A Thinking System for Market Research

In my workshops, Zero to Crore and the Business Planning Bootcamp, I insisted to carry out a marketing research activity to help founders find their brand /product voice and positioning.

Do the research before you write the marketing.

Everyone agrees with this rule. In theory.

In practice, people want to skip it.

They want to design the logo. Write the landing page. Run the ads. Post on social media. All before they fully understand their market.

That rarely ends well.

In the workshops, we slow things down.

We start with structured marketing discovery exercises. Not slogans. Not taglines.

Participants work through a series of templates. Each template forces them to answer uncomfortable but necessary questions.

• Who is the real customer?
• What problems do they care about?
• What do competitors promise?
• What has the market already heard a hundred times?
• Where does a new product actually stand out?

Check it out: https://github.com/ishwarjha/claude-marketing-research-skill

By the time participants finish the exercise, something interesting happens.

Their thinking becomes clearer.

Often the business idea itself changes.

And, I could see the sense of accomplishment and smile on their face.

The process work, but felt like it is exhausting.

Even with the templates and facilitation, the work took time. Participants must read competitor sites. Compare messaging. Think about customer psychology. Interpret patterns. Then connect everything into a clear positioning statement.

That is a lot of thinking for a workshop.

Some participants enjoy it. They lean into the analysis.

Others look at the templates the way people look at tax forms.

The methodology was always correct.

But applying it manually required patience.

I always thought about finding other ways to make it less time consuming and more structured.

When Generative AI started catching up, I tried a few times to do it with help of using right prompt. It worked, but output wasn't any close to satisfactory.

Then, Claude's ability to add custom skills caught my attention. That led to the Claude Market Research Skill.

Instead of manual work or going through tedious prompting to perform every research step, Marketing Research Claude Skill can now guide an AI system through the same methodology.

It begins with a few simple questions.

• What is the product?
• What are its main features?
• Who is the ideal customer?
• Who are the competitors?
• What stage is the business in?

Those answers create the context for the research.

Once the system has that context, it runs through the same framework we use in the workshops.

It studies competitors. It analyzes the product. It builds a profile of the customer. It examines the state of the market. Then it develops value propositions based on the insights.

The structure stays organized and guides through everything needed to complete the marketing research, including iterations.

The biggest improvement is not speed. It is consistency.

When people do research manually, the quality varies.

Some skip competitor analysis. Some misunderstand the customer. Others jump to conclusions before the evidence shows up.

The system does not get impatient.

It applies the research steps in order. Every time.

Which leaves more time for the part that actually matters.

Thinking.

The Claude Market Research Skill keeps the thinking framework intact.

It simply removes the mechanical work.

Which means founders can reach clarity faster.

And perhaps avoid writing three landing pages before discovering who their customer actually is.

That alone makes the exercise worthwhile.

If you want to try the system yourself, you can download it here:

https://github.com/ishwarjha/claude-marketing-research-skill

Use it, experiment with it, and adapt it to your own research process. The frameworks remain the same. The difference is that now the work moves much faster.