Emilia Korczynska

Passionate about SaaS product growth, and both the pre-sign up and post-sign up marketing. Talk to me about improving your acquisition, activation and retention strategy. 


Head Of Marketing

Doing all it takes to get more Product People over the code barrier with our code-free Product Adoption, Marketing & Experimentation Platform:  
Designing, developing and implementing a marketing strategy that ensures higher visibility 
Leading our stellar content team 
Implementing and driving a paid ads strategy to diversify customer acquisition. 
Driving funnel growth
Implementing an email marketing strategy 
Identifing and testing new acquisition channels
Overseeing, training, and coaching team members

Warning to all companies running LinkedIn ads to large audiences: your match rates may be inflated ☠️ We saw a “>90%” match rate of one of our largest audiences pushed from Hubspot, only to discover the number of companies inside the audience was only about ~33% of the Hubspot list. To make it even worse - when I inspected the matched audience on Linkedin and compared it to the original Hubspot audience - there were some strange companies that were simply wrongly matched (we definitely weren’t planning on targeting South African Post office…) 

So from now on, a weekly exercise: 

🥇 Cross reference our target audience with the matched audience on LinkedIn in Claude Code (exporting the list of companies from Linkedin gives you only the Company name + LinkedIn URL, so we will be pushing the audience with all the params from ZenABM’s API to Claude directly) 

🥈 Build an exclusions audience from the badly matched companies 
Excluding them from all campaigns in ZenABM 

🥉 ALWAYS have the LinkedIn URL in the audience to improve the actual match rates 

LinkedIn never fails to surprise me 🤷‍♀️

VP of Marketing @Userpilot. Author @ Product Rantz.

What a scary time to be alive: at 9:44 pm, when I was heading out to the gym (I know, I know) I suddenly (gasp) remembered I promised to send the deck (about The Most Cost-Effective Ways to Reach Your Buyer Groups on LinkedIn) 
for an event I’m talking at by the end of the week. With 2 hours 16 minutes left till the end of the week, I’d normally drop everything and start (frantically) putting my power point together, but this time - which my jacket already on - I just dumped a few instructions (some of which were from voice notes) to Claude Code (asking it to analyse exported ad performance reports, compare TLAs to other ad formats in terms of eCPC, CPM and eCTR, and write up a report + best practices for writing effective TLAs based on the top & bottom 25%) and then instructed Cowork to access the output file when it’s ready and generate a presentation similar to the one I did below, on the topic, including (here I blabbered about a few slides I wanted.) 

I left it and went to the gym. 

40ish minutes later, the presentation was waiting for me in power point. The content was good, but a bit too wordy, and the design was horrible - so I uploaded it to Gamma and asked its AI to shorten & prettify it. 

It did. I still made some manual tweaks (which I probably wouldn’t have had to do had I spent more than 90 seconds prompting in the first place - but hey, I already had my jacket on…) but altogether - it let me do the previously impossible. 

I know this is a very unsophisticated use case and that all of you are cutting cancer with Claude Code here - but the original data analysis, creating tables, graphs etc for this presentation would have previously taken me the whole day. It would be “Sunday-ruined” kind of hostage situation for me. 

The whole point is that this is now possible for the unsophisticated user. Upside? More time for life…but obviously there’s also the downside: the forever-increasing productivity treadmill: shouldn’t I have instructed my army of agents to do three decks for me at that time? Or maybe that and this post? And a blog post and a report? But if I did - who would be reading all this? (other agents? 😬)

Unfotunately my most productive teammate's name is not Claude* 😶  In February, they:  prospected 17,000 accounts and 23,345 contacts, researched and analyzed intent signals from the CRM, websites, and third party data sourced to create summaries for each company & contact;

- scored them for outreach 

- wrote unique email and Linkedin message for each contact

- sent 30,718 emails and 236 Linkedin messages

- Created bespoke PDF guides with advice on improving product adoption rate, user onboarding, user activation, or another problem the prospect was struggling with - personalized to their company use case (ok, that was their little brother Claude)

- Got 58 positive replies 

- Drove a bunch of demos, QDs and six figures in pipeline

And they get paid only $1850 per month.

That's impressive for a 8-month old (this is how long it took to build this system - using Clay + OpenAI api, because Claude Code wasn't there when we started). 

Congrats to Bilal Ahmad 艾一鸣, the father of this marketing genious.

Ok this is probably the most mind-blowing case of TLAs *smashing* on Linkedin I’ve ever seen - which made me totally reconsider our own ABM ad strategy & reprioritize demand gen plans: $0.15 cost per Landing Page click (! - 66 x cheaper than image ads!) and…$ 0.02 /engagement; … 169,571 impressions (CPM… $2.31) , 18,113 engagements and 2,669 clicks to LP (1.57% average CTR to landing page, 10.68% CTR)…all for only…$391 🤯 Audience? Senior SaaS executives (mainly CFOs, CEOs etc.), global audience (US + UK + DACH/Western EU). Several meetings booked. TLAs drove 83% of all website clicks for under 6% of the total ad spend - I told them to hold their horses until the data syncs and they can tell if the conversions were influenced by TLAs only, or have been influenced by image ads and carousels too…but when the company-level engagement results came in (from ZenABM) - the demos were all influenced by TLAs only. Needless to say, other ad formats (image & carousel ads) had to go. 

STORY TIME: 👇 The co-founder of Valueships (Krzysztof aka the “pricing guy” & the only person who actually closed a deal at my wedding except my husband) has been building amazing content & personal brand on Linkedin + conferences. But being the smartest guy in the room doesn’t scale - Kris had to sometimes hop between 3 countries in 2 days 😂 so I’ve been pushing them to try Linkedin ABM, and finally Valueships’ Head of Growth, Aleksandra, launched their ABM campaign - here’s how it did: 

Top 3 TLAs: 
🥇 - 20.92% CTR, 4.69% eCTR (= clicks to landing page/ impressions) 1,394 clicks, $0.10 CLCP - “Millennials: 'skinny jeans are still cool!' (they're not); SaaS: 'seat-based pricing is still cool!' (it's not)”

🥈- 21.03% CTR”, 3.02% eCTR, 141 LP clicks, $0.02 CLCP; “In a single month, Amos Bar-Joseph from Swan AI (just raised $6M) paid Anthropic $51,217. If Antropic did seat-based pricing like most SaaS co's, how much would they be able to charge?"

🥉- 8.46 CTR, 2.29 eCTR, 463 LP clicks, $0.10 CLCP - “As I'm sadistically bashing software companies for pricing mistakes, I couldn't let it slip. Jenna Alburger did a great job in smashing Netflix, and I spin it for myself as well:” 

👉 Full case study: https://lnkd.in/eiCSiPhh

Key patterns for the top 3:
- storytelling/humor hook (skinny jeans, real company example, Netflix teardown) - never direct product pitch
-  real companies with real numbers (Swan AI, Anthropic $51k, Netflix)

Lessons? 

Do:
✅  real people, companies, products + real data/results
✅ Write in 1st person, admit mistakes
✅ Short punchy hook ≤2 lines 
✅ Open with paradox/ specific number
✅ mention specific pain 
✅ Deliver value before any CTA (in P.S./ soft offer (but DO put the link in)

Don’t:
⛔ pitch slap, open with generic "We're excited to announce we’ve been featured in Gartner report”
⛔ Write in “brand voice” rather than *your* voice / 3rd person
⛔ no value, make it about your product/features

*Ugly cry* - after 4+ hours of debugging what the heck was going on with our LinkedIn account (first 40% match rate showing as >90% match rate, then newly pushed matched audiences *not* building at all since...Thursday last week), talking to 3+ support reps, re-allocating budget and even pausing some of our campaigns...our Account Manager finally responded (what we already heard down the vine...on LinkedIn...but from Linkedin ad experts, not  LinkedIn!)

This is *not* how you handle an outage/bug. This is how you lose your user's trust, confidence and...budgets. 

Because seriously - I was on the verge of re-allocating a significant chunk my (let's face it - very significant) monthly budget to other ad channels for the rest of the month. 

It takes <10 seconds to deploy an in-app banner (ekhm, with Userpilot, it takes <5 seconds 😉 - you can build these in-app announcements for free for 14 days here: https://lnkd.in/ej74TitF) informing users you have a problem. 

Everyone experiences bugs. It's not about eliminating them - it's about communicating them well. The users are a lot more forgiving when you do, then we you're trying to keep poker face and pretend it's business as usual. 

It's not. You're gambling with your users time. 

That never lands well.

Spotted in my area. Gives Series A B2B SaaS website navigation menu, no?  👀

For anyone I've ever "ghosted" on LinkedIn after you've asked me to pick my brain* about something related to ABM/LinkedIn ads  - A) I'm sorry B) If I'm still not getting back to you (my inbox is a mess) - then this free chatbot by ZenABM** (link in the comments) is the second best - you can ask it anything related to Linkedin ABM, and - unlike me - it will respond instantly. Aaand it also contains the knowledge from such LinkedIn ads legends as Tim Davidson, Veronika Vēbere or Maximilian Herczeg - so each of your questions will be answered by several experts at once. Unlike ChatGPT - it's generating responses based on the expert's Linkedin posts, TLAs and webinar transcripts. Enjoy! 

*as long as it wasn't a "quick question" preceeding a sales pitch - then thischatbot will definitely not buy from you either 😅) 

**is building this chatbot my husband's way to say I should be spending less time on LinkedIn? Michal Jackowski 🧘‍♀️, thoughts? 🤔

A founder I work with almost gave up on outbound because of this LinkedIn post. Instead of targeting tens of thousands of accounts - why can't we just 10x our conversion rates? Instead of 0.35% meeting booking rate - why don't we turn in into 3.5%? My recent post about our scaled outreach results has caused such a stir it may be soon turning into a meme 😅  My five cents: most people have ungodly expectations of their campaigns (be it cold outbound, Linkedin ads, or landing page conversion rates) based on some anecdotal campaigns from LinkedIn posts nobody saw any receipts for... 

Some people assumed it's 'spray and pray' - and maybe I wasn't explicit enough that the system takes 100s of contact level and company level properties ("signals" - from our CRM, organic website visits (RB2B/Vector 👻), tech/competitor usage via BuiltWith, Linkedin ad engagements from ZenABM, product launches and company news from Apify etc.), scores them for the most relevant and timely ones, and crafts a bespoke, unique message to each prospect - offering a resource tailored to their use case, company and role. 

Even with that level of personalisation - and waterfall contact data enrichment from 7+ providers, multi-threading, multi-step and multi-channel outreach (email via Smartlead and Linkedin via HeyReach.io) - I am not expecting meeting booking rates or even positive response rate > 1% anymore. I know my industry, I know the persona, and I know how "easy" it is for us to decipher a strong enough intent signal. So many people have tried to beat it - but this is the reality for us. 

Some people will miss the message. 
Most people will be too busy. 
A lot of people will just have "other priorities" and won't be interested even in a free resource/consultation. 

But if someone can prove me wrong and get us 35 positive responses from a 1000 prospects then I'm all game for it 😅 submit your applications for a free POC in the comments, I'm always in the market for that!

Unless you've been living under a rock - you've been probably having FOMO about how you can use Claude Code (the coolest kid on the block) in your work. And for a good reason: 

I'm not gonna lie and pretend I fully understand how PMs juggle so many tasks in their scope - but what I understand is that I would never want to be a product manager because of how stressful and complex the work is and how much multitasking and context switching it requires.

As Ron Yang wrote in his recent post, a lot of this can be now alleviated by Claude Code (Ron kindly shared his Claude skills for PMs for free - I've linked to his repo below), so it's definitely something I wanted to dig in here as well: 

How can Product Managers use Claude Code to streamline their work?

Most PMs still use AI like a chatbot: ask a question, get an answer, move on.

Claude Code flips the script. 

Instead of one-off prompts, you build repeatable workflows that run on your own context: files, docs, notes, transcripts, and data.

That means the AI isn’t just helping occasionally - it becomes a layer that orchestrates knowledge work.

Instead of juggling multiple tools & context stitching, you can create workflows that:

- pull context from your files
- run structured analysis
- generate outputs in the format you need
-  save them back into your system.

The hype is real because the shift is so powerful:

Don’t just ask AI questions - build your "second PM" that will be working 24/7 for you. 

Check out the post below for 4 ways PMs are actually using Claude Code - based on interviews with Teresa Torres & Sachin Rekhi that I came across on YouTube!

Hey folks, Unless you've been living under a rock - you've been probably having FOMO about how you can use Claude Code (the coolest kid on the block) 

Open article: Claude Code for Product Managers ☀️ by Emilia Korczynska • 4 min read

"If you're tired of London, you're tired of life." - the main reason why I moved to London was because I wanted to go to more tech events and build a network. To say it worked is like to say nothing at all. I'm learning so much from peers in the best way for me, and get to share my learnings too - this time, I will be talking about the most cost-effective ways to reach your ABM target audience on Linkedin at Reachdesk x Demand Gen London event on the 18th of March - mark your calendars & sign up in the comments!

Filip Matekovic

Most marketing teams don't have a marketing problem. They have an operations problem. Too much manual work. Too many tools. Not enough systems. They're measuring vanity metrics instead of revenue.

I run marketing at Hunch, where we help modern marketers fix exactly this. We automate creative and media workflows for paid social - connecting your data, creative production, and campaign execution in one system. 

You can scale high-quality, personalized ads that resonate with audiences without hiring more people or burning out your team. You get the speed to test more, the volume to beat ad fatigue, and the metrics to prove what drives revenue

I've worked with Fortune 100 brands and led teams at award-winning agencies before Hunch. I specialize in marketing operations and go-to-market strategy. Now I use that experience to run marketing at a fast-growing platform, working with 100+ e-commerce brands.

I use AI and marketing ops to build revenue systems that actually scale. Revenue over vanity, every time. If you can't tie marketing to revenue, it's not marketing - it's just content. I share how we use AI at Hunch. Real customer results. What drives revenue. Systems that scale without hiring.

Follow me to learn how to:

- Scale personalized campaigns without losing your brand voice

- Use AI to supercharge creative storytelling

- Build marketing systems that drive revenue

- Choose a platform that blends automation with human creativity

Hunch is the automated creative production and media buying platform that powers d2c brands, retailers and agencies.

Developing data-driven marketing strategies and tactics that drive positive ROI.  Growth hacking in a fast-paced environment in order to skyrocket Inbound MQL

- Complete ownership of the Hunch's marketing mix
- Responsible for achieving KPIs for inbound MQLs
- Building and scaling complex B2B marketing campaigns using ABM model
- Hunch Growth hacker and brand advocate
- Content author

Liquid Death's entire creative operation runs on a 5-person in-house team.

30 billion earned media impressions. Total spend - every production dollar, every talent fee - under $2 million.

Most beverage brands spend more than that on a single campaign.

Reason isn't the dark humor. It's the constraints.

Because the team knows what works, they handle everything from concept to execution in-house. No agency briefing cycles. No approval chains. No "too many cooks" problem.

But knowing what works only happens when you've defined what you are.

Liquid Death made one creative decision early: every piece of content would look and feel like it came from a heavy metal band, not a beverage company. Skulls. Dark humor. Anti-corporate tone. That's the aesthetic ruleset. Rigid as any brand bible.

Every time they make content, team asks one question: will this get shared? Likes and comments are fine. Shares are what they're after.

One filter, one aesthetic, one metric.

That's the system. Everything else is just execution speed.

Most creative teams operate with the opposite logic - maximum flexibility, minimum constraints. Every campaign is a blank slate. Every brief restarts from zero. Freedom feels productive. The output rarely is.

Constraints aren't a limitation on creative output. They're the reason output is possible at scale.

Liquid Death produces notable content a handful of times a month - and keeps the bar high. Not volume for volume's sake. High-quality output, fast, because the decisions about what they stand for were made once and never relitigated.

The 5-person team isn't impressive despite the constraints. It's impressive because of them.

Paid Social Playbooks | Head of Marketing @ Hunch | Predictable Revenue Systems | AI & Automation

Problem isn't AI creative tools. It's how brands use them.

Here's the pattern I see across accounts doing this wrong: they treat AI as the strategy, not the production layer. They generate 500 variations, throw them at Meta, and wait for the algorithm to figure it out.

Everyone assumes it's a production problem. Generate more. Test faster. Feed the algorithm.

Wrong game.

After working with 200+ accounts, we saw that AI scales what you already know. If you don't know what resonates with your audience, AI will just help you fail faster at scale.

Brands actually winning aren't generating more. They're coming in with proven hooks, tested templates, real audience insights - and using AI to remove the production bottleneck between knowing what works and having enough of it live.

Losers treat AI as the strategy. 500 variations, no framework, no signal. Just volume and hope.

AI scales production. It can't manufacture strategy you don't have. If your current ads aren't working, more of them won't fix that. You'll just fail faster and spend more doing it.

AI is a production engine. It amplifies what you already know works.
Volume without strategy is expensive noise.

"AI replaces teams" debate is the wrong conversation.

Everyone's arguing about headcount. Nobody's asking what the team actually does with their time.

For solo operators building simple products? Maybe. For B2B SaaS running outbound, positioning, events, demand gen, and partnerships simultaneously? 
Not even close.

What actually happened at Hunch: we removed everything repetitive. 
First drafts, research, briefing, reporting, monitoring. AI handles it. 

Our team handles everything that actually matters:
Strategy. Positioning decisions. Partnerships. GTM sequencing. The judgment calls you can't automate.

AI made our output 8x. It didn't touch our thinking.

What AI can't touch: positioning decisions, partnership judgment, GTM sequencing, reading a room on a sales call. Work where context and pattern recognition from years of experience actually matter.

"Smaller team, same output" framing is still thinking about this wrong. 
Real unlock is the same team doing work they couldn't access before - because the noise is gone.

Should you hire that next marketer?

Shopify's CEO says not until you answer this question first.

"Prove AI can't do it before you ask me for a hire." That's Tobi Lütke's rule for every team at Shopify.

He built Shopify because every e-commerce tool he tried was garbage. That scrappy, build-it-yourself mindset still runs the company 20 years later.

His core operating principle: If I do something three times, I automate it.

In 2023, he deleted every recurring meeting of 3+ people. 322,000 hours freed. That's 150 full-time employees worth of time.

Then in 2025, he raised the bar again: Before you ask for headcount, prove AI can't do it first. Some teams were already hitting 100x output with AI. Same people. Better systems.

This is how Tobi thinks: Problem is never talent. It's always process.

Manual handoffs. Repetitive tasks. Meetings about meetings. That's what kills output. 

He's spent 20 years proving that your best people aren't slow. Your workflows are.

40% of your team's capacity goes to QA.
Not testing. Not optimizing. Just verifying that 500 locations are running correctly. This is where agencies hit their ceiling.

Managing multi-location campaigns manually isn't just slow - it's a structural bottleneck that limits how much business you can actually service.

Each location needs localized creative, regional messaging, store-specific offers, and audience targeting. Manual workflows can't scale this without breaking.

Manual workflows bend at 20 locations.
They break completely at 50.

Budget changes require clicking through hundreds of ad-sets. Promo updates take entire afternoons. Execution speed collapses before strategy ever does.

I've watched agencies turn away clients not because the strategy was wrong, but because they couldn't operationally service the volume.

Bottleneck isn't creative thinking. It's campaign infrastructure.

When one agency managed 747 locations with six people doing daily manual updates, they weren't optimizing performance - they were maintaining existence.

This is the trap: either hire for repetitive work, or cap your growth.

Template-driven workflows change this completely. One spreadsheet becomes campaign operating system. Update a date, budget, or creative element once - it syncs across hundreds of locations automatically.

Each location gets its own localized creative, messaging, and offers - without manual production cycles.

That 40% QA capacity? It goes back to testing, iteration, and actual optimization.

Execution stops being the constraint. Strategy becomes the lever again.

Managing 20+ locations? See how it works → https://bit.ly/4b3QUf7

Most Meta advertisers obsess over targeting. But when Meta spends 70% of your budget on 65+ year olds, you set the wrong goal.

Algorithm is doing exactly what you told it to do. You just set the wrong task.

I saw this across 100+ accounts. Teams spend weeks on audience architecture - layering interests, adding exclusions, building targeting structures that feel increasingly precise. Meanwhile Meta has 12 creatives a month to work with.

Jon Loomer wrote about this recently - when to actually restrict your audience on Meta. His conclusion: almost never. And the reason is always same. It lives upstream from targeting.

Algorithm doesn't need better instructions on who to find. It needs more raw material to test against. When you give it 12 creatives, you're not running a targeting problem. You're running a data starvation problem, and no amount of audience refinement fixes that.

Benchmark I see across accounts that actually scale: 80+ variations per month. Most brands are at 12.

Teams are optimizing the wrong variable. Constraint isn't who Meta is finding - it's how much you're giving Meta to work with.

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The Battle

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