Skip to content

Content Strategist

Content Strategy Development

Enhances✓ Available Now

What You Do Today

Define the content strategy — audience personas, content pillars, channel priorities, editorial calendar, and KPIs. Align content efforts with business objectives and customer journey stages.

AI That Applies

AI-powered content gap analysis that identifies topics your audience searches for that you haven't covered, benchmarked against competitor content coverage.

Technologies

How It Works

The system takes the content brief — topic, audience, constraints, and style guidelines — as its starting input. NLP models process the text input by identifying entities, classifying intent, and extracting the structured information needed for downstream decisions. The output is a first draft that captures the essential structure and content, ready for human editing and refinement.

What Changes

Strategy starts with data. AI shows exactly where content gaps exist, what competitors rank for, and which topics have the highest intent signals — before you plan a single piece.

What Stays

Strategic vision. Deciding what the brand should be known for, which conversations to own, and how to differentiate requires creative and brand judgment.

What To Do Next

This section won't tell you what your numbers should be. It will show you how to find them yourself. Every instruction below produces a real, verifiable result in your organization. No benchmarks, no projections — just the steps to build your own evidence.

1

Establish Your Baseline

Know where you are before you move

Before adopting AI tools for content strategy development, understand your current state.

Map your current process: Document how content strategy development works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Strategic vision. These are the boundaries AI won't cross.
Assess your data readiness: AI tools for this area need data to work. Check whether your organization has the historical data, integrations, and data quality to support Natural Language Processing tools.

Without a baseline, you can't measure whether AI actually improved anything. You'll adopt tools without knowing if they're working.

2

Define Your Measures

What to track and how to calculate it

Time per cycle

How to calculate

Measure how long content strategy development takes end-to-end today, then after AI adoption.

Why it matters

The most visible improvement is speed. If AI doesn't save time, question whether it's adding value.

Quality of output

How to calculate

Track error rates, rework frequency, or stakeholder satisfaction scores before and after.

Why it matters

Speed without quality is just faster mistakes. Measure both.

When to check: Check after 30 days of consistent use, then quarterly.
The commitment: Give new tools at least 30 days before judging. The first week is always awkward.
What NOT to measure: Don't measure AI adoption rate as a KPI. Adoption follows value — if the tool helps, people use it.
3

Start These Conversations

Who to talk to and what to ask

your CMO or VP Marketing

What's the biggest bottleneck in content strategy development today — and would AI address the bottleneck or just speed up something that's already fast enough?

They set the AI investment priorities for marketing

your marketing automation admin

How much of content strategy development follows repeatable rules vs. requires genuine judgment — and can we quantify that?

They know what capabilities exist in your current stack that you're not using

a marketing ops peer at another company

Which training programs have the highest completion rates, and which have the lowest — what's different?

They've likely piloted tools you haven't tried yet

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.