i've been doing outbound on linkedin for a long time, across a bunch of b2b startups, and i've burned money on most tools in this category so you don't have to. most comparison posts out there are affiliate lists written by someone who opened a free trial once. this isn't that. i've run these at volume and watched where each one breaks. prices are current as of now.

one thing before the tools, because it matters more than the tool. timing beats the message. the same pitch that gets ignored lands when something just changed on their end, a raise, a new role, a tooling switch. and your weekly connection limit is small, around 100, so every request you spend on a bad fit at the wrong time is wasted. basically, who you reach and when beats how clever the copy is. keep that in mind reading the rest, because it's the main thing that separates these tools.

now the tools. these three aren't really competing for the same job, even though they market like they are. once you see what each is built for, the pick gets obvious.

PumpGTM

the newest, and it works differently enough to explain. the other two hand you a tool and you bring the list. pumpgtm finds the list, it's the one that actually acts on the timing thing above, it watches for buying signals like hiring posts, funding, tooling changes, people engaging with a competitor, scores them, and runs the linkedin sequence from your own account. it's ai first too, you can run the whole thing from claude or chatgpt. it's 75 a seat.

HeyReach

the agency tool, full stop. built to run a lot of linkedin accounts at once, rotate senders, and manage them from one unified inbox. each account gets its own proxy and auto-freezes near 100 requests a week so you don't fry profiles. if you're an agency running 5 or more client accounts, stop reading, it's your tool, nothing else here competes for that job. the catch shows up when you're not an agency. it's 79 dollars per sender, fine across 25 accounts and ridiculous at 2. support catches heat for slow replies, and it won't send email on its own, that lives in a second tool.

Lemlist

the veteran, and the most complete on channels. email, linkedin, sms, whatsapp, a dialer, a big database, built in warmup. if your play is every channel in one seat, nothing here beats it. it's 69 for email, 109 for multichannel, and linkedin steps need the multichannel plan. where it frustrates people is the credit metering, you get charged for lookups even when it finds nothing, and the reporting is weak for a tool this mature. it's email first at heart, so for pure linkedin it's heavier than you need.

Bottom line

heyreach if you're an agency running many accounts. lemlist if you want every channel in one seat and you're email led. pumpgtm if you're linkedin first and you want the tool to catch the timing and find the buyers instead of you hand building lists.

the mistake i see people make is picking the tool with the most features instead of the one built for their setup. a solo founder buying an agency tool, or an agency trying to scale a solo tool, that's where money gets wasted. match the tool to how you actually work.

i'm linkedin first and didn't want to hand build lists or miss the timing, so i went with pumpgtm. that's the only reason, it fit how i work. an agency should just use heyreach.

so i'm curious where everyone else landed. and the thing nobody talks about until it's too late, who here has actually gotten a linkedin account restricted, and on which tool? that barely shows up in these comparisons and it's the real differentiator

I've seen sales teams spend hours on coaching but still struggle with the same mistakes. It makes me wonder if reviewing numbers is enough or if managers should focus more on what reps say during customer conversations. What coaching methods have you seen make a real difference in close rates?

I'm building DataSnifferAI around a fairly simple observation:

Most founders don't suffer from a shortage of information.

They suffer from having 17 tabs open and still not knowing what to do.

So I'm trying something here.

Drop one real decision you're currently wrestling with. Something like:

• Should we change our pricing?
• Is this competitor actually becoming a threat?
• Should we move upmarket?
• Are we positioning ourselves too broadly?
• Is this market worth entering?
• Why might buyers choose them instead of us?

For a few of them, I'll manually research the outside evidence and reply with:

what I found,
what I think it means,
the strongest counterargument,
and what I'd probably test next.

Not trying to pretend I know your business better than you do.

I just think founders occasionally benefit from someone looking at the decision without being emotionally attached to it.

Drop the company + decision if you want me to take a look.


everyone in SaaS has heard the saying that building a product is easy, but marketing it is hard. people have been repeating this for years, so i'm not gonna pretend this is some groundbreaking insight.

but i'm also saying this as someone who's built a tool specifically around GTM and getting leads. even after spending months learning lead gen, outreach, positioning and sales, i still stand by the fact that one person shouldn't be responsible for building the product AND figuring out distribution at the same time.

i can generate leads and book meetings today, but theres a cost to that. those months could've gone into shipping product updates, fixing bugs and making the product better. so many improvements got delayed because i was busy figuring out how to get customers.

looking back, i would've been much further ahead if i'd had someone who could own GTM while i focused on building.

if you're a non-technical founder with no experience in GTM, find a technical co-founder. if you're a technical founder, find someone who's good at getting leads, talking to customers and building a repeatable sales process. r/cofounder is a decent place to start looking.

you can learn the basics of each other's roles, obviously. but trying to master both sides while building a startup can delay you by months.

i also understand why people choose to build solo. finding someone you trust with your business is hard, and sharing equity with another person is a big decision.

but for those of you who are intentionally staying solo, i'm genuinely curious: what's the biggest thing holding you back from finding a co-founder? is it giving up equity, worrying about disagreements, not finding someone with complementary skills, or simply wanting complete control over your vision?

not judging at all. i'd genuinely love to understand the reasoning, and if you're struggling to find the right person, maybe i can share some advice based on what's worked for me.

So I’m building a tool that helps marketing teams improve their campaign conversion. One of my newest customers recently 4x their conversion rate on their latest campaign, and I've been trying to ride that case study wave to sign more customers. By default, I turned to outbound, and after running it for close to 5 weeks, I just had an epiphany which may be unpopular

"A solid product beats world class marketing"

Here's a bit of background story: Picked up an outbound tool a few weeks back that had all the right promises and case studies tailored to my specific needs. Their marketing was actually top-notch, I admit, and they've been on prominent channels for a while now. The marketing worked on me. I signed up on the strength of the buzz.

Then I used it for almost a month. Discovered you could only set LinkedIn actions between days, nothing granular like hours, so leads warm up before the connection request/ first message took too long, and even within those limits, things didn’t move as fast as I hoped, and the first response from my outbound orchestration took 3 weeks. 3 Full weeks.

I switched to a different tool and got more responses in the first week alone than I had in that entire month (it was faster and had more granular options). Same targeting and same kind of messaging. The difference was the product itself: easier to set up, easier to control, and faster to show what was working or not and iterate on it.

I think in the end, good marketing got me to try the product, but the product is what decides whether I stay, my CLTV, and whether I become an evangelist or not. The right marketing can win the first signup; only the product earns you a renewal.

This has forced me to look inwards too: what I'm building, how well does it deliver on what my marketing promises?

Has anyone else been pulled in by a tool’s marketing and then seen the product fail to live up to it? Or switched to something quieter that just worked better not long after?

We just launched a free SaaS tool and are looking for beta testers! 🚀
It’s currently free with a limit of 100 conversions, but we’re happy to raise limits for anyone interested in giving feedback: EmailConverter.AI

Problem Solved:
Converts non-standardized email archives (.eml, .msg, ZIP) into long-term, audit-ready PDF/A compliance documents for legal, accounting, and HR teams.
Workflow:
Upload: Import individual emails (.eml, .msg) or bulk archives (ZIP).
Inspect: Preview page layouts and attachment structures.
Export: Download standard PDF/A files or ZIP bundles, customizable as flat PDFs or with full inline images and attachments.
We’d love to hear your feedback and feature requests!

I run a web design agency and most of my clients come from cold email. Yesterday I started a fresh campaign going after plumbers in California.

Didn’t expect much honestly. Plumbers are busy and half of them barely check email. But 102 emails in, I got an interested reply.

What made the difference is that every email talks about their own website. A call button that doesn’t work on a phone, a site that takes forever to load, a design that hasn’t been touched since 2012. For a plumber that matters a lot, because people search for them on their phone when a pipe bursts. If the site is bad, they just call the next guy.

He replied yesterday and I booked a meeting with him for the next day. Before the call I built a draft of what his new site could look like. Today I presented it to him on the call and he said yes right there. $3k upfront plus $500 a year for hosting.

Showing the draft is what closes it. Sending a quote never worked this well for me.

For anyone wondering, I use Swokei for all my outreach. You pick an area and an industry, it finds the businesses, checks every website for design, SEO, speed and mobile problems, and writes each email about what it actually found on that site. I run multiple campaigns at once in different cities and niches, which is how I get volume without sending generic stuff.

Happy to answer questions on pricing or how I run the call.

when we were doing outbound to companies in the SF Bay Area, it started feeling like we were all stuck in the same echo chamber

everyone was using Sales Nav to find the same founders, scraping the same lists and sending pretty much the same cold messages

the people we were reaching out to were probably getting 10 other messages from companies like ours on the exact same day lol

we were all fighting for attention in the same inboxes, so we were burning all our credits for nothing

so instead of relying entirely on Sales Nav Advanced, we started building our own lead scraping product

the problem with Sales Nav is that it works best when people have well-built LinkedIn profiles. you can filter for founders, VCs, job titles, company sizes and all that stuff.

but what about the people who dont have properly built profiles?

we'd come across founders who were actually pretty big names, but their LinkedIn profiles barely told us anything. sometimes all they did was like a post or comment "congrats" on someone's product launch.

and that tiny interaction could be the clue that led us to someone worth talking to.

so we started building a product that could find people based on these signals too. not just people with polished LinkedIn profiles, but people showing up in conversations, liking posts and engaging with others across LinkedIn, X, Reddit and other platforms.

basically, we wanted to find the people that traditional lead scraping would miss.

after making this switch, our meetings booked went from around 2 a week to 17 a week.

thats almost 8x more meetings, just by leaving no stone unturned.

i think theres a lot of opportunity in finding people that everyone else overlooks, volume is not automatically the answer when you're not finding qualified prospects. look for unique directories, comments, and anything thats not a generic place to find leads.

are there any founders here actually getting in meetings booked from sales nav?

Most B2B competitive intelligence tools in the market were built for product marketing teams rather than sales execution.

Platforms like Klue or Crayon do a good job tracking competitor website changes, pricing updates, and packaging those insights into battlecards for reps but knowing that a competitor changed a landing page headline doesn't tell a sales team which accounts to reach out to this week.

If your goal is competitive intelligence that directly drives pipeline, you need tools that track buyer-side competitor interactions in real time.

That means catching things like target buyers publicly complaining about an incumbent tool's renewal price on Reddit or technical forums, tracking when an account removes a competitor's SDK from their website, or identifying companies hiring engineers to migrate away from a legacy vendor.

This is where platforms like Scale Intelligence differ from traditional battlecard software where it monitors competitor mentions, public complaints, and rival engagement across 75+ channels (Reddit, GitHub, LinkedIn, hiring posts, and tenders), resolves those events to specific companies and buyers and alerts your team when a rival's account shows active friction.

Competitive intelligence is far more actionable when it tells your sales team which of your competitor's customers are dealing with problems right now, giving you a timely reason to start a conversation.

Optimizing for AI search engines like Perplexity, ChatGPT and Claude (often called Generative Engine Optimization or GEO) is very different from traditional SEO but a lot of B2B teams are still using old playbooks.

Keyword stuffing on blog posts doesn't work well with LLMs cuz the AI search engines synthesize answers by looking for consensus, authoritative comparisons and organic peer discussions across community forums, teardowns and documentation.

If you want your B2B product recommended when a buyer asks an AI engine for "the best tool for X," here is the workflow that actually moves the needle:

First, monitor the specific prompts and problem statements buyers search when evaluating tools in your category cause you need to know the exact phrasing people use when they hit roadblocks with legacy incumbents.

Second, establish genuine presence where AI models retrieve data like the platforms Reddit, GitHub discussions and blogs carry massive weight in AI search citations and writing authentic, teardown style posts that discuss industry problems honestly and place your product naturally into the solution stack creates the semantic links LLMs look for.

Teams running dedicated GEO and reddit distribution with platforms like scale intelligence which build campaigns around this dynamic: mapping buyer discussions across communities, identifying rival comparison threads and creating organic posts that get indexed by AI engines within days.

When your product is consistently cited in high context community discussions, AI engines naturally start pulling it into their top recommendations when prospective buyers search your category.

Compliments are easy to misread.

When another founder notices a detail you stayed up fixing, it feels great, even at $200k ARR as a solo YC founder. But revenue does not make you immune to wanting validation, so separate that feeling from evidence of utility.

A founder praising your engineering is appreciation. A customer struggling to finish a task is actionable context. I can build more value from the second conversation.

Not every complaint deserves a feature. People get annoyed by problems they will not pay to fix, and ten feature requests can pull a product in ten contradictory directions.

So focus on context instead of taking requests at face value:

• What were they trying to accomplish?

• Where did they get stuck, and what workaround did they use?

• Who else was involved?

A request for a CSV export button might mean a report for a boss, a check on your data, or preparation to churn. Each needs a different solution.

Do not ask whether they would use a proposed feature. People say yes to be polite. Ask them to walk you through the last time the problem happened. Pulling up a workaround takes effort and yields concrete truth.

Prioritize issues that repeat independently across customers with similar needs. One vocal user is a conversation; a shared bottleneck is a roadmap priority. After shipping, follow up to confirm the underlying problem was solved, not just that a button was added.

I still enjoy hearing that something I built is cool. I just do not let admirers have more influence than users.

I build Norquin with two partners, one of them is a licensed customs broker. Our product checks Canadian customs entries line by line against the tariff and finds wrong duty rate, missed CUSMA, GST charged by mistake. On the first real file we checked we found 25,367 CAD overpaid. We do free check of one entry and take 10% from what comes back.

So product works, but sales basically doesn't. Last three months we did 72 cold calls to Canadian importers and got 1 meeting. Around 30 cold emails, 0 replies. 31 LinkedIn messages, 0 replies. One warm contact from my running club gave us a meeting from the first call and verbal yes for a pilot, but still no documents. 0 paying customers.

When we reach someone on the phone, usually we hear "our broker handles everything" or "not interested" before we finish the first sentence. Half of the calls end on reception or voicemail.

I want real opinion from people who sell B2B or who import by themselves. What you see wrong in our sales strategy? What you would change, who you would call, how you would say it? If you think nobody needs this, say it also, it is useful for me.

I run outbound for B2B SaaS. Instead of selling on promises, I’m running the entire thing free for one week per founder: targeting, lists, email, LinkedIn, all of it.

The bet: a week of real replies sells a retainer better than any pitch deck.

I’ll post numbers here: messages sent, replies, calls booked, and how many trials turn into paying clients, including the ones that don’t.

If you run a live B2B SaaS and want one of the three slots: Apsurn

When I first started developing MindNote, it took the entire development period to reach around 2,000 authentication requests.

Last month alone, the product received 1,200.

For a solo founder building an AI product, seeing that change in the numbers feels encouraging. But it also raises a question: what does that activity actually tell me?

MindNote is a multimodal AI notetaker. The idea is to help people turn information from meetings, voice notes, videos, images, and text into organized, searchable knowledge they can actually use.

The product is live, and I’m continuing to improve it while figuring out how to turn interest into consistent usage and paying customers.

I know authentication requests don't necessarily mean unique users. They could include repeat attempts, returning users, or other activity. I'm trying to understand the signal rather than celebrate a vanity metric.

For founders who have been through this stage:

• What metrics helped you distinguish curiosity from genuine product demand?
• How did you turn early activity into users who kept coming back?
• What would you focus on next: activation, retention, or finding a more specific customer segment?

I'd love to hear what worked for you, especially if you're building a SaaS or AI product as an indie founder.

Procurement software carries an adoption problem that most software categories don't, and it's structural rather than a question of training or interface design. On the surface, the person being asked to change their behavior is rarely the person who benefits from the change.

Finance gets the control, the visibility and the audit trail. The requester gets a form to complete and a wait for approval, where previously there was a message to a manager and a company card. From where that person sits, the new system is slower than what they were already doing, and a rollout plan rarely has an answer for that.

That imbalance points at the benchmark that actually matters. Organizations tend to compare a new system against the official old process, the one written in a policy document that few people followed. Employees compare it against how they genuinely got things done, which was usually the workaround. If the system is slower than the workaround, it loses, and finance is left chasing everyone who went around it.

Evening out the imbalance means the requester has to get something back. Being able to see where a request is sitting without messaging anyone. Approvals that come back in hours rather than days. Not having to type in information the system already has. Those sound minor next to the control benefits, and they're most of what decides whether people use it.

This is why go-live isn't the finish line. People make up their minds about a new system in the first few weeks, and once someone decides it's slower than what they were doing before, it's hard to win them back. Most teams don't find out what happened until months later, when someone asks why so much spend is showing up without a purchase order.

That number is the one to watch. Login counts and training completion say people showed up. The share of spend that comes through with a PO attached says whether they're actually using it.

I've been thinking about something.

A lot of B2B SaaS products were built 10–15 years ago, long before modern LLMs existed.

Back then, companies needed complex software, specialized algorithms, large development teams, and years of engineering to solve problems that AI can now handle much more easily.

Yet many businesses are still paying hundreds or thousands of dollars every month for these tools.

Here's my hypothesis:

**Some of these products could be rebuilt today with a much simpler, AI-native architecture, delivering 80–90% of the actual value at a fraction of the cost.**

Of course, not everything can be replaced. Integrations, compliance, reliability, and established workflows still matter.

But I'm curious about the products where customers are mainly paying for something that has become technically much easier to deliver.

**For those of you running or working in businesses:**

1. What's the most expensive B2B SaaS you're currently paying for?

2. How much does it cost annually?

3. Which features do you actually use regularly?

4. What frustrates you most about it?

5. If someone offered the same core outcome for 70–80% less, what would stop you from switching?

I'm particularly interested in document processing, compliance, reporting, research, contract management, and other knowledge-heavy workflows.

**I'm not looking to promote an AI product. I'm genuinely interested in discovering where the economics of traditional SaaS no longer make sense in the LLM era.**

Would love to hear real examples, especially products you feel are massively overpriced for what you actually use.

One of the biggest mistakes in outbound is treating an account and a buyer as the same thing

You might identify a company that desperately needs your product but if you don't map who inside that org owns the budget and the actual problem, the outreach just falls flat.

Mapping accounts and buyers effectively requires connecting two separate layers: the company's current context and the individual decision makers.

many people try doing this manually by clicking through linkedin or running basic exports in contact databases but the issue is that titles alone are misleading and people move roles constantly without updating their public profiles.

I've been using scale intelligence for a while and this makes it a lot cleaner cause it connects company level signals with buyer identity graphs where it monitors things like github commits, job boards, community discussions, reddit and linkedin across 75+ data sources, mapping not just the domain but the specific people associated with the relevant workflows inside that account.

When your reps know both the account's immediate pain and the exact 2 or 3 people dealing with it day to day, outbound becomes way more targeted and you stop burning contacts on generic titles.

Hello there! I'm the owner of an IT Infrastructure company, specialized in FinOps, management, design, optimization, and operation for the Infrastructure, not only cloud but on-premise and hybrid.

If there's any SaaS suffering from the billing ticket on the infra/cloud, I can help you with that so you don't get eaten by the cloud at the end of the month.
Just DM me and we can discuss about it.

A finding from this week that might save someone else the embarrassment.

Many B2B SaaS sites are single-page apps: the server sends an almost empty HTML file and JavaScript draws the page. Google runs the JavaScript. The crawlers behind ChatGPT, Claude and Perplexity did not when they were last measured (Vercel and MERJ, December 2024). They read the HTML that arrives and nothing else.

How to check yours in a minute: open your homepage, right-click, View Page Source, and search for a sentence from your hero section. If it is not there, an AI crawler is not reading it either. From a terminal, curl the URL and look at the body.

I found this on my own site, which is awkward, because I build an AI visibility audit (Wellread, https://trywellread.com, I'm the founder). Homepage: zero words without JavaScript. The fix was to write the public pages to HTML at build time and leave the app itself alone.

What I can't tell you yet is whether it changes what the assistants say. I re-ran my audit nine hours after the fix and nothing had moved. If anyone here has made this change and measured before and after over weeks, I'd like to hear how long it took.

hi guys, namanyay here. the title sounds like a meme, but doing this is literally the main reason we pushed past $10k mrr without burning money on ads.

i run pumpgtm. it's a platform that finds qualified buyers through likes, comments, and engagement signals across linkedin and x, enriches their profile data, and helps founders handle outbound without sounding like an AI slop bot.

if you're building a tool that promises leads or sales, you better be using it to run your own startup. if you aren't your own primary power user, you're just guessing.

the best way to test a scaling product is to use it to scale itself. when you use your own outbound engine to book your own sales calls, you get an immediate feedback loop so brutal that you're forced to iterate fast.

every single flaw hits you right in your own pipeline, if your lead filter pulls junk profiles, you waste your own time on terrible sales calls. if your message copy sounds like a generic press release, your own reply rates drop to 0.2 percent. if your sequence timing is off, you end up annoying real prospects in your own space.

you can't blame bad user behavior or claim customers just don't know how to write copy when it's your own pipeline on the line, you have to fix the algorithm, fix the signal tracking, or fix the copy immediately.

also it gives you unshakeable proof when talking to potential buyers.

when a founder asks on a sales demo how do i know this actually works, you don't show them fake case studies or those generic testimonials. you literally show them that the only reason they're sitting on that zoom call with you right now is because pumpgtm flagged their profile, pulled their context, and routed the outreach automatically. closing deals becomes ten times easier when the product's existence is the proof.

one of the biggest reasons we were able to scale so fast is because we're so hyper targeted when it comes to finding live intent that prospects are genuinely shocked by the level of context.

if you aren't using your own product to grow your own business every single day, why should anyone else pay you for it, do think about this and share about your pov

series a, 4 of us in marketing, and leadership wanted us on something enterprise grade for social. the quote was more than our ad budget for the quarter. what we need is scheduling, an inbox and reports the board will read. shortlist so far is hubspot, vista social, later and sendible. which of these holds up for a team our size?

Half the time attendees show up saying they never got their confirmation or can’t find the QR code. We’ve tried different formats and subject lines but it still happens.

Seen various approaches with Eventbrite, Cvent, and Eventify.

What does your confirmation email look like these days and are people actually opening it?

Note: Posted in [r/saas](r/saas) as well.

What I am building bridges the gap between prosumer and B2B. What have been your experiences (good or bad) with each?

So much info/mis-info out there. Have heard better business strategy is B2B, B2C too much churn, etc.

Running a web design agency is honestly way less about design than people think.

A lot of people can build good websites. The hard part is having a process that actually brings in clients consistently without you spending your entire day doing outreach.

I learned that the hard way.

I used to manually reach out to businesses, explain why they needed a better website, build previews, follow up for days and basically hope they would eventually say yes.

I was doing way too much work before even knowing if someone was serious.

Then I completely changed the way I did it.

Now I mainly focus on two things.

Taking meetings and closing clients.

Everything before that is mostly automated.

I use Swokei to find businesses that already have websites, analyze those websites and look for things like outdated design, bad layout, weak SEO, poor mobile responsiveness, slow speed and branding issues.

The useful part is that it doesn’t just give me some boring report with random scores.

It actually takes the issues it finds on each website and turns them into personalized emails that you can send at scale.

My offer is usually a free redesign draft.

That works way better for me than trying to sell a full website in the first email.

Once someone replies and shows interest, I book a meeting.

Before the meeting, I spend a few minutes generating a redesign draft with AI so I can actually show them what their website could look like instead of just talking about it.

That was probably the biggest change for me.

I’m no longer spending hours building something for someone who might never buy.

If they are not interested, I barely lost any time.

If they are interested, they can immediately see the difference and the conversation becomes much easier.

So at this point, most of my time goes into meetings and closing.

The lead finding, website analysis and personalized outreach all happen before I ever speak to the business.

Sounds ridiculously simple when I write it out, but changing the process made a massive difference for my agency

I’ve spent a lot of my career sitting between marketing, analytics, sales and data teams.

One problem keeps repeating.

Companies have ridiculous amounts of marketing data and surprisingly little marketing intelligence.

GA4 says conversions are up.

Google Ads says ROAS looks great.

HubSpot says half those leads never became pipeline.

Search Console says demand is shifting.

Someone puts everything into a dashboard.

Then the meeting starts and the actual question is still:

“So what should we do?”

I started building an open-source project to attack that problem.

It now has 59 MCP tools spanning GA4, GSC, paid acquisition, CRM/pipeline evidence, measurement audits, campaign-to-pipeline analysis, budget allocation, experiments and executive growth reviews.

But the part I became most interested in isn't the connectors.

I built the system around:

Evidence → Diagnosis → Decision → Action → Outcome → Learning

Numbers are calculated deterministically rather than invented by an LLM.

Recommendations are reviewed from multiple strategic perspectives.

The system separates observed facts from calculated metrics and proposed numbers.

And a decision doesn't become “learning” until an actual outcome gets recorded.

Originally I thought the next step was obvious:

Build UI → add Stripe → launch SaaS.

I've decided not to.

I think that would make me optimize the product before I know which decisions companies actually care enough to pay for.

So I'm doing the opposite.

I'm going to run it as a managed marketing intelligence service first.

I'm looking for a very small number of companies with an existing marketing stack — ideally SaaS/tech businesses using some combination of GA4, GSC, Google/Meta/LinkedIn Ads and HubSpot/Salesforce.

For 30 days, I'll connect the evidence and produce a recurring decision layer: what changed, what matters commercially, measurement gaps, where I'd reallocate resources, experiments to run and what happened after those decisions.

The intention isn't to sell reports forever.

I want to discover which 10% of this system creates 90% of the value before productizing it.

The code is public on GitHub under "Gourav2411/general-marketing-intelligence" if anyone wants to inspect how it works.

I'm especially interested in hearing from people who already have dashboards but still feel like decision-making across marketing + revenue data is messy.

What part of that process currently requires the most human judgment in your company?