, speed
  • rewrite this email at 5th grade reading level
    Short emails usualy win. One point, one CTA.

  1. Conversion
    Use AI on pages too.
    Paste your landing page.
    Ask, “what is unclear, what objections are missing, what proof should appear higher?”
    This helps more than pumping out 20 blog posts no one reads.

  2. Workflow
    My simple flow:
    keyword > SERP review > AI outline > human draft > AI edit for clarity > publish > track in GSC

Watch ctr, rankings, form fills. If traffic goes up and leads stay flat, your content topic or offer is off.

AI is a research and editing tool first. Not a replacement for your brain. Thats the shift.

3

Generic AI output usually means you skipped the strategy part and went straight to typing. That’s the trap.

I mostly agree with @codecrafter, but I’d push AI even harder on analysis, not just drafting. Use it to score your existing stuff. Drop in 10 old blog posts or emails and ask:

  • which ones target problem-aware buyers vs casual readers
  • where the CTA is weak
  • what stage of funnel each piece fits
  • what likely gets clicks vs what might get leads

Big difference there. Traffic content and lead content are not always the same thing. A post can rank and still do basically nothing for revenue. Happens allll the time.

Also, use AI for offer testing. Give it your product, audience, and 3 competitors. Ask for:

  • 5 positioning angles
  • 10 lead magnet ideas
  • objections competitors are probably handling better
    That helps way more than just pumping out more “helpful content.”

For email, I actually disagree a little with the “short always wins” thing. Sometimes short works, sometimes it just feels lazy. AI is useful for making 3 versions: short, medium, plain-text story. Then test it.

One more thing people miss: train it on your voice. Feed it past emails, sales notes, founder posts, testimonials. If you don’t, yeah, it’ll sound like bland internet soup lol.

Use AI like a strategist with amneisa, not a magician. You still have to steer it.

4

I’d add one layer neither you nor @codecrafter really hit hard enough: distribution-first planning.

A lot of AI content fails because it’s written like a finished asset instead of a content system. Before generating anything, have AI map one topic into:

  • 1 search-focused article
  • 3 LinkedIn post angles
  • 1 email teaser
  • 1 lead magnet hook
  • 1 retargeting ad concept

That forces message consistency, which usually helps leads more than just polishing a single blog post.

Also, slight disagreement on “train it on your voice” as the main fix. Helpful, yes. But even perfectly on-brand content can flop if the topic has weak intent. I’d spend more time using AI to find “money keywords” with obvious action language like compare, alternative, software, template, cost, best for, vs.

For SEO specifically, use AI to:

  • cluster keywords by intent, not just volume
  • identify pages that should target demo/book-call/signup intent
  • build internal linking suggestions between traffic posts and conversion pages
  • refresh old posts instead of endlessly publishing new ones

For email, have AI draft around one job only:

  • get reply
  • get click
  • get signup
  • get purchase

Mixed-goal emails usually underperform.

Pros of using AI in marketing:

  • faster research
  • easier testing
  • better repurposing
  • cheaper first drafts

Cons:

  • easy to publish generic junk
  • can misread search intent
  • makes bad strategy scale faster
  • often over-optimizes for clicks, not buyers

Best use case: let AI do the heavy lifting, but make humans own positioning, proof, and CTA. That’s where leads actually happen.