MadKudu
by HG Insights
Predictive lead scoring and agentic GTM activation for product-led B2B teams
MadKudu is a predictive lead-scoring and agentic go-to-market platform for product-led B2B software companies. It trains machine-learning models on a customer's own conversion history to rank leads and accounts on firmographic, behavioural and in-product usage signals, then pushes scores and account briefs into Salesforce, HubSpot and Slack. HG Insights acquired it in August 2025.
MadKudu, founded in 2014 in Mountain View, California by Sam Levan and Francis Brero, is a predictive lead-scoring and agentic go-to-market platform built for product-led B2B software companies. It trains machine-learning models on a customer's own historical conversion data and scores accounts and leads along three axes — firmographic attributes such as company size, industry and installed tech stack; behavioural signals such as site activity and content engagement; and in-product usage such as feature adoption, seat invitations and login frequency — to surface the product-qualified leads that sales should work next. Scores and AI-assisted account briefs are pushed into the systems reps already live in, with connectors for Salesforce, HubSpot, Marketo, Segment, Amplitude, Mixpanel, Slack, Zapier, Make and n8n. Implementation is deliberately high-touch: a customer success manager builds and tunes the model, typically over about a month, rather than the customer self-serving a rules engine, which is both the reason the scoring is accurate for PLG businesses and the reason it is slower to stand up than a rules-based alternative. HG Insights acquired MadKudu in August 2025 after four years as a platform partner, and folded it into a Revenue Growth Agentic Ecosystem that pairs MadKudu's scoring and activation with HG's technographic and intent data fabric alongside TrustRadius review signals. The madkudu.com domain now redirects to hginsights.com and standalone pricing has been withdrawn in favour of a demo-led enterprise motion, while existing MadKudu customers remain on the product. The practical consequence is a move upmarket that suits large RevOps teams with real product-usage volume.
The RevOps or growth lead at a product-led B2B SaaS company with high signup volume, an instrumented product, and enough closed-won history for a model to learn from.
Reps stop working the inbound list in arrival order and start working the accounts a model trained on your own conversion data says will actually convert.
At a Glance
- Category
- Marketing & Sales
- Pricing
- Subscription, Contact for pricing
- Target Market
- CROs, RevOps Leaders, Growth Marketers, Demand Generation Leaders, Data Scientists
- Deployment
- Cloud-only
- Founded
- 2014
- Headquarters
- Mountain View, United States
Key Features
- ✓Predictive lead and account scoring
ML models trained on your own historical conversion data predict which free users and trial accounts will become paying customers.
- ✓Three-signal scoring model
Blends firmographic attributes, behavioural web signals and in-product usage patterns, so a score reflects fit and intent together rather than one axis.
- ✓Account Briefs and prioritised feed
Compresses the research a rep would do across many tabs into one brief and a ranked feed inside the CRM.
- ✓Agentic GTM activation
Signal-based workflows trigger routing, alerting and downstream actions automatically instead of waiting for a human to read a dashboard.
- ✓CRM and product-analytics integrations
Native connectors for Salesforce, HubSpot, Marketo, Segment, Amplitude and Mixpanel push scores into the tools reps already use.
- ✓CSM-led model build
A customer success manager constructs and tunes the model with you, which raises accuracy but stretches time-to-value to roughly a month.
- ✓HG Insights data fabric
Post-acquisition the scoring joins HG's technographic and intent data plus TrustRadius review signals for full-funnel account intelligence.
Capabilities
Use Cases
- •Prioritising a high-volume free-trial funnel
Rank thousands of self-serve signups so a small sales-assist team calls only the accounts most likely to convert.
- •Automating lead routing and lifecycle stages
Use the score to route leads to the right segment and trigger lifecycle transitions without maintaining a brittle rules matrix.
- •Evaluating acquisition channel quality
Compare predicted lead quality by channel rather than raw volume, which changes where marketing spend goes next quarter.
- •Giving reps context before the call
Deliver an account brief and prioritised feed inside Salesforce, Gong or Outreach so reps skip the manual research pass.
- •Joining product usage to third-party intent
Combine first-party product signals with HG technographic and intent data to build a full-funnel view of an account.
Ideal For
Best For
- ✓Product-led SaaS companies with high free-signup volume that need to tell sales which trials are worth a call
- ✓RevOps teams with several years of clean closed-won history for a model to train on
- ✓Identifying product-qualified leads from in-product signals such as feature adoption, seat invitations and login frequency
- ✓Lead routing, lifecycle automation and channel evaluation driven off a single score rather than a hand-maintained rules matrix
- ✓Existing HG Insights customers who want technographic and intent data joined to first-party product-usage scoring
Not Ideal For
- ✗Companies without a product-led motion — there are no meaningful in-product signals to score, and the model loses most of its edge
- ✗Teams under roughly $2,000 a month of budget, or mid-market HubSpot users, who are now outside the post-acquisition enterprise sales motion
- ✗Buyers who need a contact database, data enrichment or outreach sequencing — MadKudu scores, it does not source or send
- ✗Outbound-led organisations needing buying signals such as hiring, funding or job changes, which the product does not detect
- ✗Teams that want to self-serve configuration: push-to-CRM setup is gated to MadKudu's support team rather than admin-configurable
Deployment
Market Analysis
Pros
- ✓High scoring accuracy for product-led companies that have substantial product-usage data and clean conversion history to train on
- ✓AI-assisted scoring explanations mean reps understand why an account is ranked highly rather than being handed an opaque number
- ✓Strong customer success involvement in model construction and ongoing optimisation, which independent reviewers rate as a genuine strength
- ✓Broad native integration coverage across Salesforce, HubSpot, Marketo, Segment, Amplitude and Mixpanel
- ✓The HG Insights acquisition adds technographic and intent data plus TrustRadius review signals that MadKudu could not supply alone
Cons
- ✗Scoring only — no contact database, no enrichment and no outreach, so it is an addition to a stack rather than a consolidation of one
- ✗Requires product analytics tooling as a prerequisite, adding $200+/month before MadKudu earns anything
- ✗Ineffective for non-PLG business models where there is no meaningful in-product signal to score
- ✗Cannot detect outbound buying signals such as hiring, funding rounds or job changes, so inbound and outbound need different tools
- ✗Signal weighting is only lightly customisable, and push-to-CRM configuration is gated to MadKudu's support team rather than self-serve for admins
- ✗Implementation runs about a month with a CSM-led model build, against same-day setup for rules-based alternatives
- ✗Slack alerting routes through Zapier webhooks rather than a native Slack-first experience
- ✗No public pricing and annual minimums of roughly $25,000 to $50,000, with the post-acquisition motion pushing further upmarket and leaving mid-market HubSpot users underserved
- ✗The madkudu.com domain now redirects to hginsights.com, so the product no longer has an independent web presence to evaluate
Pricing
Starter
From $1,000/mo
- ✓Predictive lead scoring
- ✓Core CRM integration
- ✓Annual contract
Growth
From $2,000/mo
- ✓Approximately $24,000 per year
- ✓Predictive scoring plus product-qualified lead identification
- ✓CSM-led model build and optimisation
Enterprise
Contact for pricing
- ✓Custom scoring models and volume
- ✓HG Insights platform bundling
- ✓Reported deals in the $30,000 to $100,000+ per year range
There is no public price list — pricing tracking services record MadKudu as disclosing none, and since the HG Insights acquisition the pricing page has been replaced with a demo request. Third-party review data puts Starter around $1,000/month and Growth at $24,000/year, with enterprise deals commonly $30,000 to $100,000+ and Vendr reporting a median contract near $32,288/year against annual minimums of roughly $25,000 to $50,000. Annual commitments are standard and there is no free trial. Budget for prerequisites too: the scoring depends on product analytics tooling such as Amplitude or Mixpanel, which reviewers price at a further $200+/month.
Security & Compliance
Sources
This page was written from 6 sources, 6 on domains other than hginsights.com.
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