If you’re in B2B sales, you know forecasting is a nightmare. Gut instinct and spreadsheets only get you so far, and half the sales tools out there promise AI magic but deliver more confusion than clarity. This guide is for busy sales leaders and ops folks who actually want to use predictive analytics to get real answers—without the hype. We’ll walk through how to use Mantiks to forecast your B2B sales opportunities, step by step, with a healthy dose of skepticism and practical tips.
Why Bother With Predictive Analytics?
Let’s get this out of the way: Predictive analytics won’t make you a fortune overnight. But if you’re drowning in deals, chasing the wrong leads, or getting blindsided at quarter’s end, it can help you make better calls—faster.
Here’s what it’s actually good for:
- Spotting which opportunities are likely to close (or stall)
- Prioritizing reps’ time on deals that matter
- Catching red flags early, before they tank your forecast
- Giving leadership a forecast that’s more than just wishful thinking
But don’t expect it to read minds or fix a broken sales process. It’s a tool, not a miracle.
Step 1: Get Your Data House in Order
Mantiks isn’t psychic. It needs good, clean data to make useful predictions. Garbage in, garbage out.
What you need:
- CRM data: Contacts, accounts, opportunity stages, close dates, deal sizes. The basics.
- Deal activity: Emails, calls, meetings, and notes. The stuff that shows real engagement.
- Outcome data: Which deals closed, which didn’t, and why (if known).
What trips people up:
- Messy or missing fields (e.g., close dates from 1999)
- Inconsistent definitions (what counts as “qualified”?)
- Opportunities that linger forever in the same stage
Pro tip: Don’t wait until your data’s perfect. Just do a sanity check—fix the obvious junk, then move on. You’ll never have perfect data, and Mantiks can handle some mess.
Step 2: Connect Mantiks to Your CRM
Assuming you’ve signed up for Mantiks, you’ll need to hook it up to your CRM (Salesforce, HubSpot, or whatever you use). This is usually straightforward, but here’s what to watch for:
- Permissions: Make sure you’ve got admin access or get someone who does. Mantiks needs to read (not write) your CRM data.
- Data scope: Only pull in what you need—just opportunities and related activity, not every contact ever.
- Sync issues: If your CRM is slow or locked down, initial syncs can take hours. Start the process before lunch, not after.
Mantiks will usually walk you through this with a setup wizard. If the connection fails, 99% of the time it’s either permissions or a weird CRM setting.
Step 3: Let Mantiks Crunch the Numbers
Once your data’s in, Mantiks will start its analysis. Here’s what’s actually happening (stripped of AI buzzwords):
- It looks for patterns in your past deals—what closed, what didn’t, and what the deals had in common (like deal size, time in stage, or rep activity).
- It builds a model to predict, for each live opportunity, how likely it is to close and when.
- It spits out predictions—usually a “win probability,” predicted close date, and key factors driving the prediction.
What you should know:
- The first run’s predictions may be rough, especially if you don’t have much historical data. The more deals you’ve closed (won and lost), the better Mantiks gets.
- Don’t obsess over single-digit percentages. If Mantiks says Deal A has a 78% chance and Deal B has 73%, treat those as “both likely”—not gospel.
- The model learns over time, so rerun predictions regularly as you update your pipeline.
Step 4: Actually Use the Predictions
Here’s where a lot of teams drop the ball. You’ve got your win probabilities and risk alerts—now what?
How to put Mantiks’ output to work:
- Qualify ruthlessly: Use low-probability deals as a reason to dig deeper, not just drop them. Sometimes the model’s right; sometimes it’s missing context only you know.
- Prioritize outreach: Focus on high-value deals that Mantiks says are stalling. If the model flags “no recent activity” or “unresponsive contact,” take the hint and re-engage—or move on.
- Adjust the forecast: Don’t just copy-paste Mantiks’ numbers into your board slides. Use them as a gut check against your team’s own judgment. If the model and humans disagree, talk it out.
What not to do:
- Don’t let reps “game” the system by stuffing in fake activity to boost scores. Mantiks is looking for real patterns, not box-ticking.
- Don’t ignore the model just because you “feel good” about a deal. Bias is real—and predictive analytics is there to call your bluff.
Step 5: Dig Into the “Why” Behind Predictions
The best part about Mantiks is it doesn’t just spit out a number—it tells you why. Look for explanations like:
- “Deal has gone 3 weeks without activity”
- “Decision maker not engaged”
- “Similar deals in this segment typically close in Q4”
Use these to:
- Coach reps (e.g., “You need executive buy-in here”)
- Spot process issues (e.g., “Are we always slow in this vertical?”)
- Refine your sales stages or definitions if the model keeps tripping over the same bad data
Pro tip: If the explanations don’t make sense, dig into your data. Sometimes it means your CRM fields are out of whack, or reps are skipping steps.
Step 6: Keep It Simple, Iterate, and Ignore the Hype
The temptation is to treat predictive analytics like a weather forecast—something you check, note, and forget. Don’t. The real value comes from building a habit:
- Review predictions weekly: Make it part of your pipeline meetings. Ask “What’s changed?” and “What does Mantiks say?”
- Update your CRM: The cleaner your data, the better the predictions. Don’t let stale opportunities pile up.
- Tweak, but don’t overthink: If the predictions seem off, look at your process before blaming the tool.
Ignore:
- Any claim that “AI will do your job for you.” It won’t. It’s just a faster way to surface risks and spot patterns.
- Fancy dashboards you never use. Focus on the handful of reports that actually help you make decisions.
Real Talk: What Works, What Doesn’t, and What to Watch Out For
What works:
- Mantiks is great for surfacing hidden risk and forcing honest pipeline conversations.
- It saves you time on manual deal review.
- Over a few quarters, you’ll see your forecast accuracy improve—if you use it consistently.
What doesn’t:
- It won’t magically fix a broken sales process. If your team doesn’t log activity or keeps junk deals open, the model will just reflect that mess.
- Predictions aren’t perfect, especially for “one-off” deals (big RFPs, new markets, etc.).
- Over-reliance on the tool can make people lazy. Use it as an aid, not a crutch.
Watch out for:
- Overfitting: If your sales process changes a lot, the model can get confused. Rerun and retrain as needed.
- Data privacy: Make sure you’re not piping in sensitive info you shouldn’t share. Mantiks is secure, but always double-check.
Wrapping Up
Sales forecasting is hard. Tools like Mantiks can help, but only if you keep it simple and use common sense. Don’t wait for a perfect data set or a perfect prediction. Start small, review regularly, and use the insights to ask better questions. Iterate as you go. Your forecast won’t be flawless, but it’ll be a whole lot better than gut feel and crossed fingers.