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Director of Marketing

Plan and execute marketing campaigns

Enhances✓ Available Now

What You Do Today

Design and manage integrated campaigns across channels — email, digital ads, social media, events, content. Track performance against pipeline and brand objectives.

AI That Applies

AI-optimized campaign management that auto-adjusts targeting, bidding, and creative allocation based on real-time conversion data.

Technologies

How It Works

The system ingests real-time conversion data as its primary data source. The processing layer applies the appropriate analytical models to the structured data, generating scored outputs that surface the most actionable insights. The output is a recommended plan or schedule that accounts for the identified constraints and optimization criteria.

What Changes

Campaign optimization happens continuously. AI adjusts spend allocation based on what's producing the best results right now.

What Stays

Campaign strategy — which audiences, what messages, how to differentiate — requires creative thinking and market understanding.

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 plan and execute marketing campaigns, understand your current state.

Map your current process: Document how plan and execute marketing campaigns works today — who does what, how long it takes, where the bottlenecks are. You need this baseline to measure improvement.
Identify the judgment points: Campaign strategy — which audiences, what messages, how to differentiate — requires creative thinking and market understanding. 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 HubSpot 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 plan and execute marketing campaigns 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 current accuracy of our forecasting, and how would we know if an AI model is actually better?

They set the AI investment priorities for marketing

your marketing automation admin

Which historical data do we have that's clean enough to train a prediction model on?

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

4

Check Your Prerequisites

Confirm readiness before you invest

Check items as you confirm them.