If you’re running a B2B sales or marketing team, you know the pain: too many leads, not enough time, and a lot of pressure to hit pipeline targets. Lead scoring tools promise to fix that. But once you start comparing options—especially Madkudu versus the rest—it gets confusing fast. This guide cuts through the fluff so you can make a decision that actually fits your business, not just some vendor’s pitch deck.
Who’s this for? If you’re evaluating lead scoring tools (or rethinking your current setup), and you care more about results than buzzwords, you’re in the right place.
Step 1: Get Clear on What Lead Scoring Actually Solves
Let’s ground this: lead scoring is about prioritizing which leads get your sales team’s attention first. It’s not magic. It won’t make bad leads good, or fix a broken product. If you’re up to your neck in inbound leads and need to separate real buyers from tire-kickers, lead scoring makes sense. If you’re struggling for any leads at all, these tools won’t save you.
Ask yourself: - Do we get more inbound leads than we can handle? - Are reps wasting time on the wrong accounts? - Is sales complaining about “bad leads” from marketing?
If you’re nodding along, you’re ready to compare tools. If not, work on your lead gen first.
Step 2: Know What Sets Madkudu Apart (and Where It Falls Short)
Most B2B lead scoring tools promise the same things: better prioritization, more pipeline, less wasted effort. But their methods—and results—aren’t all equal.
Madkudu is best known for: - Predictive scoring based on fit and behavior (using both firmographic data and user actions) - Integrations with CRMs like Salesforce and marketing tools like HubSpot - Customization for complex sales cycles (multi-product, multi-person buying journeys) - “Out-of-the-box” models that use industry benchmarks and historical data
But, here’s the honest take: - Madkudu shines if you have a lot of data and a semi-mature GTM motion. If you’re early-stage, it can feel like overkill. - Their models aren’t totally “set and forget.” You’ll still need someone to monitor and tweak them over time. - It’s not the cheapest option. If your budget is tight or your use case is dead simple, you might not see the ROI.
Ignore the hype: No tool (including Madkudu) will magically turn low-quality traffic into pipeline. The data you feed it matters. Garbage in, garbage out.
Step 3: Identify the Alternatives Worth Comparing
Don’t get sucked into long vendor lists. Focus on the real contenders.
Shortlist to consider: - Madkudu – Predictive, behavior-based, strong for SaaS and PLG teams - Clearbit – Great for enrichment, simple scoring, not as strong on behavior - 6sense – Heavy-duty ABM platform, predictive, better for big teams with deep pockets - HubSpot Lead Scoring – Decent if you’re already on HubSpot, but limited if you need nuance - Salesforce Einstein – Predictive, but only if you’re heavily invested in Salesforce - Roll your own (custom scoring in CRM or spreadsheets) – Cheap, but only as good as your logic and discipline
Pro tip: Don’t just compare features—compare how the tools work with the rest of your stack, and how much work they’ll create for your team.
Step 4: Make a List of “Must-Haves” (Not “Nice-to-Haves”)
Before you even look at demos, agree on what actually matters for your GTM strategy. Here’s a cheat sheet:
Important criteria: - Data sources: Does the tool use firmographics, behavior, or both? Can it pull from your CRM, MAP, product, website? - Customization: Can you adjust scoring for your own ICP, or are you stuck with vendor logic? - Integrations: Will it play nice with your CRM, MAP, data warehouse, and whatever else you use? - Transparency: Can you see why a lead is scored a certain way, or is it a black box? - Usability: Will your sales/marketing folks actually use it, or is it too complex? - Support: Who helps when something breaks, or you need to tweak a model?
Stuff that rarely matters as much as vendors claim: - Fancy dashboards (you’ll export to CSV anyway) - AI buzzwords (unless you can see real-world examples) - “Best practice” templates (every business is different)
Write down your must-haves. If something isn’t on that list, don’t let a slick sales rep convince you it’s vital.
Step 5: Test the Tools—Don’t Just Take Their Word for It
You can’t judge a lead scoring tool from a demo alone. Push for a real trial or pilot—ideally, with your own data.
What to do in a pilot: - Run your historical leads through the tool. Did it actually predict who became customers? - Test how easy it is to adjust the model. If you need a data scientist, that’s a red flag. - Get sales feedback: Do the “hot” leads actually look good to them? - Check for surprises: Did the system flag any leads you wouldn’t have considered?
Pro tip: Don’t be shy about asking for help during the trial. Good vendors will guide you; bad ones will ghost you. That tells you a lot.
Step 6: Reality-Check the Pricing and Complexity
It’s easy to get wowed by a slick tool, only to find out it’s twice your budget—or takes six months to implement.
With Madkudu: - Pricing isn’t public; you’ll have to talk to sales. - Expect to pay more than entry-level tools, especially if you want custom models or advanced integrations. - You’ll need someone (maybe not full-time, but at least a few hours a month) to own it internally.
With others: - HubSpot and Clearbit are usually cheaper, but less flexible. - 6sense and Salesforce Einstein can get expensive fast and are often overkill unless you’re a big org.
Don’t forget hidden costs: - Who’s going to maintain the scoring logic? - Will you need extra data enrichment (and budget for it)? - Will your reps need extra training?
If a tool sounds too good to be true for the price, it probably is.
Step 7: Get Real About Change Management
Even the best lead scoring tool is useless if your team ignores it. If reps don’t trust the scores, or if the scores aren’t surfaced where they work (CRM, Slack, etc.), it’ll just be another unused feature.
How to make it stick: - Involve sales in testing and rollout. If they help shape the model, they’ll trust it more. - Make sure the score is visible where they actually look—don’t bury it in a dashboard no one checks. - Get feedback early and often. If people start ignoring the score, find out why and fix it.
Step 8: Ignore the Noise—Focus on Iteration
You won’t pick the perfect tool on day one. And even the best lead scoring setup will need tweaks as your GTM motion evolves.
What actually works: - Start simple. Don’t launch with a mega-complex model. - Review results every month or quarter. Are the best-scored leads actually converting? - Be ready to throw out what doesn’t work and try new logic or data sources.
Remember: Lead scoring should make your team’s life easier, not create busywork. If it’s not helping you close more deals, it’s time to rethink.
Key Takeaways
Don’t let vendor hype or a long feature list cloud your judgment. The right B2B lead scoring tool is the one that fits your current stage, integrates with your stack, and makes life easier for your team. Madkudu is a strong option for data-heavy SaaS teams, but it’s not the only game in town—and it’s not a magic fix for every company.
Keep things simple. Test before you buy. And remember, you can always adjust as you go. The goal is to help your team focus on the leads most likely to close, not to impress anyone with your tech stack.