u/No_Wish5780

Running LinkedIn as my main prospecting channel for a few months now. Pre-revenue, B2B, selling into software companies.

The pattern I keep hitting: people accept the connection request, then the follow up message goes nowhere. Not rejected, just never opened, or opened and left. I get replies, and the ones I get are good conversations. But the ratio feels rough and I cannot tell if it is rough because I am doing something wrong or because this is just what the channel looks like.

Worth saying, the message is not a pitch. I do not lead with the product. It is usually something specific about what they have built or something they posted. I keep it short and I do not ask for a call in the first message.

What I am trying to work out:

Is a low reply rate on first message normal even when the connection was accepted, or does accepting usually signal enough intent that a good message should convert better than I am seeing.

Did anything change your numbers meaningfully. Timing, length, following up versus not, warming up through comments for a few weeks first.

How long did it take before LinkedIn actually produced pipeline for you rather than just conversations. I am trying to figure out whether I am early in a slow channel or wasting effort in the wrong one.

For anyone who eventually gave up on it, what did you move to.

Happy to share what has worked on my side too. The one thing I am fairly sure about is that a comment on someone's post before the DM changes the response, but my sample is too small to trust that yet.

Building an AI layer that sits on top of existing enterprise systems. You ask a question in plain language, it queries your actual data and answers. Pre revenue, live with one deployment.

First approach was selling direct to businesses. That went nowhere and the reason was obvious afterward. Every one of them already runs an ERP. They were not shopping for another tool, they wanted something that lived inside what they already had open all day.

So we flipped to selling through the ERP vendors instead. White label it, they own the customer relationship, we power the layer underneath.

That worked. A few said yes and each one came with a set of customers attached. Distribution we could not have built one account at a time.

Then we hit the actual wall.

Most of the ERP founders we pitch have not worked out where AI fits in their product yet. Not a chatbot in the sidebar, that part everyone gets. I mean the layer that changes what a business owner decides on a Tuesday morning. Some also do not have the data depth to support it yet, and some have no way to benchmark building it in house against just integrating something, so every internal estimate looks cheap by default.

The thing that gets me is where the value actually sits. It is clearest at the far end, with the small business owner who finally gets an answer without waiting three days for someone to pull a report. But the buying decision is two steps upstream with a founder who has not seen why it matters yet.

So the pitch has to travel further than the value does, and it loses energy on the way.

Not really a product problem at this point. Closer to a conviction problem, and those move on their own timeline.

Questions for anyone who has run channel:

Did you find something that shortened the conviction gap, or did it just take however long it took?

Did you end up building the demand at the end-user level and letting them pull the channel partner in? Wondering if that is smarter than convincing the partner cold.

For anyone who sells into other software companies, how do you handle the build-versus-integrate conversation when they have never priced their own build properly?

We're a small AI company. Built something that sits on top of business data and lets non-technical users query it in plain English insights, charts, predictions. Solid product, real users, working in production.

A larger company in a different but adjacent space wanted to embed our capability into their product under their branding. We said yes.

The deal structure:

• Fixed annual fee (covers roughly one engineer's time)
• Small % of revenue on their mass-market product
• Better % on their enterprise product
• They bear all infrastructure costs including AI model costs
• Scope defined, delivery in a few months
• Pricing strategy decided together

Here's where it gets interesting.

Their margin problem is real. The AI model costs alone eat a significant chunk of per-user revenue. So when they said "we can't give you more percentage," the P&L math actually backed them up. The enemy isn't them — it's the AI infrastructure cost sitting between us.

I took it because the unit economics still work on our side. No infra burden, first real enterprise reference, usage data we couldn't get otherwise, and a bigger commercial conversation already scoped for later.

But sitting here post-deal, the question is simple: we built the core product. They built the distribution. Is a small percentage of something always better than a large percentage of nothing? Or did I just set a precedent that'll be hard to walk back?

For people who've done embedded AI or white-label deals in B2B:

1. How do you think about percentage vs fixed fee tradeoffs when you're the smaller, technical party?
2. When the partner's margin problem is genuine, how do you protect your upside without killing the deal?
3. How do you prevent scope from expanding under the same commercial terms once you're embedded?
4. Does the reference customer argument actually hold or is it just something founders tell themselves?

Honest answers only. I've already signed. Just want to know what I should be watching for.