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A Simple Tech Stack for Fractional Business Development (Without Being Creepy)

Written by Rob Smith | Mar 1, 2026 5:14:08 PM

People often ask about the tools I use for business development.

It’s an understandable question. There’s a lot of software out there promising to automate, optimize, and “10x” your pipeline.

My own approach is pretty simple, and it’s built on a few principles:

Use tools to save time on repetitive work

Use them to enrich your understanding of people you actually want to help

Don’t use them to pester or trick anyone

You can do everything I’m about to describe with a spreadsheet and manual effort. That’s how I started. Over time, I’ve layered in tools to make it more efficient.

Here’s what my current stack looks like.

The job I’m hiring my tools to do

Before I get into product names, it’s worth being clear on the job:

Find the right people (consistent with my ICP)

Connect with them in a low‑pressure way

Pull their basic info into a central place

Enrich that info so I understand their context

Segment intelligently for targeted outreach

Ask good questions of that data so I’m not guessing

No tool does all of that well. So I’ve assembled a chain.

Step 1: LinkedIn + Dripify – finding and connecting

I use LinkedIn primarily as a phonebook, not as a content platform.

My ideal contacts there are:

Presidents

General managers

CEOs

Founders of 5–50M manufacturing and B2B companies

To manage connection requests at scale, I use a tool called Dripify.

What I use it for:

Sending 40–50 connection requests per day

With a very simple, non‑salesy message:

“Hi, I’m another executive in the manufacturing space here in Minnesota. I’m expanding my network and would be glad to connect.”

What I do not use it for:

Automated follow‑up messages

Long, personalized‑sounding pitches

Scraping and spamming

Those capabilities exist in the tool, and they’re exactly where people slide into “creepy.”

My rule is simple:

Automation for the first, polite “hello.”

Human judgment after that.

Once someone accepts the request, I don’t keep messaging them on LinkedIn. My goal is to move the relationship to email if and when that makes sense.

Step 2: Zapier + HubSpot – capturing and organizing

When someone accepts my connection request on LinkedIn (via Dripify), I want to:

Capture their basic info

Store it somewhere structured

Avoid hand‑typing everything

So I use Zapier to:

Watch for new accepted connections in Dripify

Pull the available fields:

First name

Last name

Job title

Company

LinkedIn URL

Email (if visible in their profile)

Create or update a contact in HubSpot, which I use as my CRM

At this point, the record is still pretty bare:

“John Smith, CEO at ABC Manufacturing, joh[email], connected on [date]”

That’s fine. The important thing is that the data is now somewhere I control, not just floating around in LinkedIn.

Step 3: Clay – enriching context and signals

Next, I want to know more about:

The company

Their tech stack

Any obvious signals that they might be a strong fit

For that, I use a tool called Clay.

Clay can:

Take a list of companies and people (from HubSpot)

Pull in additional information from public sources:

Company size

Industry

Technologies in use (e‑commerce platforms, CRMs, etc.)

Recent news

Social activity

Push that enriched data back into HubSpot

For example, I might ask Clay to:

Identify which of my contacts:

Are manufacturers

Sell through distribution

Have an e‑commerce component

Are using certain platforms (say, Shopify or Salesforce)

Those filters let me say, “Out of 500 enriched contacts, which 80 are most directly relevant to this specific topic or problem?”

That’s the segment I used in the McKinsey email example.

Step 4: A large language model – asking better questions of the data

Once I have enriched data, I’ll often run it through a large language model (like OpenAI or Ella) to ask higher‑level questions, such as:

“Based on this info, does this contact likely fit my ideal customer profile?”

“What might their current digital challenges look like?”

“Are there signals here that suggest timing might be good or bad?”

The goal here is not to “predict” perfectly. It’s to:

Avoid obviously bad fits

Prioritize the most promising segments

Tailor my outreach language a bit based on their context

That intelligence gets stored back in HubSpot as custom fields or tags:

“ICP_fit: strong / moderate / weak”

“Has_ecommerce: yes/no”

“Sells_through_distribution: yes/no”

Now, when I look at my CRM, I can see:

Total contacts (say, 6,000)

Enriched and qualified for my ICP (say, 500)

Highly qualified segment for a specific topic (say, 80)

That’s much more useful than a big, undifferentiated list.

Step 5: Email – where real conversations happen

Once I’ve:

Connected with someone on LinkedIn

Captured them in HubSpot

Enriched their record via Clay and a model

Tagged them appropriately…

…I almost always try to move to email for any substantive outreach.

Why?

Most of my ideal buyers are not hanging out on LinkedIn all day

Email is where business conversations actually happen

It’s easier to send attachments, context, and thoughtful messages

It’s easier for them to forward things to their team

I can control cadence and content without worrying about algorithms

So a typical progression might be:

Connect on LinkedIn (simple message)

Capture and enrich their info in my CRM

Weeks or months later, send:

A one‑off personal email, or

A small‑batch “strategic interruption” email to a segment they’re part of

LinkedIn opened the door. Email is where the real conversation happens.

You can do all of this manually at first

If that stack sounds like a lot, it’s important to say: I didn’t start there.

When I began:

I found people manually on LinkedIn

I copy‑pasted their info into a spreadsheet

I did basic research in a browser

I sent 1:1 emails from my inbox

I made notes about who to follow up with and when

That’s enough to validate your ICP, your pitch, and your basic funnel math.

Only once I knew:

Who I was targeting

What I was offering

How many conversations I needed

…did I invest time and a bit of money in tools to scale the process.

You don’t want to automate confusion. Start simple. Then let tools support a process that’s already working.

The “don’t be creepy” rule

A lot of the tools I’ve mentioned, and others like them, can be used in ways that erode trust:

Long automated sequences that pretend to be personal

Aggressive scraping and messaging

Overly familiar outreach based on tiny bits of inferred info

I try to draw a hard line against that. A few personal rules:

No fake personalization.
If I’m going to comment on something specific about their company, I actually read it myself.

No high‑pressure automation.
I don’t set up “if they don’t reply in 3 days, send this,” and so on.

No pretending we have a relationship we don’t.
“We’re connected on LinkedIn” is factual. “We’ve been in touch for a while” is not, if all that’s happened is an automated connect.

Easy exits.
If someone isn’t interested, I respect that immediately. No badgering. No “just circling back.”

The whole point of this stack is to:

Spend more time with the right people

Spend less time on data entry and manual filtering

Have better, more informed conversations when they’re actually ready

Not to trick anyone into a meeting they don’t really want.

Keep the goal in mind

At the end of the day, as a fractional executive, your tech stack is there to serve a very human goal:

Find businesses you can genuinely help

Understand them well enough to be relevant

Engage at a pace and depth that matches their reality

Build a small portfolio of long‑term, high‑trust relationships

You don’t need bleeding‑edge tools or complex automations to do that.

You need:

A clear ICP

A specific problem you solve

A simple, repeatable outreach rhythm

And, if you choose, a few well‑chosen tools to make that easier

If you keep that frame, you’ll be much less tempted by “growth hacks,” and much more likely to build a practice you’re proud of.