🦾Eric Nowoslawski

I am a direct response outbound lead generation expert. And by that jumble of words, I mean that I leverage cold email to build predictable revenue pipelines for my clients. 

I leverage over 20 databases to merge Firmographic, Technographic, and Persona data to build highly targeted playbooks with my clients. 

I believe we need to arm sales teams with the knowledge of their total Target Addressable Market and teach them how to score that Market for which companies have the most pain and need their solution. 

The best way to do this is to look at public indicators such as open jobs data, employee growth/attrition, social media growth, web traffic, new product launches, employee sentiment, individual employee tech investment, company tech stacks, etc.

With this data, not only are you only messaging with people that you know have a problem that you can solve, you also are armed  with powerful messaging that cuts through the noise. 

I teach sales teams to embrace technology and multiply what is possible per employee.

Founder

2 years of effort went into the Prospeo.io Company/Contact API and this is why it was WELL worth the wait.

2 years ago Jon asked me, "If there were a database that could do anything you want, what would you wish it would do?"

I had a laundry list of ideas from

- Data accuracy and transperancy
- Organization tools for the team
- API capabilities

And then, I didn't hear from them for a little while. We kept using their email finding tool in all our Clay tables as a happy customer of course but I thought they were just focusing on that.

Then Hugo reaches out to me and says, "Hey, we finished the database the way you wanted. Want to have a look?"

I sign in to Prospeo V2 and my mouth is on the floor of everything they built. Good things definitely take time and they crushed it on this one.

I go over my favorite parts in the video down below but here are my favorite features you should check out if you don't watch the video and go straight to the site.

- Data quantity - I did comparisons of searches against Sales Navigator and was extemely happy with the counts that come back for the same filters on people and company searches in sales nav vs. prospeo

- Data quality - Every profile I checked worked at the company Prospeo says that they work at. I tried to be sneaky and check a friend that I know changed jobs a week ago and they already had that in their database.

- Email quality - All emails are SMTP verified with bounceban on top of that.
The API is so great. I just spent the christmas break making a company database we are going to scrap and just use their's.

- When you enrich a person, you get the company data with the API response so you don't have to worry about double spending on companies!

- The platform is so fast to make searches in.

- Your team can visually make searches and then click a button to get all of the JSON of that search to quickly get that search with their API.

I think they are just starting to launch it and I would highly recommend checking it out to help with your company and contact finding workflows. 

We are starting to switch a lot of TAM links internally over to them so we can stop downloading and uploading so many CSVs!

Not paid to post this or anything. 

Just found it last week and thought they did a really great job and other people would like to see it!

Check it out here! 

https://lnkd.in/dJw9eAEy

Founder Growth Engine X | Clay Enterprise Partner

Tomorrow, join me and many other outbound minds to discuss the state of outbound in 2026. (of course focused on cold email because I'm not qualified to talk about anything else). 

We’ll cover the dreaded Gmail AI filter tweet that hasn’t even been rolled out yet that everyone is asking about. 

Deliverability trends we are seeing from sending 7M emails per month on behalf of our customers

The way data is getting more accurate and cheaper and combining this with AI can cheaply laser target your ICP. 

I’ll leave the link to register in the comments. Hope to see you there! 

Vaibhav Namburi
Harris Kenny
Nick Abraham
Wesley Hoang 🛠️♠️
Alex Fine🌲
Christian Oland
Matthew Lucero
Enzo Carasso 🧲

I built a way to monitor your customer's LinkedIn content with a RapidAPI endpoint and Cursor so you can reach out to your ICP and name drop a customer they have heard of. Here's the step by step on how to do it.

I think one of the best ways that we can reach out to an ICP is if they already know of one of our successful case studies. 

You could ask your customer for a referral, but that puts work on them. 

You can monitor who they already know and reach out as if it's a regular message, and the prospect will actually have heard of the social proof you're mentioning. 

To set this up, all I did was give a voice note while walking my dog and Cursor took care of the rest. 

I hope you can even copy and paste this post and give some more context and set it up yourself. 

Step 1

Get the Rapid API endpoint. If you comment "monitor", I'll send it to you. Sorry to play this game but LinkedIn hates external links. 

Step 2

Use the MCP in RapidAPI and connect that to Cursor

Step 3

Explain what you want it to do. 

"Hey Cursor, I want to use this endpoint to build a micro app that I can enter a comma separated list of linkedin companies. I want you to 

1) find all of the posts of the linkedin companies
2) Find all of the people that work at the company and find their posts
3) Pull all of the people that have liked and commented on the posts and filter for XYZ titles and company size. 

Step 4

Add a little bit more to the prompt above about how you exactly want this to work.

Step 5

Enter Plan mode in Cursor. Drop your prompts and watch the plan

Step 6 

Edit/Approve the plan. I was lucky that Gemini Flash got this done in one shot, so I'm hoping I can pass this on and help others use it too. 

Again, comment "monitor" and I'll send it to you but if you don't want to wait for me, searching rapidapi(.)com(user)apibuilderz should help those that want to search on their own!

This workflow I made with Cursor and hosted on Railway saves me 6 hours a week on email deliverability tasks and our customers get much more consistent results from it. 

Over the last 6 months, we really systematized our email deliverability infrastructure. 

No more guessing and then ordering domains that we thought felt right. I built an SOP for everyone that I can give away at the end of the post. 

We would miss customers. Over order for some, under order for others. It was crazy. 

So we got extremely scientific about it. 

We keep all domains marked as status, Active, Insurance, or Cancel in Supabase. 

We always want to keep AT LEAST 50% of our Active daily sending volume in Insurance so that we can always rotate our domains. 

Every Friday, I would use a python script that would get the reply rates of all the domains in our campaigns so I could make decisions of what should be cancelled and what should be rotated from Insurance to Active. 

Once I had the numbers, spreadsheet warfare would begin. 

Making sure that every customer had enough and we didn't cancel too many domains. Numbers wouldn't look right so I'd check them manually. It was a mess.

Now, every Friday, I run this little Preview Global Rebatch and it send me a slack message with every customer, their daily send goal, how many domains are active, how many domains do we suggest to cancel, how many domains I need to buy more of, etc. 

And I hit accept and not only does it change all the statuses in our Supabase, it also pulls all of our customer's campaigns and swaps out the old domains for new domains. 

Easily my favorite workflow for deliverability. 

If you want our email deliverability SOP that goes over how we do this and how we work with Hypertide.io and Zapmail.ai to get it done, comment "primary" and I'll comment it back to you!

Here's the prompt to get you started building your own google maps scraper with Claude code or Cursor. 

One of my favorite things about LLMs and coding is that my team can build things that impact our business and then everyone can use. Bharatt Arorah built this google maps scraper for us and it's been so easy to use. 

Then when someone else on the team wants to add to it, it'd be really easy for them. 

This scraper is built on a RapidAPI endpoint that gives us 3,000,000 requests per month for $100 a month. 

Here's the prompt I'd give for Cursor or Claude Code to figure this out for you. 

First connect to the Rapid API MCP and then run this because it'll ask you to restart. (I don't use the MCP to actually run the code. I just use it to connect to the documentation to help set everything up). 

If you need the list of zip codes don't ask me or your mother for it. Ask Chat GPT literally asking "Do you know of any GitHub repositories that have all of the zip codes in the United States, or any other public ways that you can download that information easily?" and it'll come up, I promise. 

Long Text not optimized for a linkedin post AT ALL. 

Hey cursor, can you explore this Google Maps endpoint and build a plan for me that would be able to create an input where I can say a Google category, and then you'd be able to scrape it?

Here is a file of all the zip codes around the United States so that you have something to parse by. Search every one of these zip codes with my keyword to then find the companies that are in those areas. Build something into it that includes logic that, if a company is in a different business category that is excluded from my results, I want to be able to filter for the category. Let me know if we could exclude the cities and also run multiple category searches in one run. Set up the database schema to pull the zip codes from SupaBase. Literally go one by one doing a search across each of the zip codes. I also might wanna specify that I want to include certain cities, exclude certain cities, or include and exclude states in the future as well. Let's also add the filters for that to be possible as well. 

Hope that helps and provides a good lead gen project for people trying to get into coding with Cursor or Claude code.

Send those companies over to a Clay webhook to have a contact finding waterfall and you're all set!

I have to admit, six months ago I didn't get the point of MCPs.         
                                         
This post is for people who were like me. Also for my employees who are reluctant to start using these tools.                     
                                         
What is an MCP (Model Context Protocol)?                    
                                         
Think of it as a gateway for an AI agent to understand a tool.         
                                         
Instead of asking an agent to read API documentation (it will miss things),  
you connect it to an MCP. The agent figures out:                
 - What endpoints exist                             
 - What payloads to send                            
 - How to actually accomplish your task                     
                                         
Then you ask it to write the TypeScript or Python to make those API calls   
directly.                                   
                                         
Way more efficient. Way fewer tokens.                     
                                         
 My biggest tip:                                
                                         
 We're not actually doing a lot of work with MCPs as in moving data or doing work with MCP.             
                                         
We use them so agents understand the API documentation better.         
                                         
The MCP helps the agent learn the tool. Then we have Claude write actual code that calls the APIs.                                
                                         
That's the workflow:   
                           
 1. Connect MCP                                 
 2. Agent learns the tool                            
 3. Agent writes the automation code                      
 4. You run the code directly                          
                                        
 If you've been confused about MCPs, hopefully this helps.

A couple of customers have asked me what I think about this announcement from Google and here's my humble prediction. 

I'm not going to be naive and say that this won't have any affect on cold email. But also, even the video doesn't explain very well what this will do. 

I think that there is a best case scenario and a worst case scenario. 

Best case - this is an overall summarization of the email meaning that the preview text we optimize our first lines for today won't be as important as optimizing for how the summary will come across. 

A recipient can see the offer (maybe even stated cleaner than what an average copywriter can do) and choose to open or disregard. 

Worst case - it becomes a new spam filter and labels all external emails you haven't received before as spam with no preview. 

I truly think the actual outcome will be somewhere in the middle and lead magnets will become more and more important so you aren't just pitching calls and getting hung up in the spam filters. 

Truly, no one knows but it's not in my inbox yet but excited to see it when it is so we can start playing with it and see how it affects the channel.

Jed Mahrle

Practical Prospecting has helped 50+ B2B tech companies create custom outbound systems that consistently book meetings.

Visit our website to learn more: practicalprospecting.io

Not ready?

Join 30,000+ readers of The Practical Prospecting Newsletter: content.practicalprospecting.io
Join the waitlist for my course + community: practicalprospecting.io/vip/

Practical Prospecting is a done-for-you lead generation agency. We've helped dozens of B2B startups book meetings by creating repeatable outbound systems.

Our process has 3 steps:

(1) Email Infrastructure
(2) Precision Targeting 
(3) Practical Messaging 

To learn more, visit our website & book a free strategy call: practicalprospecting.io

After our call, you'll receive 1 unique outbound campaign idea for your B2B company (including relevant triggers, offer ideas & sample messaging)

Not ready to work with us? 

Join 22,000+ readers of The Practical Prospecting Newsletter for actionable tips and strategies: Jed.substack.com

ZoomInfo quietly dropped an insanely useful feature for list building: Company Attributes.

It includes niche data like:

- Fleet size (trucks + drivers) if you sell into transportation or fleet-heavy industries
- Recruiting team size (recruiter headcount) if you sell to Talent/People teams
- Insurance + benefits details if you sell HR software or services
- Healthcare facility info (facility type, hospital type, bed count) if you sell into healthcare
- Banking + finance attributes (bank type, assets, etc.) if you sell into financial services
- Company footprint (number of locations + countries operated in) for geo-based targeting
- Public rankings + media mentions for better personalization

Normally, you'd have to use AI prompts to research this info. But ZI has it all readily available and easy to filter. 

In this video, I share how you can use it in < 2-minutes

#zoominfopartner #sales

Coming Soon: Practical Prospecting Pro (Join The Waitlist Below)

See what happens when you simply just share pricing?!?!?!

Here’s the framework I use to fix cold email messaging when reply rates are low. 

If deliverability + targeting are solid but replies are low, don’t randomly rewrite the whole email.

Instead, test variables in this order:

Tier 1 (what actually moves reply rates):
- Pain point
- Value prop
- Offer / CTA

Tier 2 (what builds trust and buys your email more time to be read):
- Opening hook
- Social proof
- Objection handle

Tier 3 (bonus variables to test for slight increase in conversion):
- Personalization
- Length (short vs long)
- Tone / style

In this video, I break it all down. Including common mistakes for each variable.

#sales

Sales tech has gotten so crazy that you can now track when your prospects leave their competitors.

Or even when they sign with a competitor.

l use this signal for clients who sell in HIGHLY competitive spaces where contract terms are 2-3+ years long.

In those industries, it's hard to do anything mid-contract. So knowing when they're coming up on renewal (or just dropped the competitor) is obviously a huge advantage.

In this vid, I shared how you can set this workflow up in < 2 minutes with ZoomInfo

#zoominfopartner #sales

Signal-based outbound is overrated. 

For most teams, it hurts results more than it helps. 

Especially early on.

Here are 4 reasons why:

Reason #1: Signals feel important to you, not them.

You end up anchoring your message to something they barely remember or don’t care about.

As a result, the signal can often be the reason why your message backfires. 

Reason #2: It becomes a crutch

Signals replace real relevance.

Instead of fixing segmentation, value props, and offers, teams rely on “I saw X” to carry the message.

Reason #3: It doesn’t scale

Only ~10–20% of your market shows real signals at any time. That’s not enough volume to build predictable pipeline.

Reason #4: It quietly overcomplicates outbound

15–30 micro-campaigns, tiny lead pools, constant tweaking...

Outbound stops being a system and turns into a science project.

Instead, focus on fewer and simpler segments. Then keep testing your value prop, problem statement, and offer until you find something that converts. 

THEN (and only then) add in signals to increase conversion rates. 

What do you think?

#sales

If you've ever sold in the IT Services/Consulting space then you know outbound ain't easy...

I recently worked with a couple of clients in the industry. 

Here are 3 plays we ran to get meetings:

(1) Targeting companies whose IT Leader just retired

This idea came to mind after we got an email reply saying "Perfect timing, our Head of IT just retired and we're looking for MSPs". 

So we created a search in Sales Nav targeting more companies with this trigger and saw solid results (comment if you want me to create a video of how to do this). 

(2) Targeting companies with a low employee headcount to IT headcount ratio

Companies with recent growth and lots of employees but not a lot of IT folks likely have a greater need for IT support. 

So those were the accounts we prioritized. We use Clay to figure out the IT team-to-employee headcount ratio (again, lmk if you want a video). 

(3) Offering an IT audit in our CTA

There are so many MSPs out there. And all of them are asking the same thing in their emails "Are you free for a call???"

The best way to stand out in this market (and any crowded market) is to offer something of value and BE PATIENT. 

So our CTA was an offer to review their current IT setup and infrastructure to make recommendations. 

This made it much easier to book a legitimate sales meeting because we had already earned their trust. 

What have you seen work well in this industry?

#sales

We just pulled a TAM of ~180,000 contacts for a client.

They wanted to run signal-based outbound to people who had just changed jobs.

Guess how many actually qualified?

Only ~4,000
 
That's 2.22% of the market

If you build your strategy around signals, you cap your pipeline before it even starts.

Prove your message works on a broad segment first.

Then layer in signals to improve conversion.

#sales

Shoutout to the Prospeo.io team for letting me beta test their V2.

I’ve been a longtime user, mostly using their API inside Clay for bulk email + phone enrichment. The data quality for the price has always been hard to beat.

V2 is a big step forward though. They’ve added a full searchable database, and I was honestly surprised by how granular the filters are.

You can search by intent, job changes, recent funding, open roles, tech stack, and more.

Wanted to share this because a lot of people don’t have the budget for big, expensive data tools, but still need clean data and strong filters to build targeted lists without blowing up costs.

And no, this isn’t sponsored 🙂

#sales

Went live with a new client yesterday, and 4 positive replies in the first hour!

Shoutout Luke Ruffing on putting this messaging together. 

This was a market we previously tried and failed at, but approached it with an entirely different angle this time. 

No signals, just a well-segmented list of contacts where we call out something very specific about their product via scraping their help docs with AI. 

Here's the opening sentence (of course, can't give away the full email):

"Hey {{first_name}}, I was looking at how {{company_name}} handles {{workflow}} inside the product and wanted to reach out. Looks like you're using {{solution}}?"

#sales

Outbound boils down to 3 things:

(1) Right time
(2) Right person
(3) Right message

All 3 are in your control. 

Let’s break it down:

#1 Right time

You’ll never know with 100% certainty when someone is in the “buying stage”

But you can make a pretty damn good guess. 

Start by looking at your current customers and inbound leads to determine what events led them to come inbound and/or buy. 

That’s where you’ll find relevant signals to reverse engineer into your outbound strategy. 

#2 Right person

If you sell into SMB this may be the easiest of the 3. However, the larger the company you sell to, or the more complex your product is, who to target isn’t always that clear. 

Again, look at your customer data and map out every relevant job title. Then group the similar ones and create sequences with relevant messaging for each. 

#3 Right message

More than anything, you need to know what these personas *actually* care about. 

You can’t guess this. Again… this needs to come from your customer data. 

But the simplest way to do it is to read your G2 Crowd reviews and pull out word-for-word the language your customers use there.

The best cold emails use FOMO. 

One thing ALL execs care about: “What am I not doing that my peers already figured out?”

Whether you’re selling something niche, new, or in a crowded space, you can’t just pitch the tool. 

You have to make prospects realize they’re missing something.

Talk about what your customers are doing differently and the results they're getting because of it. 

But don't frame it like this: 
- "Our customers are using our tool and getting X results"

Frame it this way: 
- “A few other marketing leaders in the SEO space are shifting budget into first-party content hubs, and they’re seeing a 20% lift in inbound pipeline because of it.”

That’s where outbound wins. 

Not by forcing your way onto their priority list. 

But by planting curiosity, FOMO, and that fear of falling behind.

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist → https://lnkd.in/g7E9dXpp

Here is the 5-phase method I use to create scalable cold email campaigns that consistently generate meetings. 

It all starts with knowing what phase you're in, and focusing on getting to the next one. 

Phase 1: Negative Replies With No Context

This is when almost all replies are just some variation of “No thanks”, “Unsubscribe”, “Not interested”. 

There’s no context to the negative reply that informs on what we should change. 

Phase 2: Negative Replies With Context

This is when almost all replies are still negative, but some of them are giving you context as to WHY they're not interested. 

For example, “I’m not the right person”, “We already have a solution in place for this.”

For every one person that tells you “We already have a solution”, assume 100 other people who received that email thought it, but just never replied to tell us. 

Use this data to inform how you change messaging and targeting. 

Phase 3: Inconsistent Positive Replies

This is when we’re getting some positive replies, but they’re under ~10%. 

In this phase, dig into the commonalities of who responded positively. 

What was their job title?
What type of company?
What specific email did they respond to?

Use this data to inform how you change messaging and targeting. 

Phase 4: Consistent Positive Replies

This is when we’re consistently driving ~10%+ positive reply rates. Specifically, for a campaign where there’s a large TAM. 

Say, for example, we launched one campaign for the “new to role” signal that gets 10%+ positive reply rates. That doesn’t mean we’ve reached phase 4 yet. Because there may not be enough leads in that TAM to scale to the volume needed to consistently generate meetings. 

This is why it’s so important to focus on cold outbound before signal-based campaigns. 
 
Phase 5: Consistent Meetings

This is the final phase. We reach this phase when we’ve worked on our follow-up strategy and speed to lead, to the point where we're consistently converting positive replies into meetings (ideally at a 25%-50% rate)

Note: Sometimes you can run a campaign with a great offer that gets a ton of positive replies. But if that offer can’t get converted to a meeting. In that case, you have to rework the offer until you reach this phase. 

Hope this helps! The vid goes into much more detail. 

#sales

The real goal of outbound isn’t better personalization.

It’s finding the fewest possible segments where the same message still converts.

Most teams get this backward.

They over-segment:
- Tech stack
- Niche
- Company size
- Hiring status
- Platform usage

And end up with:
- Hundreds of leads per campaign
- No statistical confidence
- No idea what actually works

Fewer segments = more data = clearer decisions.

#sales

There are three methods for running cold email campaigns:

Method #1: Fully AI-written emails
→ Every prospect gets a completely custom email written by AI.

Method #2: Templated emails with AI personalization
→ The core template stays the same, but AI fills in specific tokens to add context for each prospect.

Method #3: Fully templated emails
→ Everyone receives the exact same email.

Here’s how I think about which one to use.

I always start with Method #3.

I want to test the bare bones of the message and eliminate variables. As soon as you introduce AI personalization, it becomes hard to tell what’s actually working: your value prop, or the personalization itself.

In round one, I’m only testing:

- The problem statement
- The value prop
- The CTA

I keep iterating until I see:
- 1%+ reply rates
- 10%+ positive reply rates

I'm really just looking for signs of life.

Once I have that, I move to Method #2 and start layering in AI-driven context to make the email feel more 1:1.

At this stage, I want a noticeable lift:
→ 2%+ reply rates
→ 20%+ positive reply rates

Usually stop there.

Fully AI-written emails have so many variables that it's hard to do right at scale. 

I would not recommend this until you already know what’s working and your prompt has extremely tight guardrails.

That said, I’ll be sharing the exact prompts I use for fully AI-written emails in an upcoming newsletter (link in profile).

Which method do you use most right now?

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist → https://lnkd.in/g7E9dXpp

#sales

Here’s how we pull contact info for blue-collar and small businesses.

All you need is a list of company websites.

From there:

We run a prompt in Clay to double-check ICP fit.

If it passes, we run a second prompt to research the company and site to find the owner’s name and email.

If we only get the name (no email), we use tools like LeadMagic, Prospeo, IcyPeas, FindyMail, etc. 

All you need is a full name + domain to find an accurate work email.

The hit rate is high because small businesses usually have this info somewhere on their site.

Doing it manually is a pain in the ass.

So we let AI do it for pennies instead.

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist → https://lnkd.in/g7E9dXpp

#sales

Here's a simple approach I use for segmenting accounts:

I use three buckets:
 → Actively Growing
 → Signs of Growth
 → Stagnant/Declining 

This helps me narrow in on WHO to reach out to first and WHAT angle I should take with my message.

Actively Growing → lead with hiring, expansion, urgency
Signs of Growth → lead with timing, curiosity, “worth a look”
Stagnant/Declining → lead with risk, inefficiency, or status quo cost

I built a simple ChatGPT prompt that takes a company list and returns a clean, segmented list for you. 

Here's the prompt:

You are a careful company researcher. Your job is to classify each company into one category using only verifiable, recent evidence.

Buckets (choose exactly one)
- Actively Growing
- Signs of Growth
- Stagnant / Declining

How to evaluate each company

1) Start with Actively Growing (check first)

Review:
The company’s Careers page or official ATS (Greenhouse, Lever, Workday, Ashby, JazzHR, iCIMS)
The company’s official LinkedIn “Jobs” tab (no third-party reposts)

Rules:
Only count roles in: {{Insert your ICP}}
Only include roles posted or updated in the last 120 days
To qualify as Actively Growing, at least ONE must be true:
- 3+ relevant open roles
- Roles across 2+ relevant departments
- Roles across 2+ locations
- An official hiring announcement in the last 90 days

If this is met → stop and label “Actively Growing.”

2) If not Actively Growing, check Signs of Growth

Look for dated announcements from the company or reputable media:
- Funding round (2025+)
- VP / C-level hire (last 180 days)
- M&A activity (2025+)
- New office, product launch, or major partnership (last 180 days)

If at least one strong signal exists → label “Signs of Growth.”

3) If neither applies

→ label “Stagnant / Declining.”

When evidence is weak or mixed, always choose the more conservative bucket.

Output format (IMPORTANT)

Return results as a table, one row per company, with these columns:
- Company
- Bucket (Actively Growing / Signs of Growth / Stagnant / Declining)
- Reason (1–2 plain-English sentences)
- Hiring Evidence (role count, departments, most recent post date)
- Growth Signals (if any)
- Source URLs
- Confidence (0–100)

Rules
- Use only sources with visible dates
- Do not guess or infer
- No filler text outside the table

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist → https://lnkd.in/g7E9dXpp

#sales

Open article: Coming Soon: Precision Prospecting PRO by practicalprospecting.io

A good friend of mine is looking for an entry-level marketing role.

Titles she’s open to: Marketing Coordinator, Marketing Specialist, Marketing Associate, Apprentice, or Paid Intern.

She’s less focused on pay and more focused on learning directly from someone strong in marketing and getting real, hands-on experience.

She has a few years of part-time experience running ad campaigns, managing social media, and helping execute events.

Based in Tampa, but open to remote opportunities as well.

If you know of any open roles or would be open to an intro, please drop a comment or DM me. 

Appreciate any help!!!

#hiring #marketing

Your outbound sequences should tell a story. 

Each email needs to build on the last. 

Here's an example of what I mean (based on what I do):

Email #1:

Hey {{first-name}} - [mention the buying trigger we found].

[Make a hypothesis about a problem they’re experiencing because of that trigger].

If it sounds relevant, I think I found a way we can help with this.

Mind if I share more info?
___

The key to this first email is being intentionally vague about how we solve the problem. 

First, we “show them we know them” in the first line. 

Then, we nail the problem they’re likely experiencing in the second line.

Finally, in the third line/CTA, we create curiosity with the goal of getting them to respond to find out how we solve this problem.

Email #2: same thread

For more context, {{first-name}} - it involves [your solution for solving the problem].

Here’s a visual to explain how it works:

[Insert a screenshot of what your product does to solve this problem]

Think this could help?
___

In the second email, we're explaining how we solve the problem with a visual. This gives the sequence synergy and flow.

Email #3: same thread

{{first-name}} - If [problem] is top of mind given [buying trigger], I thought this could help: [insert helpful resource].

Happy to share more resources on this if you’d like.
___

In the third email, we share a helpful resource with no CTA. The goal is to help them solve part of the problem for free with a helpful resource.

Ideally, this resource comes from a 3rd party (i.e. not from our company so that we don’t come off as biased).

By giving first, we build trust so that hopefully, they’ll come back to learn how we can help them solve the whole problem.

One week later we repeat this thread in a new email chain - but we focus on a new problem.

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist →

This is the #1 reason good cold emails still get ignored.

And the fix is pretty simple.

Have you ever had a situation where you KNOW your deliverability is good and you KNOW you're reaching out to the right people... yet, you still aren't booking meetings???

Usually, it's because there’s a “hidden objection”

The hidden objection is what your buyer thinks when they open your email, read it, and process what you said, yet still decide not to respond.

So how do you find the hidden objection(s)?

I use this ChatGPT prompt every time. 

And it works like GOLD. 

Here it is...

I work for {{company}}. We do {{insert very specific explanation of what you do}}. I'm writing a cold email campaign to {{persona}} and need your help. 

I know my emails are landing in their inboxes, and they're reading them. Yet, they're still not responding. So I need you to act as if you're in the mind of a {{persona}} receiving this email: {{insert email}}.

If you were truly a {{persona}}, and you received this cold email, what are all the reasons you wouldn't respond? 

Tell me what makes you skeptical, what makes you confused, and what factors are at play that I'm not seeing that would make you not want to take action and book a meeting with me. 

This feedback will help me know what I need to do to improve my cold emails and get more replies.

_____

Once you've identified the hidden objection(s), simply address them upfront in your emails.

You may have to A/B test different ways of how you address it but keep testing until you find something that works. 

P.S. I’m opening a private community where I share behind-the-scenes of real outbound campaigns + the exact GPTs, prompts, and templates we use daily.

Join the waitlist →

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🦾Eric Nowoslawski

Jed Mahrle

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taplio

The Battle

🦾Eric Nowoslawski

Jed Mahrle

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}🦾Eric Nowoslawski's LinkedIn Performance

Performance ScoreJed Mahrle's LinkedIn Performance

Ready to grow your LinkedIn presence?

Performance Score🦾Eric Nowoslawski's LinkedIn Performance