Growth Hacking with AI
Fast business growth requires the ability to identify growth opportunities, form hypotheses and test them quickly against measurable results. Growth Hacking with AI combines growth hacking methodology with generative AI to compress the research, ideation, content-production and analysis cycle from weeks to hours. Working in a team with a real client or startup, you will learn to design AI-supported growth experiments that contribute to better-informed business and marketing decisions.
Practical info
Course Date
Capacity
3 ECTS (78 academic hours, of which 16 in classroom and 62 individual work)
Lecturers
Language
English
Method
Blended
Location
EBS University, A.Lauteri 3, Tallinn
Price
From idea to measurable growth experiment
The course provides a systematic framework for turning growth objectives into concrete, measurable experiments. You will learn to analyse a company’s growth funnel using the AAARRR model, select strategies suited to the business context, and use AI tools to accelerate analysis and execution. Each experiment is connected to an explicit hypothesis, a single variable, a success threshold, a validation window and relevant metrics. Hands-on work with a real client or startup allows you to apply the methodology directly in a real business context.
Who is Growth Hacking with AI intended for?
The course is particularly relevant for learners and professionals working in marketing, business development, sales, growth, product management and entrepreneurship who want to use AI more systematically to support business growth. The course is delivered at bachelor level. No formal prerequisites or previous experience in growth hacking or AI tools are specified in the programme.
Explore the course
Sessions 1–4 are delivered in class and Session 5 is delivered online.
The course is deliberately hands-on: theory is delivered in short blocks, while the majority of learning activities centre on a team-based growth sprint for a real client or startup. Team activities are organised and tracked on a shared Trello board from the first session, making progress visible throughout the course.
The specific AI techniques and prompt patterns used in Sessions 2–4 will be finalised closer to the course dates to reflect the state of available tools. Genspark, Google AI Studio, the AAARRR framework and the core growth metrics remain fixed elements of the methodology.
Topics Covered
Why is it important?
Growth hacking differs from traditional marketing through its systematic, measurable and rapid approach to experimentation. The AAARRR framework provides a structured view of the company’s growth funnel and connects its stages with relevant performance indicators.
What will happen?
The session introduces the growth hacker mindset, lean experimentation and the AAARRR framework. Teams are formed, a Trello growth sprint board is set up, and a real client or startup is selected as the course application case.
Why is it important?
Generative AI can significantly accelerate market and competitor research, information structuring and the analysis of growth opportunities. At the same time, it is important to verify sources and critically assess AI-generated outputs.
What will happen?
Participants explore Genspark and Google AI Studio and use AI to support competitor analysis and mapping of the client’s AAARRR growth funnel.
Why is it important?
Rapid experimentation creates value when the selected growth strategy fits the company’s objectives, constraints and stage of development. A well-designed experiment helps assess the impact of a single variable and inform the next decision.
What will happen?
The session covers different growth strategies and the structure of growth experiments. Teams select three strategies and plan their application, while the specific AI techniques will be finalised closer to the session date.
Why is it important?
The right metrics help distinguish activity from actual growth and assess whether an experiment supports the intended business objective. Systematic tracking provides a stronger basis for future growth decisions.
What will happen?
The session covers key growth metrics, tracking dashboards and the North Star metric. Teams connect their selected strategies with relevant metrics and forecasts.
Why is it important?
The value of a growth strategy also lies in the ability to justify decisions and connect actions with measurable outcomes. Structured feedback helps evaluate the work and identify next steps.
What will happen?
In the final online session, teams present their growth strategies, use of AI tools, metrics and forecasts. The session also includes Q&A, feedback and peer assessment.
Entry requirements
- Higher secondary education degree or an equivalent qualification;
- Sufficient proficiency in English (B2)
- Valid temporary residence permit or EU citizenship.
Learning outcomes
Upon completion of the course the student is able to:
1. Explain the principles of growth hacking and how the growth hacker mindset differs from traditional marketing.
2. Map a company's funnel using the AAARRR framework (Awareness, Acquisition, Activation, Retention, Referral, Revenue) and identify its friction points.
3. Use AI agents and multimodal AI tools (Genspark, Google AI Studio) to conduct market and competitor research, generate creative assets, and produce experiment artefacts.
4. Select and justify growth strategies appropriate to a client's objectives, constraints and stage.
5. Design growth experiments with an explicit hypothesis, a single variable, a success threshold and a validation window.
6. Assign the correct metrics to each experiment and build a tracking dashboard (conversion rates, k-factor, CAC/LTV, D1/D7/D30 retention, ARPU, DAU/MAU).
7. Define a North Star metric and set defensible numerical forecasts for each strategy.
8. Work as a growth team using a Kanban workflow, and critically assess the limits, biases and reliability of AI-generated outputs.
Course Completion and Assessment Criteria
Attendance is monitored and strictly required, as most exercises take place during the sessions. Participation and preparation are assessed continuously throughout the course, and assessed assignments are documented in Trello.
The final grade consists of two equally weighted components:
- Final Presentation – 50%, group grade.
- Continuous Assessment – 50%, individual grade.
Students also evaluate the contribution of their team members to support fairness in assessing individual participation.
Learning Enviroment
The courses takes place at EBS’s modern campus in Tallinn, Lauteri 3. Students have access to ergonomic classrooms, the EBS library, and the cloud-based Canvas learning platform. The study process is supported by online tools such as Canvas and MS Teams. Free Wi-Fi is available throughout the building.
The University reserves the right to make adjustments to the programme in cooperation with the lead lecturer to ensure the best possible learning experience.
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