Lead scoring software ranks your leads and accounts by how likely they are to buy, so reps call the right ones first. For most B2B SaaS teams, that score belongs in the CRM they already use: HubSpot Marketing Hub, or a custom scoring object in Salesforce. Dedicated tools such as Common Room, Reo.dev and 6sense earn a place when your strongest signals sit outside the CRM, in product usage, GitHub activity or third-party intent data.
We’re The GTM Engineering Company. We build scoring models for B2B SaaS companies between post-seed and Series C, and this list comes from what we’ve seen hold up inside client CRMs. Every price below was checked on the vendor’s own page on October 5, 2026.
We’re a member of Clay’s Expert Program. We have no paid relationship with any other tool on this list.
Key Takeaways (TL;DR)
The Best Overall Lead Scoring Software: HubSpot Marketing Hub ranks first because the score lives in the CRM your reps already open, with A1 to C3 grades they read at a glance and no extra vendor to sync.
Why Do You Need It: Without a score, reps pick accounts on instinct and miss anything new, such as a past champion who changed jobs. At one client, 53% of contacts no longer worked at the company their CRM record named.
Who It’s For: B2B SaaS teams on HubSpot or Salesforce with at least one SDR or AE working a pipeline bigger than they can call. Dev-tool, PLG and enterprise ABM teams each have a dedicated option below.
How to Choose the Right One: Pick a tool whose score lives where reps work and combines company, contact and opportunity data. Then confirm a rep can see why a record scored the way it did, and that you can change a weight in an afternoon.
Expected Price: Software runs from Clay at $167 a month and HubSpot Marketing Hub Professional at $800 a month up to custom contracts at 6sense and Demandbase. If you want the model built and run for you, our done-for-you engagements cost $5,000 to $7,000 a month.
Top Lead Scoring Software in 2026 at a Glance
Tool | Best For | Key Features | Pricing |
|---|---|---|---|
HubSpot Marketing Hub | HubSpot-native B2B SaaS teams | Fit, engagement and combined A1 to C3 scores on contacts and companies | From $800 a month (Professional, billed annually) |
Salesforce Einstein + custom object | Salesforce-native teams with an admin | Predictive lead score plus a custom object for account roll-ups | Included in Performance and Unlimited; add-on on Enterprise |
Common Room | PLG and community-led SaaS | AI Scoring on people and accounts, hover to see why | From $2,500 a month (billed annually) |
Reo.dev | Dev-tool and open-source companies | 0 to 100 account activity score from GitHub, docs and product signals | Pricing on request |
Clay | Custom scores from data your CRM lacks | Enrichment, scoring formula and AI note pushed to your CRM | From $167 a month; CRM sync from $446 a month |
6sense | Enterprise ABM | Predictive account fit and buying-stage scores | Pricing on request |
Demandbase | Enterprise ABM teams with opportunity history | Pipeline Predict score from 0 to 100, refreshed nightly | Pricing on request |
Factors.ai | Mid-market account-based marketing | Custom and predictive account scoring, G2 and LinkedIn intent | Pricing on request |
MadKudu (HG Insights) | PLG companies with conversion history | Predictive fit and behavior scoring | Pricing on request |
What Is Lead Scoring Software?
Lead scoring software assigns every lead or account a score, or a tier, that estimates how likely it is to buy. The score combines two inputs: fit, meaning how closely the record matches your ICP, and intent, meaning whether anyone there is showing buying behavior right now.
Account scoring applies the same idea to companies. An account scoring model rolls up every contact, product event and opportunity tied to one company into a single number. In B2B lead scoring you need both levels, and each should feed the other. A VP of Sales at a 20-person design studio can look like a perfect lead while the account is a poor fit. Three mid-level engineers at a 300-person Series B company might each score low, yet together they are often the strongest buying signal in your CRM.
We also blend intent scores into the company and contact scores. Most intent providers sync to HubSpot and Salesforce, so that data can land on the same record.
The category splits into three types of tools:
Rules-based scoring. You assign points to fields and actions. It works on day one and anyone can read the logic.
Predictive lead scoring, where a model trained on past wins and losses sets the score. It needs volume: Salesforce requires at least 1,000 leads created in the last 200 days, with 120 of them converted, before Einstein builds a model for your org.
Signal-based scoring reads live activity across your website, product, community and GitHub. Common Room and Reo.dev sit here, along with ABM tools like 6sense.
On almost every project we start with a rules-based fit score, then layer intent on top. The weights in that fit score depend on how well you define your ICP with data, so do that work first.
Why Do You Need Lead Scoring Software?
You need it because reps have more accounts than hours, and without a ranked list they choose by memory. Selling hours are already scarce: in Salesforce’s State of Sales report, reps said they spend 70% of their time on non-selling tasks. Memory favors the accounts they already know. It misses a new VP of RevOps at a target account, a spike in pricing-page visits, or an opportunity that nearly closed last spring.
Stale data makes it worse. The same Salesforce research found only 35% of sales professionals completely trust the accuracy of their organization’s data. In our client CRM audits, as many as 60% of contacts had left the company their record still named. At one of our clients, an AI sales enablement company, the figure was 53%. We turned that decay into a job-change trigger and built PLG scoring across 10,000+ contacts, so former users who moved to new companies surfaced as leads.
A working score changes two things you can measure:
Who gets called first. Tier 1 accounts reach a rep the same day the signal appears.
What marketing hands over. The MQL definition becomes a tier cutoff the sales team agreed to.
Inbound gets better too. For one AI company, we de-anonymized form fills submitted with personal email addresses and recovered 1 in 5 inbound leads as qualified ICP accounts. Those leads were in the CRM all along, scored as junk.
Who Needs Lead Scoring Software?
RevOps leaders who inherited a messy stack
You started 3 to 12 months ago and found HubSpot or Salesforce, Clay, Apollo, an intent tool and a few spreadsheets, none of them sharing a score. Your mandate is to show progress within 90 days. A tiered account score is often the fastest visible win, because sales sees it on every record the week it ships.
Founders and CEOs at post-seed to Series C SaaS
At $1M to $30M ARR, you can’t justify a full RevOps team yet, and new business is behind plan. You need to know whether the problem is lead volume or lead choice. A score built on your closed-won history answers that within a quarter.
Sales leaders whose reps work unranked lists
CROs and VPs of Sales feel the gap when two reps call the same account and nobody calls the account that visited pricing three times. Lead prioritization software gives every rep the same order and gives you a way to audit it in pipeline reviews.
Marketing ops and growth teams arguing about MQLs
If sales rejects half your MQLs, the definition is the problem. An agreed fit-plus-intent model replaces the form-fill MQL, and it gives you a defensible way to report which campaigns produced Tier 1 accounts.
Dev-tool, PLG and open-source companies
Your buyers read docs, star repos and install packages long before they fill a form. Buyers in other categories behave the same way. In a Gartner survey of 632 B2B buyers, 61% said they prefer a rep-free buying experience. Standard intent data misses most of that. You need ICP scoring tools that read product, GitHub and community signals, which is why Reo.dev and Common Room are on this list.
Best Lead Scoring Software: In-Depth Review & Comparison
We ranked these 9 lead scoring tools against the factors in our buying guide below and against what we’ve seen inside client stacks. Every price comes from the vendor’s own page, checked on October 5, 2026.
A few names from older lists are missing on purpose. Breadcrumbs was acquired by MadKudu in October 2024. Pocus was acquired by Apollo.io, announced March 31, 2026. And HubSpot announced on June 30, 2026 that it is acquiring Warmly, whose intent data will likely end up feeding HubSpot scoring.
1. HubSpot Marketing Hub Lead Scoring
Overview
HubSpot lead scoring lives in the same CRM your team uses for email, deals and reporting. That location is its biggest advantage. You can combine company, contact and deal data into one score without syncing anything, and the score shows up in list views, workflows and reports the moment you save it.
Ideal For
B2B SaaS teams already on HubSpot as their CRM
Marketing ops managers who want scores they can edit without a developer
Companies with under 50 reps that need tiers this quarter
Top Features
HubSpot’s lead scoring tool builds three kinds of scores:
Fit scores read attributes like job title, company size and revenue.
Engagement scores count website visits, email opens and form submissions.
Combined scores place each record on a nine-cell grid from A1 to C3. The letter is fit and the number is engagement, which hands you tiers without extra work.
Marketing Hub Professional and Enterprise score contacts and companies. Sales Hub Professional and Enterprise add company and deal scores, and AI-built contact scores need Marketing Hub Enterprise.
Why They Stand Out?
From what we see in client builds, HubSpot lead scoring is one of the strongest options for HubSpot-native teams, mostly because of where it lives. The A1 to C3 grid is easy for reps to read on a list view. Scores can trigger workflows and lead routing directly.
Pros
No extra vendor, contract or integration
Letter-number grades that reps understand on first sight
Up to 50 scores on Enterprise, enough for separate models per product line
Scores feed workflows and reports with no sync delay
Cons
Starter plans include no scoring at all.
Engagement scoring only sees activity HubSpot tracks; product usage needs its own sync.
At $800 a month, Professional is a big jump for a team that only wanted scoring.
Pricing
Lead scoring starts on Marketing Hub Professional at $800 a month billed annually ($890 billed monthly), with 3 core seats and up to 5 scores. Enterprise starts at $3,600 a month with 5 core seats, up to 50 scores and AI recommendations.
Final Verdict
If you run HubSpot, start here before buying anything else. Look elsewhere when your best signals live in GitHub, your product database or a community, since HubSpot can’t see them without a separate sync.
2. Salesforce Einstein Lead Scoring + a Custom Scoring Object
Overview
Salesforce remains a strong option when your whole CRM already runs on it. Einstein Lead Scoring gives each lead a predictive score trained on your own conversion history. We pair it with a custom scoring object that holds account and contact scores, because the setup matters more than the license.
Ideal For
Salesforce-native B2B SaaS and enterprise sales teams
Companies with an in-house admin or a partner who maintains custom objects
Orgs with enough lead volume to train a predictive model
Top Features
A predictive score per lead, once you meet Einstein’s data thresholds
Custom objects that hold roll-up scores outside the Lead, Contact and Account layouts
Scores available to assignment rules, flows and list views
Why They Stand Out?
Salesforce gives you full control over how scores roll up. An account score pulls from contacts, from product usage if you run a PLG motion, and from opportunities. Build that directly on core objects and you end up with dozens of formula fields that confuse SDRs and AEs and are painful to change a year later. A separate object keeps the logic in one place, so weights change without anyone touching core records.
Pros
Deep control over roll-ups and routing
Einstein’s predictive layer can sit on top of your rules-based fit score
Handles enterprise record counts and complex territory rules
Cons
Einstein needs 1,000 leads in 200 days, 120 of them converted, for an org-specific model.
Custom objects take admin time to build and more to maintain.
Enterprise Edition customers pay extra for Einstein.
Pricing
Einstein Lead Scoring is part of Sales Cloud Einstein. Salesforce includes it in Performance and Unlimited Editions and sells it at extra cost on Enterprise Edition. Add-on pricing is on request.
Final Verdict
A good fit for Salesforce shops with admin capacity. Smaller teams without an admin will spend more time maintaining the object than using the score, and should weigh the trade-offs in our HubSpot vs Salesforce for startups comparison before committing.
3. Common Room
Overview
Think of Common Room as CRM scoring with far more inputs. It collects signals your CRM never sees, including product usage, website visits, job changes, GitHub activity and what Common Room calls dark-funnel activity. Its AI Scoring ranks people, then aggregates those scores on the account.
Ideal For
PLG companies with free users spread across many accounts
Community-led SaaS with active Slack or Discord groups
Teams with signals in five or more separate sources
Top Features
Person-level and account-level AI Scoring, included on every plan
Hover-over explanations showing the behaviors and attributes behind a score
Signal weights that RevOps can adjust without a data science project
Why They Stand Out?
Explainability is the detail we like most. A rep can hover over any score and see what produced it, which answers the question reps ask most often: why did this record score 82 when that one scored 45? RevOps can change weights with simple controls.
Pros
Connects anonymous and community activity to real accounts
Scores sync back to the CRM
Includes 5 seats and 100,000 contacts on the entry plan
Cons
$30,000 a year minimum is a lot for a seed-stage team with one SDR.
Value grows with each source you connect, so a team with only CRM data gets little from it.
Reps who never open Common Room depend on a clean CRM sync.
Pricing
Essential is $2,500 a month billed annually, with 5 seats and up to 100,000 contacts. Advanced (15 seats, up to 250,000 contacts) and Enterprise (30 seats, up to 750,000 contacts) are custom priced.
Final Verdict
Common Room earns its cost for PLG and community-led companies with spread-out signals. A sales-led company selling to finance teams will find most of its sources empty.
4. Reo.dev
Overview
Reo.dev scores developer intent for companies that sell to engineers. Standard intent providers mostly miss developer research, because it happens on GitHub, in docs and in package managers. Reo.dev says it tracks more than 150 million intent signals from over 50 sources and maps developers to their companies.
Ideal For
Dev-tool and API-first companies
Open-source projects with a commercial edition
Developer-led growth teams adding outbound
Top Features
Its Account Activity Score runs from 0 to 100, weighted across every developer at the account. It reads GitHub activity, documentation visits, product installs, telemetry and community activity, then sorts accounts into High (60 to 100), Medium (20 to 60) and Low (0 to 20). Data pushes to your CRM through native integrations.
Why They Stand Out?
Reo.dev has its own scoring mechanism, and its bands give reps a call order out of the box. We have used it in production. For one open-source developer company, we built an outbound engine on Reo.dev that treats GitHub repo activity as the buying signal; the developer-signal outbound case study shows how it connects to sequencing. In our builds, the Reo.dev score lands in the CRM as one more input to the account score.
Pros
Catches GitHub, npm and docs activity that general intent data misses
Three plain bands that need no training
Account scores roll up from individual developers
Cons
Outside dev tools, APIs and open source, the signals thin out fast.
Pricing isn’t published.
A second score to reconcile with your CRM fit score
Pricing
Pricing on request.
Final Verdict
Reo.dev is one of the smartest choices for companies whose buyers write code. Sales-led SaaS companies selling to HR or finance will get little from it.
5. Clay
Overview
Clay is a data workflow tool where a score is one column in a table. You enrich each record from many providers, write the scoring formula, add an AI column that explains the result, then push score and tier into HubSpot or Salesforce. We use Clay on most of our scoring builds, which is part of why the disclosure at the top exists.
Ideal For
Teams whose scoring fields don’t exist in the CRM yet
RevOps engineers comfortable with formulas and data credits
Companies scoring on hiring, traffic growth or social reach
Top Features
Enrichment from many data providers on one row
AI columns that write the account scoring note
CRM auto-sync on Growth and above
Why They Stand Out?
Clay’s output feeds the CRM score. Hiring activity, traffic growth and LinkedIn follower counts become scoring fields, and the result lands where reps work. Our Clay workflow templates cut the build time.
Pros
Turns almost any public data point into a field you can weight
Cheap to start, with a free plan for testing
The AI note is a few minutes of work once the table exists
Cons
Someone has to own the table and its credit budget.
Credits add a variable cost on top of the plan.
The $167 Launch plan has no CRM auto-sync.
Pricing
Clay’s pricing page lists a free plan with 100 data credits a month. Launch is $167 a month for 15,000 actions, and Growth, the first plan with CRM auto-sync, is $446 a month for 40,000 actions. Enterprise is custom.
Final Verdict
Clay suits teams with a builder on staff. Without one, tables go stale within a quarter and the score stops updating. Our Clay lead scoring guide walks through the method.
6. 6sense
Overview
6sense scores accounts and their buying groups. Its predictive models estimate fit and buying stage for each account using third-party intent data mapped to companies, and the results sync to your CRM and ad tools.
Ideal For
Enterprise ABM teams selling into large buying committees
Marketing teams running account-based ads
Companies with a dedicated RevOps or marketing ops function
Top Features
Predictive account scores with a buying-stage estimate
Third-party intent data mapped to accounts
Buying-group views across multiple contacts
Why They Stand Out?
6sense scores the whole buying group instead of one contact, which matches how enterprise deals close. It’s one of the strongest choices for teams whose deals involve six or more stakeholders.
Pros
Wide third-party intent coverage
Account and buying-group views in one place
Feeds both CRM and ad audiences
Cons
For a $5M ARR company with two AEs, it is usually more than you need.
Setup takes real RevOps time.
On 6sense’s pricing page, predictive models, scores and dashboards appear only in packages with Predictive AI. The data-credits-only package doesn’t include them.
Pricing
Pricing on request.
Final Verdict
Worth the evaluation for enterprise ABM programs with budget and staff. Most post-seed to Series B teams should start with CRM scoring and add 6sense later, if ever.
7. Demandbase
Overview
Demandbase is an ABM suite whose scoring piece, Pipeline Predict, estimates how likely each account is to open a new business opportunity. It trains on your past opportunities and blends engagement, firmographic, intent and website visitor data.
Ideal For
Enterprise and upper mid-market ABM teams
Companies with at least 50 accounts that opened new business opportunities in the past year
Marketing teams that already run Demandbase for advertising
Top Features
According to Demandbase’s support documentation, Pipeline Predict scores accounts from 0 to 100. Scores of 95 and above read “Highly Likely,” 50 to 94 “Likely,” and anything under 50 “Unlikely.” Scores update automatically every night, and a new model takes 24 hours to build.
Why They Stand Out?
The minimum data bar is lower than many predictive tools. Pipeline Predict needs at least 50 distinct accounts that opened New Business opportunities in the past 12 months, which a Series B company can reach.
Pros
Clear three-label output reps can act on
Nightly refresh keeps scores current
Trains on your own opportunity history
Cons
The model only reads activities assigned Engagement Points above 0, so setup errors silently shrink its inputs.
Built for enterprise teams; small teams pay for modules they won’t use.
No published prices.
Pricing
Pricing on request. Demandbase’s pricing page describes a “platform fee” covering software and services, plus a flat fee per user.
Final Verdict
Demandbase fits ABM teams that want predictive account scores trained on their own pipeline. Teams without an ABM motion will find HubSpot or Salesforce scoring covers what they need.
8. Factors.ai
Overview
Factors.ai is an account-based marketing tool that identifies which target accounts are researching you, through website behavior, ad interactions and third-party sources, then ranks them for sales. It also names individual visitors where it can, so a rep sees the person behind the account visit.
Ideal For
Mid-market B2B SaaS marketing teams running LinkedIn and Google ads
Teams that want account scoring and attribution in one tool
HubSpot or Salesforce users adding G2 and LinkedIn intent
Top Features
Custom account scoring on Basic plans and above
Predictive account scoring on Growth and Enterprise
Integrations with HubSpot, Salesforce, G2 and LinkedIn, per its integrations page
Why They Stand Out?
Factors.ai combines de-anonymized website visits with G2 and LinkedIn intent, so the score reflects research happening off your site too. Attribution in the same tool lets marketing see which campaigns produced high-scoring accounts.
Pros
Custom scoring starts on the entry paid plan
A free tier to test website identification
Ad audiences built from scored accounts
Cons
Predictive scoring requires Growth or Enterprise.
Pricing isn’t published, and the company typically bills on annual contracts.
Overlaps with your CRM’s own scoring if you already use HubSpot scores.
Pricing
Pricing on request. Plans run Free, Basic, Growth and Enterprise.
Final Verdict
A sensible pick for marketing-led teams that want account scoring tied to ad spend. Sales-led teams that rarely run paid campaigns will use only part of it.
9. MadKudu (Now Part of HG Insights)
Overview
MadKudu made its name on predictive fit and behavior scoring for PLG SaaS. It no longer exists as an independent company, and you should know that before you evaluate it. MadKudu acquired Breadcrumbs in October 2024, then HG Insights acquired MadKudu on August 11, 2025. Madkudu.com now redirects to hginsights.com.
Ideal For
PLG companies with enough product and conversion history to train a model
Teams already buying technographic data from HG Insights
Top Features
Predictive fit and behavior scores for accounts and leads
Paired with HG Insights’ technographic data
Why They Stand Out?
It covers predictive lead scoring for teams whose product usage predicts conversion better than firmographics do. The HG Insights pairing adds tech-stack data to the fit side of the score.
Pros
Built for PLG from the start
Breadcrumbs’ scoring now sits in the same product line
Technographic coverage from HG Insights
Cons
The roadmap has shifted through two acquisitions in ten months.
Needs clean usage and conversion history.
No public pricing.
Pricing
Pricing on request through HG Insights.
Final Verdict
Consider it if you already buy from HG Insights or run a PLG motion with years of conversion data. Ask about the roadmap directly before signing a multi-year contract.
For tools that act on scores instead of producing them, see our guides to lead intelligence platforms and signal-based outbound tools.
How to Choose the Best Lead Scoring Software (What to Consider)
Six factors decide most of our recommendations. Run every tool on your shortlist through them before you read feature pages.
1. Put the score where reps work
If reps have to open another app to see a score, they stop checking within a month. Native CRM scoring wins here by default. A third-party tool needs a clean sync back to the account and contact record, and the score must appear in the list views reps sort by.
2. Combine company, contact and opportunity data
Deals close through buying committees. Forrester’s State of Business Buying 2024 found that 13 people are involved in the average buying decision. A tool that only scores individual leads misses the account picture, and a tool that only scores accounts can’t tell an SDR which person to call.
Where the combined score lives matters too. We always build scoring in a separate object, or a dedicated section of the account record. Roll-ups from contacts, product usage and opportunities get messy fast on core objects, and every extra field confuses SDRs and AEs who don’t need to see the inputs.
3. Make every score explain itself
Every scoring tool needs a way to explain its meaning to the end user: which fields it reads, what it adds up and why the result is what it is. On every project we add two fields that do this work.
The first is a tier: Tier 1, 2 and 3, or A, B and C, like school grades. A rep remembers that an account is Tier 1. Nobody remembers whether 73 was good.
The second is an account scoring note, an AI-written text field that says in plain words why the account or lead scored the way it did. These are usually easy to build. Here’s what the fields look like on a record:
Field | Example value |
|---|---|
Account tier | Tier 1 |
Account score | 86 |
Fit score | 42 of 50 |
Intent score | 44 of 50 |
Account scoring note | Tier 1. 180 employees, Series B, US. Hiring 3 SDRs this month. Two contacts visited pricing twice in 7 days. |
Last recalibrated | July 1, 2026 |
The note exists to build trust. Once reps understand how a score is built, they bring suggestions to improve it, because they can see what it misses. They also start using it in their own reports and in how they prioritize opportunities. Reps who don’t trust a score build their own spreadsheet, and then you have two scoring systems.
4. Choose fields that predict revenue
There are a million fields you could score on. These are the ones we have used to score accounts for B2B SaaS clients:
Category | Fields |
|---|---|
Firmographic | Employee count, team size, revenue range, company growth %, industry, sub-industry, country, region, global territory, relevant job openings |
Persona | Interested department, ABM persona, seniority, leadership contacts |
Intent and engagement | De-anonymized visitors on the website, product pages and GitHub; webinars and events attended; meetings scheduled before |
Commercial history | Invoices paid in the last 3 years, opportunities that nearly closed and didn’t, active opportunities in the last year |
Data depth | How much data you hold on the company or contact |
Social | LinkedIn followers and connections, Instagram and TikTok followers |
Start with firmographic and persona fields, since they make up your fit score and work on day one. Give commercial history more weight than most teams do: an opportunity that nearly closed last year is often your warmest account. Social follower counts belong in the model only when they predict revenue, which is common for a creator tool and rare for a DevOps product.
Intent fields depend on catching anonymous visits first, so look at website de-anonymization tools before you weight them. And clean the data underneath. Gartner’s data quality research puts the cost of poor data quality at $12.9 million a year for the average organization. A model that reads stale job titles and duplicate accounts ranks the wrong people with total confidence, so a pass on CRM data hygiene belongs before launch.
5. Plan recalibration from the start
Your ICP will shift within a year. Changing a weight or adding a field should take an afternoon, and the tool should let you do it without rebuilding.
We recalibrate every 6 to 9 months, so the score still represents the business as it is now. A company at $3M ARR scores accounts differently from the same company at $15M, with new segments, a new pricing tier and twice the sales team. Pull closed-won and closed-lost deals from the period, check which fields separated them, and adjust. Then update the SOP that explains the scoring to reps, and show it inside the CRM if you can, through help text on the score field or a pinned note. If scores trigger assignment, review your lead routing software rules at the same time.
6. Match predictive tools to your data volume
Predictive lead scoring only works when there’s enough history to learn from. Salesforce Einstein asks for 1,000 leads in 200 days with 120 converted, and Demandbase’s Pipeline Predict needs 50 accounts that opened new business opportunities in the last 12 months. Below those numbers, start with a rules-based fit score and intent on top, and revisit predictive scoring once the history exists.
Everything You Need to Know About Lead Scoring Software
Ratings are our judgment from client builds and vendor documentation, checked in October 2026. Five filled stars is best; for Affordability, more stars means a lower cost to get started.
Pros and cons
Tool | Top pros | Main cons |
|---|---|---|
HubSpot Marketing Hub | No extra vendor; A1 to C3 grades; feeds workflows directly | Not on Starter plans; misses product data; $800 a month entry |
Salesforce Einstein + custom object | Full roll-up control; predictive layer; handles enterprise scale | Strict data thresholds; admin time; paid add-on on Enterprise |
Common Room | Wide signal coverage; hover-to-explain scores; easy weight changes | $2,500 a month entry; needs many sources; separate interface |
Reo.dev | GitHub and docs signals; clear bands; developer roll-ups | Narrow fit; no public price; second score to reconcile |
Clay | Any data point as a field; cheap start; AI notes | Needs an owner; credit costs; no CRM sync on Launch |
6sense | Third-party intent; buying-group views; ad audience sync | Oversized for small teams; long setup; Predictive AI packages only |
Demandbase | Three clear labels; nightly refresh; trains on your pipeline | Engagement Points setup; enterprise scope; no public price |
Factors.ai | Custom scoring on Basic; G2 and LinkedIn intent; attribution | Predictive on Growth only; annual contracts; overlaps CRM scoring |
MadKudu (HG Insights) | PLG focus; Breadcrumbs folded in; HG technographics | Roadmap shifts; needs conversion history; no public price |
Ratings
Tool | Ease of use | Integrations | Support | Affordability | Explainability |
|---|---|---|---|---|---|
HubSpot Marketing Hub | ★★★★★ | ★★★★☆ | ★★★★☆ | ★★★☆☆ | ★★★★☆ |
Salesforce Einstein + custom object | ★★☆☆☆ | ★★★★★ | ★★★☆☆ | ★★★☆☆ | ★★★☆☆ |
Common Room | ★★★★☆ | ★★★★☆ | ★★★★☆ | ★★☆☆☆ | ★★★★★ |
Reo.dev | ★★★★☆ | ★★★☆☆ | ★★★☆☆ | ★★★☆☆ | ★★★★☆ |
Clay | ★★☆☆☆ | ★★★★★ | ★★★☆☆ | ★★★★☆ | ★★★★☆ |
6sense | ★★☆☆☆ | ★★★★☆ | ★★★★☆ | ★☆☆☆☆ | ★★★☆☆ |
Demandbase | ★★☆☆☆ | ★★★★☆ | ★★★★☆ | ★☆☆☆☆ | ★★★☆☆ |
Factors.ai | ★★★★☆ | ★★★★☆ | ★★★★☆ | ★★★☆☆ | ★★★☆☆ |
MadKudu (HG Insights) | ★★★☆☆ | ★★★★☆ | ★★★☆☆ | ★★☆☆☆ | ★★★☆☆ |
Get a Done-for-You Scoring Model from The GTM Engineering Company
If you’d rather not configure and maintain the score yourself, we build and run it inside the CRM your reps already open. ICP fit and intent signals combine into a tier, every record gets a plain-language scoring note, and Tier 1 accounts route to the right rep. For one AI sales enablement client, that meant PLG scoring across 10,000+ contacts and a lifecycle cut down from 20 stages.
Two reasons to start now. First, a score built on this year’s closed-won deals is ready before next year’s planning. Second, the first month has fixed deliverables: by day 30 you have a prioritized fix list, a working enrichment table and at least one live signal flowing into your CRM. Engagements run 3 or 6 months at $5,000 to $7,000 a month, with the CRM audit included, and every HubSpot, Salesforce or Clay license stays in your name.
FAQs About Lead Scoring Software
What is the best lead scoring software in 2026?
The best lead scoring software in 2026 for most B2B SaaS teams is HubSpot Marketing Hub, from $800 a month on Professional, because the score lives in the CRM reps already use. Salesforce teams get the same benefit from Einstein Lead Scoring plus a custom scoring object. Add Common Room, Reo.dev or 6sense when your strongest signals sit outside the CRM.
What should I consider when choosing the right lead scoring software for me?
When choosing the right lead scoring software, consider where the score lives, whether it combines company, contact and opportunity data, and whether reps can see why a record scored the way it did. Check that you can change weights without a rebuild, since we recalibrate every 6 to 9 months. For predictive tools, confirm you have the history, such as 1,000 leads in 200 days for Salesforce Einstein.
How much does lead scoring software cost?
Lead scoring software costs anywhere from $167 a month to custom enterprise contracts. Clay starts at $167 a month, though CRM sync needs Growth at $446 a month. HubSpot Marketing Hub Professional is $800 a month billed annually, Common Room Essential is $2,500 a month, and 6sense, Demandbase, Factors.ai and Reo.dev price on request.
Do I need a tool or a team to set up lead scoring?
You need both a tool and someone who owns the model, because software alone doesn’t choose fields or set weights. HubSpot holds up to 5 scores on Professional, yet someone still has to pick the inputs, weight them from closed-won data, write the SOP and recalibrate every 6 to 9 months. If a RevOps lead or admin has that capacity, configure the tool yourself. If not, a done-for-you build runs $5,000 to $7,000 a month.
How do I get started with The GTM Engineering Company?
To get started, request the 30-day audit through our booking page. We review your CRM, your closed-won history and your current scoring, if any. By day 30 you have a prioritized fix list, a working enrichment table and at least one live signal flowing into your CRM.
What is the difference between lead scoring and account scoring?
The difference between lead scoring and account scoring is the unit: lead scoring ranks individual people by fit and intent, while account scoring ranks companies. An account scoring model rolls up every contact, product event and opportunity at one company into a single score or tier. In B2B SaaS you need both, because deals close through buying committees of several people.
