If you’re running a B2B sales pipeline, you already know there’s no magic bullet—just a series of steps where deals can (and do) fall apart. Maybe leads vanish after a demo, or proposals collect dust. If you’re tired of hand-waving and want to actually fix these leaks, this guide is for you. I’ll show you how to use Unless analytics to spot exactly where deals drop off, make real improvements, and avoid the usual “just try harder” advice you see everywhere.
Let’s get into it.
Why B2B Pipelines Leak (And Why You Need Real Analytics)
Every B2B pipeline leaks. That’s normal. But when you can’t tell where or why, you’re flying blind. Sales teams guess, marketing blames sales, and everyone’s frustrated.
Here’s what actually helps:
- Knowing where in your pipeline leads disappear.
- Understanding why—not just how many.
- Making small, testable changes and seeing if they work.
Unless analytics isn’t magic, but it does give you a clear view of your pipeline so you can stop guessing and start fixing.
Step 1: Map Your Actual Pipeline—Not the Fantasy Version
Before you even touch analytics, get honest about your pipeline stages. Forget the ideal flow. Write down what actually happens, warts and all.
Typical B2B pipeline stages:
- Lead captured (form fill, inbound, etc.)
- Qualification (call, survey, whatever)
- Demo or discovery call
- Proposal or quote sent
- Negotiation
- Closed (won or lost)
Pro tip: If you can’t describe what happens at each stage in plain English, neither can your analytics platform.
Step 2: Set Up Unless Analytics to Mirror Your Pipeline
Unless analytics can track just about anything, but garbage in, garbage out. Set it up to follow your actual process, not the textbook one.
How to do it:
- Define key conversion events. For each pipeline stage, set up an event (e.g., “Demo booked”, “Proposal sent”, “Contract signed”).
- Integrate with your tools. Unless can connect with CRMs, web forms, calendar tools, and email platforms. Don’t skimp on this—if you skip steps, your data will be full of holes.
- Tag your traffic sources. Know if leads come from paid, organic, referrals, or outbound. This is easy to overlook and hard to backfill later.
What to ignore: Fancy dashboards that track vanity metrics (like “engagement score” or “views per page”) don’t help you fix drop offs. Stick to clear, pipeline-specific events.
Step 3: Find the Actual Drop Offs—Not Just the Big Numbers
Once data’s flowing, the real work starts. Unless will show you conversion rates between stages. But don’t just look at the totals—dig into where the biggest leaks are.
Look for:
- Stages with unexpected drop offs. Maybe 80% show up to demos, but only 10% get a proposal. That’s your problem area.
- Drop offs by source. Are outbound leads dropping off earlier than inbound? Maybe your outreach is too aggressive, or your landing page is off.
- Time to next step. If people linger too long in one stage, that’s often a silent killer.
Pro tip: Don’t panic about drop offs—every pipeline has them. Just focus on the biggest leaks first.
Step 4: Dig Into the “Why”—Not Just the “What”
Numbers tell you where the leaks are, but not why. Unless can help, but you’ll need to do some digging:
- Session replays: Unless records how users interact with your site or forms. Watch a few real user journeys. Are they confused? Do they hesitate before a form? Are they bailing at a weird question?
- Field-level drop off: See which form fields cause people to quit. If “company size” is tripping everyone up, maybe it’s too early to ask.
- Segment by persona or company size: Maybe startups bail at the pricing page, but enterprises don’t.
What doesn’t work: Guessing. If you think you “know” why people drop off but haven’t seen it in the data, you’re probably making it up. Watch real sessions or ask users directly.
Step 5: Fix, Test, and Repeat—But Don’t Overthink It
Here’s where most teams get stuck: they see a drop off, brainstorm a dozen “fixes,” and try them all at once. Bad move. You’ll never know what worked.
Instead:
- Pick one change. Maybe rewrite a headline, remove a form field, or clarify next steps after a demo.
- Test it. Unless lets you track cohort conversion rates over time, so you can see if the change made a real difference.
- Wait for real data. Give it a week (or however long your sales cycle is) before judging.
- Rinse and repeat. Move on to the next bottleneck.
Pro tip: Small, boring changes often work better than big redesigns. Don’t let the “growth hack” hype distract you.
Step 6: Use Unless to Close the Loop with Sales and Marketing
Analytics isn’t just for the ops or marketing folks. Get sales involved early. Unless makes it pretty easy to share dashboards or even set up alerts.
- Regular pipeline reviews: Look at drop offs together. If sales says “marketing leads are garbage,” show the data. If marketing says “sales never follows up,” check the timestamps.
- Share wins and losses: When you fix a drop off, tell the team. When something doesn’t work, share that too. No shame in it—everyone’s guessing half the time anyway.
- Automate where it helps: Set up alerts for sudden changes (like demo bookings dropping by half). No one has time to check dashboards all day.
Honest Takes: What Works, What Doesn’t, and What to Ignore
What works:
- Clear, simple event tracking—don’t overcomplicate it.
- Watching a handful of real user journeys instead of just looking at charts.
- Fixing one thing at a time and measuring results.
What doesn’t:
- Tracking generic “engagement” without tying it to pipeline steps.
- Changing everything at once and hoping for the best.
- Overanalyzing edge cases—focus on the big, obvious leaks first.
What to ignore:
- Any tool or consultant promising “plug-and-play” pipeline fixes.
- Overly complex funnels with 10+ micro-stages.
- The idea that you can “optimize” your way out of a bad product or sales team.
Keep It Simple, Stay Skeptical, and Iterate
You don’t need a PhD or a 40-page dashboard to find and fix pipeline drop offs. Get clear on your actual process, track it with Unless, watch what real people do, and fix the stuff that’s obviously broken. Then do it again. Keep it boring, keep it real, and don’t fall for hype.
If you focus on real data and small changes, you’ll see results—no magic required.