AI in Marketing | Live Workshop | Oct. 21

From online conversations to marketing content using AI

AI in marketing is about much more than asking a chatbot to write captions.

In this live workshop, see how marketers can use AI and data together to understand what audiences are talking about, identify topics worth exploring, analyse sentiment and turn those insights into relevant content.

Through a practical marketing-intelligence workflow, participants will see how publicly available online conversations can move through a process of: DATA → TOPICS → SENTIMENT → INSIGHT → CONTENT

What will happen during the workshop?

We will demonstrate an end-to-end workflow built around online audience conversations.

1. Discover audience conversations

See how an internal data tool can collect posts from selected Reddit communities based on:

• chosen subreddits

• relevant keywords

• a defined time period

The objective is to move beyond assumptions about what audiences care about and begin with actual conversations taking place within relevant online communities.

2. Identify topics worth investigating

Once the data has been collected, participants will see how marketing teams can review signals such as:

• discussion topics

• post titles

• engagement

• comments

• upvotes

• recency

• community relevance

These signals can help narrow a large volume of conversations into a smaller set of topics for further investigation.

3. Analyse audience sentiment with NLP

The selected conversations can then be analysed using Natural Language Processing.

Participants will see how sentiment analysis can help explore whether conversations around a topic appear:

• positive

• negative

• mixed

• uncertain

• frustrated

• enthusiastic

This adds another layer to marketing research.

Knowing that people are discussing a topic is useful.

Understanding how they feel about it can be considerably more valuable.

4. Turn data into an audience insight

Data alone is not a marketing strategy.

The next stage is interpretation.

Participants will explore how marketers can move from:

“People are discussing this.”

to:

“This may tell us something important about what this audience needs, wants, worries about or finds interesting.”

This is where human judgement remains essential.

AI can help organise and analyse information, but marketers still need to decide what the information means and whether it is relevant.

5. Select a content opportunity

Not every popular topic deserves content.

We will explore how to evaluate potential topics based on factors such as audience relevance, engagement, sentiment, recency, usefulness and connection to the marketing objective.

6. Use AI to develop the content

Once a topic has been selected, participants will see how AI can assist with turning the underlying insight into potential marketing content.

This may include developing:

• social-media content

• article ideas

• campaign angles

• email concepts

• educational content

• audience-specific messaging

The emphasis will remain on using AI to support the marketer rather than replacing marketing judgement.

What You Will Learn

By the end of the session, participants should have a better understanding of:

Audience research with AI

How marketers can use online conversations as a source of audience intelligence.

Social listening

How discussions happening across online communities can reveal emerging questions, concerns and interests.

Data-led topic selection

Why content ideas do not always have to begin with brainstorming.

NLP sentiment analysis

How language can be analysed to understand broad patterns in audience sentiment.

AI-assisted content development

How an audience insight can be translated into a potential piece of marketing content.

Human judgement

Why AI-generated analysis and content still require interpretation, verification and editorial decision-making.

A Practical Example

Imagine a marketing team wants to understand what university students are saying about internships.

Instead of immediately asking AI:

“Give me ten posts about internships.”

the team could first:

1. identify relevant online communities;

2. collect recent discussions around internships;

3. examine which conversations receive engagement;

4. identify recurring topics;

5. analyse sentiment around those topics;

6. investigate what students appear confused or concerned about;

7. select a meaningful content opportunity;

8. use AI to help develop the content.

The result is content informed by audience evidence rather than content generated from a blank prompt.

Frequently asked questions

Ready to See AI Used on a Real Marketing Problem?

Don't just learn how to prompt AI.

Learn how marketers can use data, NLP and AI together to understand an audience and decide what to create.

Register for the AI in Marketing - Live Workshop.