Prioritize your sales pipeline. Accurately assign points based on profile fit and behavioral engagement to instantly distinguish hot SQLs from cold prospects.
Designed for marketing and sales teams to align on prospect qualification standards effortlessly.
Input your scoring thresholds to watch the dashboard classify your leads into Cold, Warm (MQL), or Hot (SQL) instantly.
Calculates scores by combining explicit firmographic data (job title) with implicit behavioral data (pricing page visits).
Includes a deduction feature to lower scores for inactive prospects, competitors, or users visiting your career page.
Clear color-coded badges transition from blue (Cold) to green (Hot) indicating immediate sales pipeline readiness.
Your scoring criteria and data are processed entirely in your browser. We never store or track your proprietary sales metrics.
Test out new scoring models on the go during marketing meetings. The dashboard functions flawlessly on all smartphones.
Aligning on what constitutes a "good lead" saves immense time. This tool helps:
Test out different scoring models before building them permanently into HubSpot, Marketo, or Pardot workflows.
Set strict point thresholds so your Account Executives only spend time calling leads with high buying intent.
Build and communicate the mathematical logic that transitions a lead from marketing (MQL) to the sales team (SQL).
Analyze how heavily behavior (like webinar attendance) should weigh against job titles when passing leads down the funnel.
Implement a basic, foundational lead scoring framework for early-stage startups without paying for expensive enterprise CRMs.
Showcase custom scoring models to clients visually to explain why certain leads generated require further nurturing.
Without lead scoring, sales teams waste hours calling prospects who aren't ready to buy, while hot prospects go ignored and buy from competitors. Our calculator helps you visualize and build the perfect qualification model.
Scroll up to calculate ↑See how the Manqoosh Lead Scoring Calculator compares to manual scorecards.
Lead scoring is the process of assigning point values to each prospect in your CRM. The Manqoosh Lead Scoring Calculator allows you to rapidly test out different point distributions between demographic profile fit and behavioral engagement before committing them to your marketing automation platform.
Why is this crucial? If sales calls every lead that downloads a whitepaper (even students or low-level employees), they will complain about "bad leads." If they only call CEOs, they miss engaged mid-level managers acting as researchers. Lead scoring strikes the perfect mathematical balance between profile fit and buying intent.
To build a strong CRM model, you must use all three factors. Explicit data is what they tell you (e.g., +20 points for VP title, +15 for Enterprise size). Implicit data is what they do (e.g., +10 for visiting pricing page, +5 for opening email). Negative scoring is vital to remove bad fits (e.g., -50 for visiting the careers page, or -20 for bouncing). This combined formula provides a flawless qualification metric.
Stop manually sorting through bad leads. Manqoosh helps B2B brands scale inbound marketing, automate lead qualification, and drive closed-won revenue.
Beyond free pipeline tools, Manqoosh offers specialized digital solutions to ensure your business scales profitably online.
Build high-performing, fast, and responsive websites that capture lead data seamlessly and convert visitors into pipeline.
Explore ServiceDrive targeted traffic and capture high-intent leads with data-driven PPC campaigns designed to put your brand at the top of search.
Explore ServiceEngage your audience, build B2B brand loyalty, and drive initial MQL conversions through strategic social content.
Explore ServiceOptimize your product listings and store presence to dominate popular e-commerce marketplaces and boost direct sales.
Explore ServiceImplement powerful strategies to attract, nurture, and score high-quality prospects into valuable business deals.
Explore ServiceGet expert insights on CRM setups, lead flow architecture, and actionable digital strategies tailored to your sales goals.
Explore ServiceScale your business efficiently with measurable, results-oriented performance campaigns focused on driving SQL volume.
Explore ServiceSecure, blazing-fast, and reliable hosting plans tailored to keep your landing pages online and capturing leads at their best.
Explore ServiceLead scoring is a methodology used by marketing and sales teams to rank prospects based on perceived value. A higher numerical score indicates a lead is hotter and more ready to be engaged by the sales team.
Explicit scores deal with data the lead provides (job title, company revenue, location). Implicit scores are based on their tracked behavior (email clicks, webinar attendances, website page views).
Negative scoring ensures your list stays accurate. If a highly-ranked lead suddenly stops opening emails for 6 months, or visits your "Job Openings" page instead of "Pricing", their score should decay so sales doesn't waste time on them.
A Marketing Qualified Lead (MQL) shows interest but isn't ready to buy (e.g., scores 50-79). A Sales Qualified Lead (SQL) has shown direct buying intent and matches your target profile (e.g., scores 80+), making them ready for a sales pitch.
Most CRMs use a 100-point scale for simplicity. Typically, reaching 80-100 points triggers the lead to be passed to sales. However, highly complex enterprise models might use scores that scale up infinitely based on lifetime behavior.
You can build these rules in the lead scoring settings of your CRM. Use our tool to figure out the math (e.g., +15 points for "CEO", +10 points for "Viewed Pricing Page") before configuring those exact IF/THEN logic statements in your software.
Yes, if you don't use score decay (negative scoring) or limit implicit points. E.g., someone visiting your homepage 50 times shouldn't get 50 points if they never visit a high-intent page like "Contact Us". Always cap behavioral points.
Valuable explicit properties define your Ideal Customer Profile (ICP). This typically involves B2B data like Job Title/Seniority, Industry type, Annual Revenue, and Employee Headcount.
No, manual adjustment defeats the purpose of an automated, unbiased scoring system. If sales feels a lead score is consistently inaccurate, marketing and sales should regroup to adjust the baseline algorithm instead.
You should review your point thresholds quarterly. Check if leads labeled "Hot" are actually closing at a high rate. If they aren't, your criteria might be too loose and needs tightening.
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Balloon Store is one of our valued clients, and together we’ve built a growth-focused digital strategy that delivered impressive results in a highly competitive market.
| Metric | Source | Change (%) |
|---|---|---|
| Organic Traffic | SEMRUSH | +378.1% |
| Backlinks | SEMRUSH | +160.4% |
| Ref. Domains | SEMRUSH | +94.1% |
| Organic Keywords | SEMRUSH | +1,811.7% |
| Organic Traffic | Google Analytics 4 | +3,603.6% |
| Search Results | Google Search Console | Missing |
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