Florin Tatulea

Sales Leader | LinkedIn Top Voice 2023 | GTM Advisor | Focusing on Seed → Series B

I'm a passionate leader that lives and breathes all things sales.

I was lucky enough to be the first sales hire at Loopio and have had the opportunity to be a part of and contribute to the exponential growth that had led us to a sales team of ~50 strong. In my 6.5 years at Loopio we grew revenue by 65x. 

I am now doing it all over again at Common Room

Whether it's been as an SDR, AE, Manager or Director, I'm constantly looking for ways to reinvent myself and my team.

I'm a people-first leader that understands that leading a team is not about me. It's about lifting others up and seeing them succeed. My success is simply a bi-product of my team's success. 

As a sales leader, I'm curious about scaling sales teams, generating pipeline, increasing win rates and lowering ramp times in a remote world.

As an individual, I'm passionate about copywriting, sequence/cadence building, leveraging social selling and the future of sales technology.

Director of Sales

Last month, after 20 months of building at Common Room, I took some time away from being a full time operator. 

It’s been an absolutely EPIC journey. 

In a relatively short timeframe that I’ve been there: 

-We 4x’d ARR 
-4x’d the size of the SDR team
-Sourced 7-Figures in outbound revenue
-20x’d monthly outbound pipeline $ and built the outbound engine from scratch
-Re-architected our internal Common Room instance. This involved “GTM Engineering” the brain behind our outbound program using our AI agents
-Recruited and worked with the best operators I’ve ever had the chance to work with in my career. 
-Opened career paths and had our first rounds of SDR to AE promotions (this is a really important one for me)

The program is now in fantastic hands with Sara Hanegby . 
 
There aren’t enough words to say how grateful I am for everybody on this journey. You know who you are!! 

On the side, I’ve also been running my own 6-figure media company. 

I’ve given my career my all over the last decade and needed to slow down to focus on some other aspects of my life. 

It’s why I’ve been quiet on here the last month as I've stepped away from the tech echo chamber.

But… I am baaaack!!! 

I have some really exciting projects in the works and I’m looking forward to doing some advisory work and helping the start-up ecosystem over the next few months. 

If you are a company < $20M ARR and are thinking about scaling your outbound program I’ve figured out quite a few things over the last 12 years in B2B SaaS: 

1. I've built outbound from scratch at 4 companies and 3 have already been acquired.

2. I’ve designed and scaled sales programs, selling into SMB to large enterprise (Fortune 100 companies). 

3. I’ve cracked the code selling into Sales, Marketing, Rev Ops, Engineering & HR Leadership and have built systems that work across industries.

Im also excited to work with orgs on the content and thought leadership side. If you are selling to GTM leadership, I’ve built a curated audience of ~90,000 across LinkedIn, Substack & X. 

I’m only a DM away. 

It’s the most exciting time EVER to be building. 

LETS GOO!

GTM Leader | LinkedIn Top Voice | Advisor

I just took a look at the new Nooks launch.

Users of Outreach and Salesloft are going to want to take a look after what I saw with the their new AI Sequencer.

I believe they are going to seriously shake up the legacy sequencing space. 

Not a lot of people know this, but I was one of the first 10 customers of Nooks when the company was still just Dan, Rohan & Nikhil and a virtual sales floor.

As a multi-time customer, not even I could have predicted the level of execution that their team was going to put forth.

Apart from building a quality product FAST, Nooks did something (intentional or not) that is going to give them a massive competitive advantage over the next couple of years.

They owned the action/execution layer FIRST, and have now built the Data Foundation layer (Account Research, Signals, etc.) around it.

Most GTM tech orgs in the market today are doing the exact opposite.

They built the data foundations and are now trying to build an execution layer.

Why is this important?

Because the action layer is where the rep lives. If you own the action layer and do it well, it’s VERY sticky.

Reps will kick and scream if you take it away from them. Re-training tens or hundreds of reps on a new system of action is a nightmare for enablement.

Trust me, I’ve lived through the kicking and screaming.

Selling GTM tech, everybody was constantly asking us… “Can you integrate with Nooks? That’s where our reps live.”

Right now there is a full-blown race to see who will own the full “Sales OS”.

Today, Nooks made this race a lot more interesting by launching their new Agent Workspace for Intelligent Outbound.

They just added:

1. Signals (Combining live web intent with your CRM and past calls)
2. Autonomous Account Research Agents (Running in the background 24/7)
3. List Building Capabilities
4. An Omnichannel Sequencer (Executing across Email, Phone, SMS, and Social)

Imagine autonomous agents that monitor web intent in the background, cross-reference it with your CRM, draft hyper-personalized emails, and then drop the warmest leads into a power hour calling block.  Because it's actually an action layer, the feedback loop makes it smarter with each engagement. 

You can argue that they have a real chance at being the MAJOR player in the consolidation of the GTM tech stack.

They also have a massive moat of call data (50% of our own outbound meetings came from cold calls)... which a lot of other data platforms simply do not have.

​​GTM Leaders: what are your thoughts on this space? Let's debate below

(PS - go check out the massive Nooks launch ). 

#NooksPartner

SDR teams are toast. 

In fact...

SDR teams are so screwed that OpenAI and Anthropic are hiring SDR teams aggressively. 

The thing is, outbound is not a game of AI and automation. 

AI is a tool. 

Outbound is a game of: 

Precision

Timing

Deep industry expertise

Human relationships

It's why orgs like Ramp recently shut off their autonomous outbound program. 

It's why the people that make these LLMs realize that humans are still necessary. 

At least for now :)

If you prospect on LinkedIn, you should watch this. 

This is something I’ve always struggled with that I’ve now found a solution for.

If you use sequencing platforms like Outreach, Salesloft and Gong Engage you’ll know that after you do the manual steps of sending connect requests, LinkedIn activity just gets lost to the void.

There is no easy way to systematically filter for:

1. New LinkedIn connections who are actually in your ICP vs general networking contacts

2. Prospects who have accepted your request but you never actually bothered to send a DM to

This has made systematic outreach that’s coordinated more difficult.

This is no longer a problem as I’ve started to use Kondo: Superhuman for LinkedIn DMs. 

I can now:

→ Filter for connections and bulk tag them as prospects

→ Search for specific personas very easily with a fuzzy search that actually works

→ Open a custom of these personas posts on LinkedIn to build more tailored outreach

SOOO much easier. 

They have a great promo running right now if you sign up by the end of the week (Feb 28):

2 months free with this code:  https://lnkd.in/gFETw84Z

You are welcome :) 

#KondoPartner

2026 is the year to double down on cold calling.

Last year, 50% of all of our qualified opps came from cold calling. 

Keep it simple.

First, get yourself a proper data provider for cold calls so you actually get connects. 

FullEnrich has been an absolute CHEAT code for us with their 20-provider waterfall. 

They now also have amazing search functionality directly in the platform so you can build proper lists. 

Then, I break this down into 3 parts (here's an example):

1️⃣ Permission Based Opener

Hey this is {NAME}, I was actually just on the customer tab on your website at
{ACCOUNT}, and had a question. Do you have a sec?

2️⃣ Menu of Pain (most important part)

Noticed you are selling to accounts like {ACCOUNT}. Typically when I talk to SDR leaders at commercial open source companies, they’re focused on one of these three things:

1. Your SDRs see tons of developer engagement but struggle to identify which users are actually ready for a sales conversation.

2. Your team relies on community signals, but it’s hard to surface and action on real buying intent.

3. SDRs waste time digging through GitHub, Slack, forums, and LinkedIn instead of working on the right leads.

3️⃣ Open Ended Question

How are you making sure your SDRs are focusing on in-market leads?

-----

I like the menu of pain, because if done correctly and the messaging is tight, at least one of the 3 challenges is something they are likely thinking about.

This then opens the conversation.

3 days left this week. Let's get it 🫡

#FullEnrichPartner

No alternative text description for this image

How do you feel about this take GTM leaders? 

To me it comes across as a take from somebody who doesn’t fully understand GTM. 

Sure, there are a lot of incredible things AI can do to automate TAM building, lead scoring, account research, funnel optimization etc. 

But GTM is also still one of the professions that is still deeply human. 

I doubt this person has spent a lot of time making cold calls, on demos, meeting clients in person etc. 

If you believe this, you essentially believe that robots will be selling to each other only in the near future. 

No offense to you Jay Sahnan. I respect the opinion and it’s a good discussion 🙏🏻

graphical user interface, text, application

We talk about “GTM Engineering” and “Revenue Orchestration” but how does it apply to outbound? 

Here’s how you tactically execute a strategy at scale using signal data. 

Now we have the ability to capture 100+ signals at a time, transform the data and tell us which leads are the lowest hanging fruit.

That’s a HUGE amount of context for sales reps to have in one place and it means that we can now get HYPER-specific with our messaging and sequences.

Each signal that is important to your organization should have its own purpose, messaging, and sequence built out.

Step 1: Write down all the signals that you currently have access to at your organization. 

There are standard signals everybody can use (I.e. web visits) but also very specific signals to your org (I.e. software outages for an outage tracking product) 

Step 2a: Map out where each signal implies a lead is in the buyer journey

Look at the image below. You can see that a signal and therefore message has to adapt to where somebody is in the BUYER JOURNEY.

Step 2b: Create a lead-scoring system that takes into account which signals (or combination of signals) tend to imply that an individual and account is ready to buy or at least talk to sales. 

This usually happens when they are in the “Solution Aware” and “Product Aware” stage.

Step 2c: Cross reference these leads with your account level- ICP criteria. 

Not all leads that exhibit buying behavior work at accounts that are good fits for your business. (THIS IS CRUCIAL). 

Step 3: Create messaging (i.e. email campaigns, outbound sequences etc.) for each signal.

You can get even more complex here and create messaging or sequences for combinations of signals.

Step 4: Set up alerts and workflows so that if a lead provides a certain signal or hits a certain threshold they get put into the respective “campaign”.

There are many platforms to do this in… Common Room, Clay etc. 

THREE OTHER THINGS TO CONSIDER:

1. Top of funnel leads that aren’t ready to talk to sales go in automated sequences that are more focused on education (this can either be done by marketing or SDRs)

2. Mid-to-Bottom of funnel leads are sent to the sales team and are put into the appropriate sequences (emails + call scripts + LinkedIn message templates are already built out by the team). It is up to the SDRs/AEs here to do additional research and tie your product's value to your prospect’s strategic priorities.

3. Consider the size of the account and the number of owners on the buying committee. Start multithreading into the various decision makers/economic buyers who will influence your deal so you establish momentum early.

(h/t FletchPMM  for the great visual)

#sales #outbound

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Obtained a GPA above 3.5 for the entire academic year 2011-2012

Dean`s List

E3 Business Case Competition

Top Ranked Junior Tennis Player - Canada  

Talk Master Certification 

Competed against 20 business schools across the U.S. including Wharton, Stern, Berkeley and Sloan. 
This competition asked students to choose a stock to either long or short, with the only requirement of it having a 30 day SMA of over $200m in market cap. Our team, being the only international presence in the competition,  chose to pitch Iridium (IRDM), a satellite communications company, and have received a final judgement score of 24/30 based on Stock Selection, Presentation, and Q&A. 

Georgetown Stock Pitch Competition

Cold Email Conversion Machine by Florin Tatulea

Prospecting from the Trenches | Florin Tatulea | Substack

Working with Local Food Plus, a not-for-profit aiming to drive a sustainable food model to the benefit of local farmers and retailers in Ontario

There is a very simple but important question that most sales reps miss when they are selling to GTM leaders . 

And I say this from experience as somebody that buys software. 

Put simply: 

“Is your team hitting their number…What % of attainment is your team at?” 

The harsh reality is that unless you are a SVP/EVP/C-Level exec with long term incentives, the average GTM leader doesn’t really care to change much if things are working well. It’s a massive uphill battle to sell to a leader that is crushing. 

Even most VP, Sales are just trying to survive next quarter. 

It’s very difficult to sell somebody the “future” if they are at 110% of quota as a team and in accelerators. 

Saves you a lot of time as a rep. 

Just what I’ve seen over the last decade. 

Thoughts?

Demand @ Common Room | Advisor to SaaS Startups | Ex Growth & Marketing @Segment @Retool

Core focus: demand gen, marketing automation, conversion optimization, paid acquisition, lead nurturing and scoring, multi-touch attribution, funnel analysis

Kevin White

This is the best swag I’ve ever given away at an event: scrunchies.

Overheard at the eTail™ this week:

“Can I get a few more? I have two daughters at home.”

“I feel like there’s never swag for me at events. These are great!”

“Are you the booth with the scrunchies? My colleague sent me over here for one.”

–––––––

In addition to the positive crowd feedback, here’s why I love scrunchies as swag:

✦ Lightweight and compact (easy travel)
✦ Brand tie-in (scrunch;scrunchies)
✦ Price point (~$3 per)

All markers of a great giveaway in my book.

Our scrunchies were such a hit that I feel the need to get more out in the wild as a brand awareness play.

If you want one, drop a comment below (”scrunchie” or “scrunch”) or just DM me, and we’ll send a few out.

===

P.S. When you get yours, I won’t be mad if you share about it on the socials and tag Scrunch.

Marketing @ Scrunch | Advisor to SaaS Startups | fmr Growth & Marketing @Segment @Retool @Common Room

I’m about ready to throw in the towel on direct attribution.

In the past, we used to be able to push people to our website, slap on a UTM, or gate an ebook behind a social form.

These tactics no longer work in a world where…
-- People don’t want to leave the feed.
-- People don’t want to be tracked.
-- People have been burned by one too many ebooks.

Seeing these trends play out (and engagement rates tank), I’ve adjusted 80% of my digital investment to non-attributable channels.

Let’s take a quick inventory:
-- LI paid ads (90% thought leadership) 🕳️
-- Podcasts & newsletters 🕳️
-- Influencer programs 🕳️
-- AI search 🕳️
-- Google ads ✅

The only channel above I can attribute the traditional way (i.e., clean UTM → website conversion → CRM visibility) is Google Ads.

Everything else is indirect.

Yes, some of the channels listed above include attributable links (e.g., podcasts, newsletters, influencer posts), but most people don’t click them.

What the user journey actually looks like goes something like this…
-- Exposure to content
-- Absorb some of the message
-- Take note for the future (repeat) OR
-- Take action if timely

And, when they take action? It’s usually a branded search or a direct website visit.

When this is your reality, trad attribution is pretty much useless (harmful even).

But, alas, not all attribution is lost.

It’s still possible to triangulate where something was sourced in a zero-click world.

Introducing: Neo-Attribution.
-- Add a self-reported attribution field
-- Build in “how’d you find us?” as a discovery question
-- Flag channels sales transcripts
-- Track brand presence in AI answer engines (ahem... Scrunch)

(Btw, just having fun with the name and not actually trying to shoehorn in a new term)

Start tracking these touchpoints systematically, overlay pipeline trends with investment, and you’ll start to get a picture of which channels are working and where to double down.

Sure, it’s not perfect. It’s a little messy. Your data science team won’t love it.

But it’s what we’ve got.

Cat’s out of the bag.

Attribution as we once knew it is not coming back.

It’s time we stop fighting perfect attribution and embrace the shift.

“AEO is just SEO rebranded.”
“There’s no such thing as rankings in AI search.”
“Tracking AI responses is moot because LLMs are probabilistic.”

☝️ Things search experts say about AI search (aka AEO GEO).

And, to a large degree, they’re not wrong.

But for us facing real-world expectations from execs (and the board), this is not helpful rhetoric.

*What exactly is the alternative?*

When your CEO comes to you and asks: “How do we compare to competitors on ChatGPT? I searched and didn’t see us show up.”

Your response can’t be: “Well… funny you say that, because our SEO results are still looking strong, and the experts say ‘if you're doing well in SEO, then you're doing well in AEO’ so I think we're set! That, and your responses are personalized to you, so maybe you’re too paranoid about our competitors?”

That’s a recipe for unemployment.

===

So what’s the alternative?

If AI search is probabilistic…
If prompts are infinite…
If responses vary…

We need to stop treating measurement the same way we’re accustomed to in SEO.

AI search doesn’t work that way. 

Responses are probabilistic. 
Prompts are super long tail with infinite variations. 
Memory and personalized results are the norm.

But that doesn’t mean it can’t be measured. It just takes a different approach.

The most common mistake we see is falling into the “boil-the-ocean” trap--e.g., trying to track every permutation of every prompt. That’s a fool’s errand.

A better approach is to track a consistent, representative set of prompts tied to the topics that matter to you (and to track them the same way over time).

When you do, in return, you get a barometer that reveals how your brand shows up over time in the topic areas that matter to your bottom line.

At Scrunch, we liken this approach to a 🌤️ weather station: A single reading doesn’t tell you much, but a network of readings over time reveals how you’re trending.

And that’s one of the core shifts in how to treat AI search vs SEO.
We don’t have GSC (although Bing just added this).
We don’t have ad impressions (not yet, at least).

What we have is a weather station (if you will) that provides a stable, consistent stream of readings, indicating whether the climate is shifting.

Michael Iannelli, PhD details more on this approach (plus more analogies) on the Scrunch blog. Will post the link below if you want to go deeper.

Two announcements dropped this week that speak to a trend I predict will blow up this year: Optimizing sites for AI bot traffic.

Those two announcements?
→ Cloudflare introduced Markdown for agents
→ Google Chrome shipped WebMCP (aka Schema 2.0)

While both address the opportunity at hand from different angles, they both signal that 1) AI traffic is something to pay attention to, and 2) the standards and protocols in place will shift.

I predict this is just the start. In the coming weeks, I’d bet we’ll see similar announcements from “big” tech—browsers, CDNs, CMS (heck, maybe even the AI platforms themselves).

Important sidebar: ”Big” in quotes above because these are public players making announcements vs. your random llm.txt or AI landing page.

As we saw in Web 2.0, standards like Schema 1.0, E-E-A-T, etc., became understood and hardened over time.

It would be a welcome addition to the AI search space, which still feels like the wild west to some degree.

The big difference is that there are many players—OpenAI, Perplexity, Gemini, Anthropic—all which might create their own “standard.”

But even it that’s the case, at least we’ll get some transparency into the black box.

Regardless of the nuance, one thing remains true: AI bot traffic should to paid attention to.

There’s a user (usually with intent) on the other side of it. And at some point in the near future, that traffic will start transacting.

It’s no longer the case that we can ignore the bots!

Microsoft just opened up Pandora’s box, giving us a first real glimpse into AI search performance straight from the horse’s mouth.

Sure, it’s just Copilot and Bing AI summaries.
And sure, it doesn’t reveal actual prompt volumes.

But what it does give us is visibility into two very important things:

1️⃣ How LLMs interpret prompts

Microsoft uses the term “Grounding Queries” (aka query fan outs).

Their definition of a grounding query: “Shows the key phrases the AI used when retrieving content that was cited in its answer.”

In other words, grounding queries is what Copilot uses to chunk and interpret long-tail prompts before retrieving content.

––––––

2️⃣ Citation volume (prompt volume by proxy)

The new AI performance tab in Bing Webmaster Tools shows:
✦ Total citations: Times your content was shown in an AI-generated response.
✦ Cited pages: Tally of unique pages cited in the selected time window.

So, while actual prompt volume isn't shown, we do get a proxy for what users are prompting, at what volume, and how we show up.

––––––

Okay, so what?

While Microsoft doesn’t exactly dominate AI search market share, they 1) have a pretty decent sample size and 2) I’d guess have some insider info as to how ChatGPT—the platform with the largest market share—works.

If you buy into those two assumptions (and I do), here’s how I’d take action👇

Track top-performing Grounding Queries across models
⤷ Use an AI visibility product (ahem… Scrunch) to track how your top Copilot prompts are performing across other models like ChatGPT, Perplexity, Gemini.

Double down on top cited content
⤷ If citations are a proxy for prompt volume, use your top-cited content as a guidepost to create similar content and continue reinforcing those pages to stay on top.

Reverse engineer cross-model gaps
⤷ If you’re cited in Copilot but not elsewhere, it’s a signal that you’re on the right track but just not there yet. Uncover what’s being cited or mentioned instead and reverse engineer how to level-up top performing pages in Bing Webmaster tools to get faster wins.

A reminder that sometimes small changes can have an outsized impact.

This might be dating myself, but back in the early aughts, there was a popular website called WhichTestWon.

As the name implies, the site would show you an A/B test and let you guess the winner before revealing the answer.

Most of the wins felt counterintuitive (I think my hit rate was less than 50%).

What stuck with me wasn’t just that results were surprising.

It was that many of the tests were just tiny changes (button text here, headline tweak there), which yielded massive results.

I’ve always wanted to ship one of those “minutes to implement; hit your number” type of growth experiments.

But in all my years, I’d never managed to catch the proverbial white whale.

Until now.

A few weeks ago, we shipped a 4-word test that crushed to the tune of:
📈 +54.49% uplift
✅ 97.5% chance to win
✅ Statistically significant

The experiment?

Changing our homepage CTA from “Get Started →” to “Get your free report.”

Why I think it won:

Low perceived risk
⤷ “Get started” feels like a journey. “Free report” feels like a gift.

Clear tie-in to the input
⤷ Domain → report makes sense. Domain → onboarding doesn’t.

Specific > generic.
⤷ “Get started” is vague. “Free report” is concrete.

Curiosity trigger
⤷ “Report” implies insights about you.

===

Now, of course, in addition to getting more conversions, we actually had to deliver on the promise.

So when a domain is submitted, we actually generate a real, personalized report using our product and a bit of AI magic.

CTA promises insight. And the UX flow delivers.

taplio

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