AI for Marketing
Research, content, personalisation and campaign analysis with AI — with your judgement still in charge.
What this track covers
For marketers who want to use AI well, not just use it. Audience and competitor research, copy that still sounds like your brand, personalisation that is not creepy, campaign analysis with the numbers checked, and the ground rules on customer data, copyright and claims. Best taken after AI & Data Fundamentals.
New to AI? Every track builds on AI & Data Fundamentals.
What you will be able to do
- Use AI for audience and competitor research, and check what it returns
- Produce and edit content that stays in your brand voice
- Analyse campaign results with AI without misreading the numbers
- Set your team's AI ground rules on data, copyright and claims
Units and bites
- Unit 14 bitesAbout 12 min
AI in the marketing workflow
Where AI helps marketing work, and where your judgement stays irreplaceable.
- 3 min
Where AI fits in marketing
Three jobs AI can help with — research, creation, analysis — and the one it can't take: judgement.
- 3 min
Research, creation, analysis: choosing tools
General chatbots, marketing-specific tools, or the AI features in tools you already use.
- 3 min
A brand brief for AI
One document with your brand voice, audience and no-go list, ready to paste into any prompt.
- 3 min
Measuring the time saved
An honest way to judge whether AI is actually speeding your team up.
- Unit 25 bitesAbout 15 min
Audience and market research
Using AI to understand customers and markets — without trusting invented facts.
- 3 min
Summarising customer reviews
Turning thousands of reviews into themes, with real quotes as evidence.
- 3 min
Personas, carefully
Personas built from real data vs personas AI made up — and how to tell them apart.
- 3 min
Competitor scans
Comparing competitors' positioning, pricing and messages quickly and checkably.
- 3 min
Social listening with AI
Reading public conversation about your brand, and the limits of automatic sentiment.
- 3 min
Checking research for invented facts
Market sizes, quotes and sources that sound real but don't exist.
- Unit 36 bitesAbout 18 min
Content with AI
Drafts, variations and repurposing — with the brand voice intact.
- 3 min
Copy that sounds like you
Examples, no-go lists and editing: keeping AI in your brand voice.
- 3 min
Variations for testing
Generating headline and CTA variations that differ for real, not just in synonyms.
- 3 min
One piece, many formats
Turning one article into posts, an email and a short video script.
- 3 min
SEO and AI search
How people now find brands through AI answers, and what that means for your content.
- 3 min
Images and video
What to watch with AI-made visuals: copyright, real people and honesty.
- 3 min
Editing AI drafts
A short checklist before anything AI wrote goes live.
- Unit 44 bitesAbout 12 min
Personalisation and segments
The right message for the right person — and the line not to cross.
- 3 min
Segments vs personalisation
When customer groups are enough, and when individual personalisation is worth it.
- 3 min
Messaging at scale
Personalised email and WhatsApp messages without losing control.
- 3 min
Recommendations
How "you might also like" works and how to tell whether it helps sales.
- 3 min
When personalisation gets creepy
Data you may legally use is not always data you should use.
- Unit 55 bitesAbout 15 min
Campaign analysis with AI
Asking your campaign data questions in plain language, and checking the answers.
- 3 min
Asking AI about campaign data
Preparing the data and the question so the answer can be trusted.
- 3 min
Reading AI-made charts critically
The axes, date ranges and aggregation to check on every automatic chart.
- 3 min
Spotting what changed
Comparing periods and channels to find what drove results up or down.
- 3 min
Writing the campaign recap
An honest recap of what worked, what didn't and what comes next.
- 3 min
Questions the data can't answer
When AI sounds sure about "why" but the data only shows "what".
- Unit 65 bitesAbout 15 min
Risk, privacy and brand safety
Customer data, copyright, disclosure, and AI ground rules for your team.
- 3 min
Customer data and the law
What Indonesia’s data-protection law means for customer data you put into AI tools.
- 3 min
Copyright and AI content
Who owns AI-made content, and the risk of copying someone else's work.
- 3 min
Disclosure
When and how to tell your audience that AI helped make something.
- 3 min
When brand voice fails
Embarrassing public AI mistakes, and how to prevent them.
- 3 min
An AI policy for your team
One page of ground rules: which tools, which data, and who signs off.
Questions about this track
Learning
How long does AI for Marketing take?
About 87 minutes in all: 6 units made of 29 bites of about three minutes each, and every bite ends with a quick check. You can do one bite a day or several in a row.
Do I need to know how to code?
No. Every Datamew track is written for working professionals without a technical background. Where there is arithmetic, it is the kind you can do on a phone or in a spreadsheet.
Where should I start?
Everyone begins with AI & Data Fundamentals, which covers how AI works, how to write a good prompt and how to read data honestly. Then take AI for Marketing for your role.
When can I start learning?
Datamew is coming to iOS and Android soon. There is no release date or price announced yet: join the waitlist and we will tell you when the app is out.
Is it available in Bahasa Indonesia?
Yes. Datamew is written in English and Bahasa Indonesia.
More tracks
- AI & Data FundamentalsHow AI works, how to instruct it, and how to read numbers honestly.
- Data Analytics for MarketingMetrics, funnels, A/B tests, attribution and cohorts — the numbers behind marketing decisions.
- Data Analytics for HRPeople analytics: turnover, hiring, engagement and pay fairness — with privacy protected.
- Forecasting for Retail & E-commerceForecast demand, plan stock, and be ready for Ramadan, 11.11 and 12.12.
- Forecasting for MarketingForecast traffic, leads and campaign results, and defend the numbers in the budget meeting.
- Forecasting for FinanceBudgets, revenue and cash forecasts, rolling forecasts and scenarios, with spreadsheet arithmetic.
- Product Recommendation for E-commerceHow "you might also like" works, the data behind it, bundles, and how to measure the impact.
- Product Recommendation for Retail & MediaLoyalty programmes, personal vouchers and "watch next": recommendations beyond the online shop.
Read while you wait
Guides from the Datamew team, free on the web today.
AI Engineer Career Path: Roles, Skills, Salary and a Realistic Roadmap (2026)
An AI engineer builds products on top of existing AI models, such as ChatGPT-style chatbots, document search and AI agents. Most do not train models from scratch. Instead, they connect models to data, tools and users, then test that the results are reliable.
9 min read
How to Write a Good Prompt: A 5-Part Framework for Work
A good prompt gives the AI five things: context, task, input, format and limits. It says who the work is for, what to do, which material to use, how the answer should look and what to avoid. Then you check the answer and ask a follow-up.
7 min readBe first on the app
Leave your email and we will tell you the day Datamew lands on your phone. One email at launch, no spam.
- Coming soon onApp Store
- Coming soon onGoogle Play
- Use it now onthe web