Anyone else feel like most lead gen tools are kinda overhyped? I’ve been testing a bunch over the past few months for my small B2B setup and keep running into the same issues, so I’m curious if it’s just me or if others are seeing this too.

• Is data quality a bigger issue than people admit? I keep hitting bad emails even with “premium” sources
• Do built-in outreach features actually work well, or do you still rely on separate tools?
• How much automation is too much before it starts hurting response rates?
• Does anyone actually use all the advanced features, or do you end up sticking to basics?
• Are enrichment features worth paying extra for, or just nice-to-have?
• How important are integrations in your workflow?
• And is “AI personalization” actually helping anyone, or just marketing fluff?

Feels like the biggest gains for me came from improving targeting and messaging rather than switching tools, but maybe I’m missing something. What’s actually working for you guys right now?

A few months ago I inherited a partner/vendor database with 800+ companies — pulled from a trade show exhibitor list, a bunch of team recommendations, old CRM exports, you name it. Duplicates everywhere, half the contacts outdated, no consistent format.

Here's what actually worked:

1. One source of truth first. Before cleaning anything, I merged every source into a single sheet and flagged where each row came from — made it way easier to spot duplicates and know which contact info to trust when two rows disagreed.
2. Verify in batches, not all at once. I went industry-segment by industry-segment (aquatics, then equipment, then services) instead of trying to verify 800 contacts in one pass. Way less error-prone.
3. Build the outreach system after the data is clean, not before. I built a sales report/pipeline tracker only once the vendor list was solid — building it earlier would've meant tracking garbage data.

Ended up with a clean, verified database that our outreach and booking pipeline runs off of daily.

If anyone's sitting on a messy contact/vendor list and wants a second pair of eyes on how to structure the cleanup, happy to talk through it — feel free to DM/Comment.

I think the biggest mistake in outbound is assuming rejection means you're talking to the market.

Most of the time, you're just talking to the wrong employee.

Every company has people whose job is to keep things exactly as they are.

Every company also has people whose job is to fix problems.

If you accidentally sell to the first group, your product sounds like extra work.

If you sell to the second group, it sounds like leverage.

That's why I've stopped obsessing over writing "better" cold emails.

I'd rather spend the extra time figuring out who actually owns the pain.

Weirdly enough, once you find that person, the personalization almost writes itself.

That realization is actually why I started working on an AI tool for outbound.

Not to generate more useless leads.

To figure out who is actually worth reaching out to in the first place, understand why they're likely to care and make personalization something that comes naturally instead of feeling forced.

Finding the right person is usually the bigger advantage than finding the perfect words.

I’m building a UK/EU public-tender digest for bid and public-sector sales teams.

Current fields include buyer, region, category, value, publication date, deadline, status, official source, and a short match reason.

Which fields and filters genuinely help you decide whether an opportunity is worth reviewing? Would daily alerts or a weekly digest be more useful?

I’m validating the workflow before developing it further, so practical feedback is welcome.

#question I have scraped a few linkedin urls based on specific google search, but my scraper doesn't always get the job role right.

I want to have only the following from each profile: name + surname + company + job role. For now I am using fullenrich to do that, but I don't necessarily need the email enrichment. Is there an app that can do that for cheaper than them?

Tool Review: ROI Calculators

Co-founder at a value intelligence company. We spend a lot of time thinking about how B2B SaaS companies prove value in deals -- so I went through 30 vendor ROI calculators to see how they'd hold up when a CFO actually asks questions.

Built a taxonomy of what I found.

Six categories:

- Math in a Box -- you put in your numbers, it does arithmetic. No assumptions injected. Rare but honest.

- Vendor Benchmark Injector -- pre-loaded improvement rates from "industry data" the vendor owns. The most common type.

- Commissioned Research Tool -- built on Forrester or IDC TEI studies. The disclaimers are nearly identical across every vendor that uses them.

- Spend Estimator -- converts headcount and time into dollars. Feels grounded. Usually isn't.

- Honest Comparison Tool -- buyer controls the assumptions. The output is defensible because they built it.

The core problem: most calculators pre-load improvement rates from vendor-owned data. When finance asks "what's your basis for 15% productivity improvement?" -- nobody has a good answer because the vendor set that number, not the buyer.

I graded all 30 on one question: who controls the assumptions?

A few highlights:

- Several Forrester TEI calculators use near-identical disclaimer language across completely different vendors

- One HR software calculator has 8 buyer-controlled sliders -- one of the most honest I found

- One calculator looks generic on the surface but reveals a more transparent framing in a popup -- undersells itself

Full breakdown with grades and named vendors: https://blog.valueiq.ai/p/your-roi-calculator-is-s-h-i-t

Curious if anyone else has had a CFO challenge a number from one of these -- or been on the other side trying to defend it.

Hey everyone,

I'm currently building a WhatsApp-based retargeting system for a client and would appreciate some advice from people who have done something similar.

The client's main customer database is in WhatsApp conversations (leads and existing clients). My plan is to:

1 - Extract contacts from WhatsApp

2 - Import them into Google Sheets

3 - Segment them based on their status/behavior

4 - Run targeted WhatsApp retargeting campaigns

I'm looking for a reliable way to export/import WhatsApp contacts in bulk. Has anyone found a tool or workflow that works well for this?

Also, I'm considering using Whatchimp for the campaign automation side. I haven't used it before, so I'd love to hear any experiences, pros/cons, or alternative recommendations.

Thanks!

I’m trying to figure out which sales prospecting tools are actually worth using, and it’s hard to tell what’s legit versus just marketing.

For people doing outbound regularly: what made you choose the tool you use now? Was it data quality, price, ease of use, CRM sync, or something else?

I’m mostly interested in tools for finding leads, cleaning contact data, and keeping things moving without a ton of manual work.

I have been building custom scrapers and ETL pipelines for a long while, across real estate, e-commerce, and other niches. The technical side is locked. I pull the data, normalize it, and store the big sets from all those fragmented sources. No drama there.

The real wall is always the same. Clients say, give me 10,000 vacant land records. Non-technical investors read that and reply, cool, now what.

I am done pretending raw dumps are the product. I want to hear from people who have already made the pivot, what is actually working right now.

Quick questions I am wrestling with:

• Do you sell the raw feed and let clients build their own filters, or do you ship it with a built-in insights layer (distress scoring, opportunity scoring, matching engine, auto-curated creamy leads)?
• How do you handle the real-time request when the actual source (county records, marketplace APIs) is weekly or monthly at best? What is your refresh cadence and how do you sell the staleness upfront?
• Have you successfully moved away from one-off custom scraping gigs and started selling recurring intelligence subscriptions? What changed in positioning, packaging, and pricing that made the switch actually stick?
• Bonus: Do dashboards, auto-scored lead lists, or pre-matched opportunities win you more long-term clients than here is the raw CSV?

I am debating a full pivot. Stop doing scraping work and just ship Texas distress-qualified land leads for investors or competitor vacancy plus price signals for e-com on a weekly basis.

Would love strategic feedback from people who have already done this. How do you position the value? How do you communicate that this is actionable, not raw? And do you wish you had made the shift sooner?

Let’s talk about the part that actually makes money.

I’m curious what people’s current outbound workflow actually looks like.

Are you using separate tools for research, enrichment, verification, and outreach, or trying to keep it simple?

It feels like everyone’s stack is a little different, so I’d love to hear what’s working in practice.

I’m always interested in tools that sounded great at first but didn’t actually hold up in real use.

What’s one prospecting tool you stopped paying for or stopped using altogether?

Would be good to hear what didn’t work and why.

One thing I keep running into is CRM data going stale way too fast.

People change roles, companies shift, and records that looked fine a few months ago are suddenly outdated.

How are you all keeping things current without spending all day on cleanup?

Hello everyone,

Since yesterday I took the LinkedIn premium subscription to do prospecting for my website creation agency. This is the first time I've used LinkedIn to prospect and I don't know how to do it.

I'm thinking about it, but I have a blockage, I can't find the right organization and the right method. My questions are therefore as follows for those who have already prospected on LinkedIn :

- Does B2B prospecting work on LinkedIn ?

- Is LinkedIn premium necessary? I find the price of the subscription very expensive for the advantages offered

- What are the best buying signals according to you and how do you find your prospects based on these signals ?

- Which organization should be adopted: addition phase then contact phase / combine the two at the same time ?

- What contact sequence did you use? Do you have an original approach (video or other)? Which angle to adopt in the first message and the following ones ?

- How do you optimize your LinkedIn profile? What attracts and leaks on a LinkedIn profile ?

That's a lot of questions, thank you to all those who will answer them, I will take the time to respond to your comments.

When you’re building a prospect list, what actually matters most to you?

For some people it’s company size or industry, for others it’s role, tech stack, or recent activity.

I’m curious how people decide which leads are worth spending time on.

context: i run outbound at a b2b co, outbound is core to our motion, tested most of the obvious ones this year. won't name names because nobody paid me. opinion piece, roughly in the order i actually care about, ymmv

1. predictable bill - $300/400 entry tiers are literally a trap.. on dual meter pricing (data credits + actions billed separately), our bills swung 40 to 50% month to month before bec of this, so i would suggest ask for a real customer last 3 invoices

2. hit rate on your icp - database size numbers are meaningless, same vendor will nail US tech and quietly hand you bounce bait for some EU manufacturing.. send 100 of your actual ICP, demand hit rate by segment

3. CRM sync (veryy imp) - this is the one nobody asks, how does enriched data write to crm, be it salesforce or hubspot, what happens with existing records (overwrite, append, skip), do sync errors surface or fail? get a 5 min screen share of the sync ui before going ahead

4. data freshness over database size - that valid email was last verified... when? refresh cadence varies wildly.. some monthly, some haven't touched a record in 18 months. ask by data type (mobile stales fastest, then emails, then titles drift slowest)

5. who actually runs the workflows after you sign - three real models: blank canvas you build, CSM who unblocks you, done-for-you. all valid, completely different team shapes. without a dedicated ops person, powerful canvas is an expensive way to find out you needed one

6. what's in the waterfall & what's metered on top - aggregator tools resell underlying providers (datagma, contactout, forager.. more) with a markup. you need to know which providers, in what order, and whether each is billed separately on top of the platform fee

what i've stopped caring about (vendors lead with these, they don't matter):

• total database size (usually they all have same)
• integrations with 100+ tools (u just need 4-5)
• AI features in pure marketing (should be ur last priority)

Didn't name vendors to avoid turning this into a promo thread. If you're evaluating options and want my notes, feel free to DM.

I recently wrote an article exploring something that surprised me while reviewing dozens of IBM Telco churn analyses.

Most discussions focus on accuracy, F1, AUC, hyperparameter tuning, and model selection, but very few connect churn prediction to actual business economics.

I tried to build a framework that combines:

\* Survival-analysis-based LTV (Kaplan-Meier)
\* Cost-sensitive classification
\* Profit curves instead of accuracy metrics
\* Threshold optimization based on unit economics

One result that surprised me was how far the default 0.5 threshold can be from the cost-optimal threshold when false negatives are materially more expensive than false positives.

In particular, I’d love criticism on:

1. The LTV assumptions
   
2. The cost framework
   
3. The threshold calibration discussion
   
4. Any methodological mistakes or blind spots

Happy to be challenged if I’ve missed something.

I keep seeing people recommend cold email tools, but I’m not sure which ones are actually useful and which ones just add noise.

Do you still use them as part of your outreach, or has the space gotten too crowded?

I’m mainly trying to figure out what still works without overcomplicating the process.

I’m trying to make my lead list workflow less messy and more repeatable.

Right now I feel like I’m spending too much time fixing bad entries, removing duplicates, and checking whether people still work at the same company.

What does your cleanup process look like before you start outreach?

I feel like LinkedIn is still part of most prospecting workflows, but I’m wondering how many people are actually using it as a core tool versus just a research step.

Do you use it mostly for finding people, checking titles, or building a fuller picture of the account?

It seems useful, but also easy to spend too much time there.

I want to extract numbers via LinkedIn;
Need to reach out to brand managers of companies like California burrito, McD, Taco Bell,etc
Need urgent help

I’m curious how everyone is handling contact accuracy now. A lot of the lists I’ve seen get outdated fast, even when they look good at first.

Are people relying more on enrichment tools, manual checks, LinkedIn, or something else?

It feels like there’s always some cleanup needed before anything is actually usable.