Hi {{ first_name | there }},
Recently, Iâve been heads down in Claude Code. I wanted to share a practical workflow you could implement in your business today.
Letâs dive in!
Today, in 10 minutes or less, youâll learn:
đ Why drowning in client feedback is actually a goldmine waiting to be unlocked
âĄď¸ Why Claude Code beats regular Claude Projects for serious customer development
âąď¸ How a non-technical person can build a client research workflow in 15 minutes

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đĄ How I built a client research analyst in 15 minutes (using Claude Code)
Youâve gotten your first clients. Youâre finally scaling up.
But now youâre drowning in service delivery. Overwhelmed.
You absolutely donât have time for customer research, when you barely had time to do your own laundry yesterday.

However, you just know your 14 recent client calls must contain nuggets of insight that can help level up your service quality or grow your business faster.
So how do you unlock these insights without overburdening yourself?
Previously, I showed you how to use AI prompts for customer research.
An obvious solution: Dumping your client meeting notes into a Claude Project, then running an effective prompt over them. I still do this a lot. Itâs fantastic.
But sometimes itâs not enough.
In these cases, I bring out the heavy artillery - Claude Code.
While it looks intimidating at first, Iâve found it extremely powerful even as a non-technical person.
Today, Iâm going to show you how I leverage Claude Code to accelerate my client research workflow in 15 minutes.
1/ Why Claude Code?
I still use Claude Projects a lot, but have run into several pains:
Too much copy-pasting between Claude + docs
Repetitively uploading files into projects
Difficult to move context across chats
Losing track of my prompts
Inability to update docs
Not to mention - that feeling of horror when I see my Claude Desktop app freezing yet again.

Claude Code emerged onto the scene this spring.
At first I was skeptical. But then I tried it after hearing so much hoopla about it - and was blown away. Using it was the first time I felt a visceral âagentic AIâ moment.
Now Iâm leveraging the tool not only for coding, but also business workflows.
Hopefully this client research walkthrough can show you how Claude Code can help you too.
2/ How to setup Claude Code as a non-technical user
First things first. To get Claude Code running, I whipped up the olâ Terminal:

If youâre not a dev, donât be scared of Terminal. Youâll get used to it.
Next, I downloaded Claude Code by entering this command into terminal (Anthropicâs full instructions). Here it is for Mac:
curl -fsSL claude.ai/install.sh | bashAnd for Windows:
irm https://claude.ai/install.ps1 | iexThen, I created a âcustomer_researchâ folder in my Finder and navigated to it using the command âcd customer_researchâ (quick instructions).
Once I was there, I typed âclaudeâ in the terminal to open Claude Code:

Boom. Youâre in.
Now for the exciting part - building your own analyst.
3/ Building a client research analyst
Now that weâre in Claude Code, Iâm going to show you how I setup my research analyst.
I created a sub-folder meeting_notes and uploaded all my meeting notes, transcripts, and documents as markdown files.
⥠For advanced users: To speed this up, I connected Claude Code to Notion MCP, then prompted it to export my Notion customer meeting notes into this meeting_notes folder.
Afterward, to avoid having to copy-paste prompts, I created a Claude Slash Command. To do this, I created two prompt files in the folder .claude/commands:
topic_analysis.md: Analyzing customer feedback and bucketing them into 4 topics: pain points, blockers, customer requests, and solution feedback.
insight_generation.md: taking the output and grouping similar snippets into common insights with actionable recommendations.

This basically saved my prompts as markdown files in a folder, which is pretty convenient. No more losing track!
Next, I prompted Claude Code to run the topic analysis and save the output in a markdown file called topic_analysis_output.md

Then, I fed this output into the insight generation prompt to created the final synthesized insights.
Voila! I got a research summary of client insights, supporting quotes, actionable recommendations grouped by the topic.

The actual research output was a great starting point:

Iâve been impressed by how Claude Code manages context more smoothly than Claude Projects, producing higher-quality outputs IMO.
In particular, these insights helped me answer questions like:
What are the common pain points, requests, and feedback?
What are the actual quotes clients have said related to this insight?
What actions should I take in response to this feedback?
Separately, Iâve also built a web dashboard to visualize this data with charts and a structured UI. (Not covering this today, but so much easier to create than before with Claude Code.)

4/ Wrapping up
From here onwards, I can see tons of possibilities.
I can use this research output to do things like:
Craft ideal client profile descriptions
Create a dashboard UI (like above)
Generate sales landing page copy
Build the actual landing page
Create a discovery call script
Write sales emails copy
All within Claude Code. And thatâs just the tip of the iceberg.
So would I recommend Claude Code?
It might seem intimidating as a non-dev, but Iâd recommend trying it out if youâre feeling inspired and not afraid to get your hands dirty.
And if you do, building your own customer research analyst could be the perfect weekend project. Let me know how it goes.

đ Last Weekâs Gems
𤯠Shorting the AI jobs apocalypse (David Deming)
đ§ On the Reverse Flynn Effect (Cal Newport)
đľ How to Keep This Hot Stock Market From Melting Your Retirement Dreams (WSJ)


Dexter Zhuang
Say hi đ on LinkedIn or Substack Notes
đ Partner with Portfolio Path
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