10 ChatGPT Marketing Examples to Improve Your Workflows

If you’ve been following the evolution of ChatGPT, you’ve likely seen the hype around custom GPTs. They’re tailored AI assistants trained on your business’s own content, data, and processes.

But what does that actually look like in a modern B2B marketing team?

At Cognism, we’ve gone all in. From SEO to content, sales enablement, and messaging QA, our team has built and deployed a range of custom GPTs to improve how we work without slowing us down.

In this article, we’re lifting the lid on our internal AI toolkit. These are real ChatGPT marketing examples from our team, designed to solve real problems, streamline complex workflows, and give us back time for the strategic work that matters.

1. LinkedIn Ad Copywriter GPT: Faster ad creation

One of the biggest time drains in paid social is writing LinkedIn advertising copy that feels fresh, tailored, and aligned with different personas and regions. It’s easy to get stuck rewriting the same lines or second-guessing whether a visual and headline really work together.

That’s where our LinkedIn Ad Copywriter GPT comes in. It’s designed to generate high-quality, persona-specific ad copy at scale, taking into account LinkedIn’s character limits, ad formatting best practices, and localisation needs.

Whether you start with a product description or upload an image from a campaign, the GPT can create three distinct ad variants, each written with a different emotional trigger in mind: urgency, curiosity, or emotional resonance.

From there, we can layer on follow-up prompts to tailor messaging by vertical (e.g. SaaS, Manufacturing), persona (like RevOps or Demand Gen), or region (such as DACH, with German-language output).

The result?

We can rapidly spin up creative options, A/B test messaging across markets, and localise our campaigns, without needing to rewrite everything from scratch each time.

It’s helped our team move faster, reduce creative bottlenecks, and spend more time on what actually improves performance: testing and optimisation.

2. Landing Page Generator GPT: Faster landing page creation

Building landing pages for paid campaigns used to be a slow, manual process. Drafting a single page could take up to two hours, especially when you factor in back-and-forth QA, aligning with brand messaging, and finding the right proof points or case studies to include.

To speed things up, we created a Landing Page Generator GPT. It uses a consistent, high-converting structure that mirrors Cognism’s HubSpot template layout and messaging house.

All we need to do is input the target theme and SEO keywords, and the GPT returns a fully drafted landing page, complete with persuasive CTAs, integrated proof points, and links to relevant case studies.

The copy follows best practices for conversion and is aligned with our tone of voice out of the box.

So far, it’s cut page creation time from over an hour to just a few minutes, with early QA reviews showing only minor tweaks needed before publishing. It’s made scaling paid campaign pages significantly more efficient, without sacrificing quality.

3. Competitor Comparison GPT: Faster competitor insights

Sales teams constantly ask for quick-fire comparisons against competitors, especially lesser-known ones that don’t already have a battlecard.

Before, this meant digging through internal docs, Slack threads, and scattered notes. Now, we use a Competitor Comparison GPT to simplify that process.

You can ask the GPT for a head-to-head comparison, and it returns a structured summary that includes pricing, key strengths and weaknesses, and clear differentiators.

It pulls from a mix of internal documentation and public-facing sources, so the output is grounded in what’s already known, but formatted for quick understanding.

It’s not 100% hands-off; there’s still a need to cross-check for accuracy, but it’s dramatically reduced the time spent gathering competitor insights from scratch.

4. Messaging House GPT: Unified brand messaging

To keep all of our custom GPTs aligned with Cognism’s tone of voice and brand positioning, we’ve developed a central Messaging House GPT. 

The idea is simple but powerful:

Instead of relying on team members to manually reference tone of voice docs or positioning guidelines, this GPT will act as the master source of truth for all content marketing generation.

We’ve uploaded our full style guide and messaging house into the GPT and keep it regularly updated. Other GPTs, like the LinkedIn Ad Copywriter or Landing Page Generator, will reference this master instance, ensuring everything from ad copy to campaign pages stays on brand, uses the right terminology, and reflects the most recent messaging updates.

The goal is to reduce brand drift, ensure fresh positioning is instantly reflected everywhere, and shorten feedback loops by getting content closer to the mark on the first draft.

5. LLM Content Reviewer: Optimising for AI discovery

As more B2B buyers begin their research inside tools like ChatGPT, Perplexity, and Claude, we needed a way to ensure our content was not only showing up, but showing up with authority.

The challenge?

Understanding how content is selected, cited, or ignored by LLMs is still a bit of a mystery.

To help navigate this, we built a custom GPT trained specifically to review articles against the kinds of criteria LLMs use when surfacing content. It looks at factors like clarity, topic depth, brand authority, and citation structure - essentially giving us a clearer framework for writing content that’s more likely to be referenced by AI marketing tools.

Using it is simple:

• You paste in a live article URL, and the GPT returns a detailed audit: what’s working, what might be confusing, where coverage could go deeper, and how well the content aligns with best practices for AI visibility.
• It finishes with a checklist of actionable improvements designed to boost your chances of being featured in LLM results.

While it’s still difficult to track exact attribution from LLMs, we’ve already seen an increase in referral traffic from AI tools.

Even if this GPT isn’t the sole driver, it’s become a valuable step in our publishing workflow, especially as AI becomes a more common discovery channel.

6. Blog Writer GPT: Speeding up SEO production

Creating high-quality SEO content that ranks and sells is no small feat. It’s not just about writing; it’s also about briefing, researching, framing, optimising, and authentically weaving in the product narrative.

That’s where our Blog Writer GPT comes in!

We trained this custom GPT on our best-performing blog formats, incorporating Cognism’s tone of voice, SEO structure, and value propositions.

It now acts as a rapid first-draft engine for listicles, competitor comparison pages, and solution-led articles, each one built to speak in our voice and position Cognism naturally as the solution.

Using it is straightforward. You pick a blog format, such as a listicle or competitor page, then answer a few context-gathering prompts. The GPT returns a full draft aligned with SEO best practices, including keyword targeting, CTA placement, and product messaging.

While we’re still ironing out a few quirks (like its occasional reluctance to write full paragraphs), it’s dramatically reduced the time we spend on early-stage research and framing.

For high-intent or lower-funnel SEO content, it’s become a solid foundation to build on.

7. Cognism ToV Reviewer: Keeping messaging consistent

As more teams contribute to marketing, whether it’s sales writing emails, product managers suggesting website copy, or partners drafting ads, brand consistency can start to slip. Manually reviewing every piece of content is time-consuming and often subjective.

To solve this, we created the Cognism Tone of Voice Reviewer GPT. It acts as a virtual brand editor, checking any piece of content, including blog posts, emails, landing pages, and ads, against our internal tone of voice guidelines. 

The GPT evaluates everything from structure and formatting to clarity of messaging, CTA strength, and even competitor references.

The workflow looks like this:

• Paste or upload your content, and the GPT returns specific, actionable feedback.
• It highlights what’s working, flags what’s off-brand, and suggests sharper, more on-tone alternatives.

Since rolling it out, we’ve significantly reduced the time spent QA’ing content and ensured our messaging stays consistent across a growing, distributed team.

8. Case Study Finder GPT: Sales enablement on demand

One of the most common questions the content team used to get was: “Do we have a case study for this?”

Whether it was sales prepping for a call or marketing building a campaign, finding the right customer story was often manual and inefficient. Most people defaulted to asking someone on the team or just gave up.

To fix this, we built the Case Study Finder GPT. It’s trained on our entire case study library and designed to surface the right story based on criteria like region, industry, use case, or outcome.

Using it is simple:

Just ask a question like, “What are our strongest UK-based case studies?” and the GPT will return a shortlist that includes the region, the challenge or use case, key results, and a direct link to the asset.

It’s not perfect - it sometimes shares extra links we didn’t ask for - but it’s already made a big difference.

Teams can now self-serve faster, sales can build more compelling decks and follow-ups, and the content team can focus on creating new assets instead of digging through old ones.

9. Case Study Drafting GPT: Faster content production

Producing case studies used to be one of the more resource-heavy parts of our content engine.

Between formatting, writing from scratch, and sometimes outsourcing to freelance writers, each story required a significant lift.

So, we needed a faster, more scalable way to turn great customer interviews into publishable assets. Enter the AI-Generated Case Study Drafting GPT.

We take the transcript from a customer interview (usually a video or written Q&A), combine it with a few examples of existing Cognism case studies, and prompt ChatGPT to generate a new story following our trusted format of challenge, solution, and results.

The output is surprisingly strong. With just a few light edits, the draft is usually ready to send to the customer for sign-off.

What used to take several hours or involve external help now takes a fraction of the time.

As a next step, the team is working on building a dedicated custom GPT version so this workflow can be used more widely across the business, with consistent formatting, voice, and messaging baked in.

10. SME Insight GPT: Faster research, better content

One of the most valuable inputs to our content is the perspective of subject matter experts (SMEs), from podcasts, interviews, and internal calls.

But until recently, those insights were trapped in 45-minute transcripts, making it time-consuming to find the right quote for a blog or thought leadership piece.

To solve this, we created a custom GPT trained on SME transcripts.

Every time we finish a B2B influencer interview, we upload the transcript to a shared file. Those documents are then fed into a custom GPT that acts as a live, searchable knowledge base of expert insights.

When writing new content, we can now prompt it with questions like, “What have our experts said about ABM?” or “Any quotes from X on targeting enterprise buyers?” and it instantly pulls relevant, pre-vetted quotes.

The result?

A huge reduction in manual search time and a much smoother process for embedding real expertise into our content. The team now spends less time trawling through transcripts and more time crafting narrative and sharpening the story.

The real impact of custom GPTs in B2B marketing

What all of these examples have in common is that they’re not just experiments; they’re embedded workflows. Each custom GPT we’ve built has helped us save time, reduce friction, and improve the quality or consistency of our output.

But more than that, they’ve unlocked a new way of thinking.

Instead of asking, “Can AI do this for me?”, we now ask, “Where are we losing time, and could a custom GPT help us get it back?”

That shift in mindset has made us more agile, more consistent, and more strategic in how we operate as a marketing team.

Whether it’s writing better copy, speeding up SEO production, enabling sales, or ensuring brand consistency, custom GPTs have become our quiet force multipliers, working in the background so our team can focus on the work that truly moves the needle.

And we’re just getting started.

As the tools evolve and our library grows, we’ll keep sharing what’s working and what’s not to help other B2B teams build smarter, more scalable marketing engines with AI.