# Content Marketing Workflow

> Research, draft, optimise and publish a marketing article end to end

| | |
|---|---|
| **Category** | Content Creation |
| **Type** | Multi Tool |
| **Difficulty** | Beginner |
| **Automation** | Semi-automated |
| **Runtime** | ~1h 35m |
| **Est. cost** | $2.4 |
| **Version** | 1.0.0 |

## Purpose

Turn a topic into a published, optimised article without the usual week of back-and-forth. The workflow covers the full path — research, outline, draft, optimise, review, publish, measure — and names exactly which tool does what at each stage.

It is deliberately semi-automated: the AI does the research synthesis and the first draft, a human owns the edit and the final approval. That split is what keeps the output publishable.

## Problems solved

- Blank-page paralysis at the start of every brief
- Inconsistent tone across writers and freelancers
- SEO treated as an afterthought instead of an input
- No repeatable process, so quality swings article to article

## Benefits

- Repeatable quality — the same steps every time
- SEO built into the outline rather than retrofitted
- The human review point is explicit, not assumed
- Every step names its tool, so the process survives staff turnover

## Limitations

- Factual claims still need a human check — the draft will state things confidently that are wrong
- Competitive keyword research needs a paid SEO tool to be worth much
- Does not replace subject-matter expertise on technical topics
- Image generation rights vary by provider — check before publishing

## Success metrics

- Time from brief to publish-ready draft
- Organic sessions per article at 90 days
- Editor changes required per draft
- Cost per published article

## Prerequisites

- **Api key** — OpenAI or Anthropic API key
- **Account** — SEO research tool _(optional)_
- **Account** — CMS with an API
- **Credits** — Image generation credits _(optional)_

## AI tools used

- **ChatGPT**
- **Claude**
- **Jasper**
- **Copy.ai**

## Steps

### 1. Topic and audience research

Establish what the audience already knows, what the top-ranking pages cover, and where the gap is. This is the step people skip, and it is why most AI content reads generic.

- _Tool:_ Perplexity
- _Model:_ GPT-4o
- _Time:_ 15 min

```text
You are a content strategist. Research the topic "{{topic}}" for an audience of {{audience}}.

Review these competitor pages: {{competitor_urls}}

Produce:
1. What every competitor covers (the table stakes)
2. What NONE of them cover (the gap)
3. Three angles that would differentiate our piece
4. The five questions a reader most wants answered

Be specific. Do not pad. If the gap is small, say so.
```

> ⚠️ Verify any statistic it surfaces against the original source before it reaches the draft

### 2. Keyword and SERP analysis

Pick one primary keyword and a handful of secondaries with real volume, and note the search intent the SERP is actually rewarding.

- _Tool:_ Surfer SEO
- _Time:_ 10 min

### 3. Outline generation

Turn the brief and keyword set into a section-by-section outline, with the argument each section makes.

- _Model:_ Claude Sonnet
- _Time:_ 8 min

```text
Using this research brief and keyword set, write a section outline for an article of about {{word_count}} words.

Brief: {{brief}}
Primary keyword: {{primary_keyword}}
Secondary keywords: {{secondary_keywords}}

For each section give:
- The H2
- The single point that section makes
- Which keyword it naturally serves
- Roughly how many words

The outline must build an argument, not list topics. No section should be skippable.
```

### 4. Draft generation

Generate the draft section by section against the outline. Section-by-section beats one long generation: tone holds, and you can regenerate one part without losing the rest.

- _Model:_ Claude Sonnet
- _Time:_ 12 min

```text
Write the section "{{section_heading}}" of an article titled "{{title}}".

The point this section makes: {{section_point}}
Brand voice: {{voice_guide}}
Target length: {{words}} words

Rules:
- Lead with the point, then support it
- Concrete examples over abstract claims
- No filler phrases ("in today's fast-paced world", "it's important to note")
- Do not repeat what earlier sections covered: {{previous_sections}}
```

### 5. SEO optimisation pass

Check keyword placement, heading structure, internal links, meta title and description, and image alt text.

- _Tool:_ Surfer SEO
- _Time:_ 10 min

> ⚠️ Do not stuff to hit a content score — a readable article that scores 78 beats an unreadable one that scores 95

### 6. Human review and fact check

A person reads the whole piece, verifies every factual claim and statistic against its source, and makes the edit. This step is not optional.

- _Time:_ 30 min

> ⚠️ Skipping this step is how organisations publish confident falsehoods under their own brand

### 7. Publish

Push to the CMS with meta fields, hero image, canonical URL, internal links and schema.

- _Tool:_ WordPress
- _Time:_ 5 min

### 8. Measure and iterate

Schedule a 30/60/90-day check on impressions, position and conversions, and feed what you learn back into the outline prompt.

- _Tool:_ Google Search Console
- _Time:_ 5 min

## FAQ

**How long does this actually take end to end?**

About 95 minutes of wall-clock time per article once the prompts are tuned, of which roughly 30 is human review. The first two or three take longer while you calibrate the voice guide.

**Can I automate the human review step?**

You can automate the checks — readability, keyword placement, broken links — but not the judgement. Someone has to verify the factual claims, because the draft will state wrong things fluently.

**Which model should I use for drafting?**

Any current frontier model produces a usable draft. The bigger lever is outline quality and the voice guide, not the model choice.

**Do I need a paid SEO tool?**

For step 2, effectively yes — free keyword data is too coarse to pick between close options. The rest of the workflow runs without one.

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_Exported from AIToolsay — https://invitationbuddy.com/workflows/content-marketing-workflow_