Krossings for Pendo · for GTM leaders

Pendo's 2026 GTM Blueprint.

Built by experienced revenue operators in 48 hours from public sources. Now imagine it pointed at your data.

6
Pipeline-ready accounts
47
Buying signals mapped
0
Calls needed to source it
Krossings for Pendo · for revenue leadership

Six accounts. Ready to engage.

Built by a forward-deployed revenue team that becomes a second pipeline source.

6
Accounts ready to engage
3
Tier-1 priority accounts
0
Calls needed to source it
30d
To a live second channel
Why now

Three forces resetting the buying window.

Each observable in public data.

Commercial

The new-product-leader clock

A new CPO or VP Product makes foundational tooling decisions inside their first 6 to 12 months. Every Tier-1 account on this list has a new product leader or an active Product Ops hire in that window: Drata is recruiting a Senior Product Operations Manager, Clio is hiring a Senior PM for onboarding and activation, and Lattice brought in SVP Product G. Vives in November 2025. The moment "evaluate later" turns into "decide this quarter."

Market

The AI Act observability deadline

The EU AI Act compliance window closes in August 2026, and enterprise AI agents are being deployed faster than anyone can measure them. Companies that shipped copilots, like Clio Duo and Lattice's HR agent, now face board and regulator questions they cannot answer without agent-level observability. Pendo's Agent Analytics is the first purpose-built solution, and the window to instrument before the deadline is open and closing.

Technical

The fragmented-stack tax

Analytics in one tool, guides in another, feedback in a third: PMs on fragmented stacks wait 5 to 14 days for a feature-adoption answer that a unified platform returns in under a day. Drata's own Amplitude case study calls its prior tools "complicated, siloed, and lacking flexibility." Every day of latency is a day of invisible churn, and finance is now cutting the point-solution budgets that created the sprawl.

Our forward-deployed revenue team finds your next accounts, builds the plays, and runs the channels to close them. Live in 30 days. No new hires.

Part 1 · The Surprise

Verified accounts. Ready to engage.

Every account cleared exclusion, ICP fit, realism, and verified pain signals. Each one ships with a four-touch sequence ready to send.

Drata
Tier 187/100
Security & Compliance Automation SaaS · ~732 employees · ~$100M ARR · Series C, $2B valuation
Deep Dive Included ↓

Pain signals

HighConfirmed Amplitude customer — published case study calls prior analytics "complicated, siloed, and lacking flexibility"; drove a 4x feature-adoption lift after fixing gaps
HighSenior Product Operations Manager role posted — budget allocated to unify product tooling and process
HighOnboarding friction documented in the same case study — "some companies were slow to complete onboarding for certain employees"
MedAgentic AI for Vendor Risk Management launched Aug 2025, "deepest AI Agent integration in the category," with no agent analytics
Brian Elmi LinkedIn unverified
VP Product, Drata
Clio
Tier 184/100
Legal Technology SaaS · ~2,371 employees · $500M ARR · Series G, $5B valuation
Deep Dive Included ↓

Pain signals

HighHiring Senior PM, Onboarding & Activation — owns the critical first 120 days across every Clio product
HighOwn 2026 UK&I Legal Insights Report shows legal-specific AI adoption fell from 58% to 40% — a measurement gap, in their own data
HighClio Duo AI copilot launched with no dedicated agent analytics or ROI measurement
MedReviews flag limited reporting customization, restricting tailored analytics
Michelle Dunlea LinkedIn unverified
VP Product Management, Clio
Lattice
Tier 183/100
HR Technology SaaS · ~537 employees · ~$100M+ ARR · Series F, $3B valuation

Pain signals

HighAI Agent launched with public controversy — scrapped worker-equivalency plan after backlash, then relaunched; needs measurement credibility, no agent analytics
HighNew SVP Product Guillaume (G) Vives (Nov 2025) — new product leader in the first-90-days tooling window
MedMarch 2026 updates added "expanded analytics, new AI capabilities," suggesting current tooling is insufficient
MedHRIS customer growth surged 250% — rapid new-product adoption creates measurement pressure
Guillaume (G) Vives LinkedIn unverified
SVP Product, Lattice
Fivetran
Tier 277/100
Data Infrastructure SaaS · ~1,849 employees · $300M ARR · Series D, $5.6B valuation

Pain signals

HighHiring Senior Product Ops Data & Tools Specialist — product tooling optimization is a funded priority
HighAll-stock dbt Labs merger (Oct 2025), ~$600M combined revenue — two products, two personas, one analytics gap
MedTracks product health metrics (adoption, RWFU, NPS) but the Product Ops hire signals current tooling needs an upgrade
Anjan Kundavaram LinkedIn unverified
Chief Product Officer, Fivetran
Contentful
Tier 274/100
CMS / Digital Experience SaaS · ~1,036 employees · $200M ARR · Series F, $3B valuation

Pain signals

MedNew CEO Karthik Rau appointed — new leadership typically triggers a tooling evaluation across product experience
MedCPO Karl Rumelhart hired from VMware — enterprise-scale product leader likely reassessing the stack
MedAI and personalization features launched Mar 2025 with no dedicated adoption measurement announced
MedDeveloper-to-marketer user-base expansion fractures adoption measurement across divergent personas
Karl Rumelhart LinkedIn unverified
Chief Product Officer, Contentful
Carta
Tier 270/100
Fintech / Equity Management SaaS · ~2,000 employees · $500M ARR · Series G, $7.4B valuation

Pain signals

HighHiring VP Product, Corporations and VP Product, App Platform — expanding product team signals analytics tooling gaps
MedMulti-product portfolio (equity, fund admin, valuations, capital markets) with divergent adoption curves
MedHigh switching cost drives strong retention but can mask in-platform adoption gaps
Vrushali Paunikar Verified
Chief Product Officer, Carta

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The proof

Less pitch. More proof.

Every tab below is real work on Pendo's market, traceable to public sources.

CompanyTierScorePQS MatchTop SignalPrimary Contact
DrataSecurity & Compliance SaaS Tier 1 87/100 PQS-1, PQS-3 Amplitude customer with fragmented stack + Product Ops hire + AI agent, no analytics Brian ElmiVP Product, Drata
ClioLegal Technology SaaS Tier 1 84/100 PQS-1, PQS-3 Hiring onboarding PM + own research shows AI adoption fell 58% to 40% + Clio Duo no analytics Michelle DunleaVP Product Mgmt, Clio
LatticeHR Technology SaaS Tier 1 83/100 PQS-3, PQS-1 New SVP Product + AI agent relaunch needs ROI proof + 250% HRIS growth Guillaume (G) VivesSVP Product, Lattice
FivetranData Infrastructure SaaS Tier 2 77/100 PQS-1 dbt Labs merger + Product Ops hire + multi-product analytics gap Anjan KundavaramCPO, Fivetran
ContentfulCMS / DXP SaaS Tier 2 74/100 PQS-1 New CEO + new CPO + AI features launched + developer-to-marketer expansion Karl RumelhartCPO, Contentful
CartaFintech / Equity Mgmt Tier 2 70/100 PQS-1, PQS-2 Hiring two VP Product roles + multi-product portfolio + hidden adoption gaps Vrushali PaunikarCPO, Carta (verified)

The score is a layered read of what's observable, what domain knowledge unlocks, and what combinations reveal. 47 signal types mapped across the four segments.

18
Surface signals

What anyone can see

Product Ops and Product Analytics job postings, AI agent and copilot launch announcements, funding rounds and IPOs, new CPO and VP Product appointments, split-tool tech stacks visible in BuiltWith and Wappalyzer. Easy to detect, widely searched, noisy alone.

16
Deep signals

What domain knowledge unlocks

SEC 10-K risk-factor language on digital transformation ROI, Bombora topic surges on "product analytics" and "change management," WalkMe and Whatfix contract-expiration proxies via technographic change, EU AI Act compliance filings, and Glassdoor "tooling fatigue" themes.

13
Inference chains

What combinations reveal

Pain built by cross-referencing 2 to 3 points where no single source confirms it but the combination does. A single signal is a hypothesis; two aligned signals are a lead; three or more with context are a priority account.

Worked example · PQS-1 high-confidence rule A split-tool analytics stack detected + a Product Ops or Product Analytics hire + a PM team over five or an active vendor evaluation. Drata hits all three (confirmed Amplitude-only analytics, a Senior Product Operations Manager posting, and a documented onboarding-friction problem from its own case study), which is why it scores 87.

The content engine, on the call.

Bottom-of-funnel SEO/AEO topics mapped to each segment — the content that captures buyers researching the category through answer engines. We walk the live plan through on the call.

Book the walkthrough →

Four pain-qualified segments, defined by observable pain rather than firmographics. Open one to see its definition, target persona, trigger signals, and why-now.

Product usage data is fragmented across three or more tools, with analytics in Amplitude, guides in Appcues, and feedback in Qualtrics. PMs cannot answer "which features drive retention" without a two-week engineering sprint, and every new tracking event or in-app experience is bottlenecked on developer availability.

Target persona

VP / Head of Product at B2B SaaS and software companies (200 to 10K employees) with a customer-facing product and two or more analytics or guide tools detected

Trigger signals
  • Product Ops or Product Analytics hire posting to unify a fragmented stack
  • Multiple analytics and DAP vendors visible in BuiltWith or Wappalyzer
  • Product leaders posting about "data silos" or analytics fragmentation
Why now: Companies with fragmented stacks average 5 to 14 days per feature-adoption insight versus under a day on a unified platform. Acute at annual planning and post-funding, when proving efficiency matters most. The richest signal environment of the four segments.

CS teams discover churn only at renewal. No early-warning system ties product behavior to account health, so CSMs rely on relationship intuition rather than behavioral signals. The operation is reactive firefighting, not proactive intervention.

Target persona

VP / Director of Customer Success at B2B SaaS companies (100 to 5K employees) on a subscription model with NRR below 115%

Trigger signals
  • Job postings for "churn analyst" or "retention strategist"
  • CS hiring surge without corresponding CS tooling investment
  • NRR below the 110% SaaS benchmark, or Gainsight/Totango deployed without product usage data
Why now: Each 1% of gross-retention improvement at a $50M ARR company is $500K saved annually. Companies without behavioral churn signals lose 2 to 4x more accounts. Peaks in Q1 post-renewal post-mortems and Q3 pre-renewal prep.

The organization has deployed AI agents, whether customer-facing chatbots, internal copilots, or embedded AI features, but has zero measurement infrastructure for agent performance. It cannot answer whether the agents are helping users, causing frustration, or returning any ROI.

Target persona

VP / Head of Product or AI Product lead at companies (500+ employees) that have publicly announced an AI agent or copilot deployment

Trigger signals
  • Press or blog posts announcing AI agent or copilot launches
  • Job postings for "AI Product Manager" or "AI Experience Lead"
  • Executives posting about AI investment with no mention of measurement
Why now: 56% of enterprises have deployed AI analytics but only about 15% can measure agent-specific ROI. Acute in 2026 as the EU AI Act deadline approaches in August and first-year AI budgets face ROI review. Pendo Agent Analytics is the only purpose-built answer.

The enterprise deployed new internal software such as Salesforce, Workday, SAP, or ServiceNow, but adoption has stalled below 50% and roughly 27% of employees use unauthorized shadow tools instead. Training was one-time; ongoing behavioral change was never instrumented.

Target persona

CIO, IT Director, or Head of Digital Transformation at enterprises (1,000+ employees) with a recent major software deployment

Trigger signals
  • WalkMe or Whatfix contract expiring (via job postings or technographic data)
  • Large-scale CRM/ERP implementation announced in the last 18 months
  • "Digital transformation" leadership hires or IT posts about change-management challenges
Why now: The average enterprise wastes 30 to 40% of SaaS license spend on unused seats; a 5,000-person company at $10M/yr loses $3 to 4M to non-adoption. Acute 6 to 18 months post-deployment, once launch enthusiasm fades and the adoption data turns damning.

The buying committee mapped — each role with the pain that defines it and the hook that moves it.

Economic Buyer
CPO / CIO / CRO
"We are spending on AI and on a stack of product tools, and I cannot get a clean answer on what either is returning. Consolidate the spend and prove the ROI."
Hook: Lead with tool consolidation and the AI ROI gap. Finance and IT mandates to kill point-solution budgets make the single-platform story land at the executive-sponsor level. Proof: time-to-insight in hours, not quarters.
Business Owner + Champion
VP / Head of Product
"I can't identify underutilized features without an engineering sprint, my roadmap calls are driven by politics not data, and in-app messaging is stuck behind developer availability."
Hook: Lead with retroactive analytics, no-code guides, and reduced engineering dependency. The primary buyer and often the final decision maker under 1,000 employees. Counter the "we already have Amplitude" objection with the guidance and feedback layer Amplitude lacks.
Co-sponsor
VP / Director of Customer Success
"Churn shows up at renewal, onboarding is manual and labor-intensive, and I cannot prove which CS interventions actually drive retention."
Hook: Lead with predictive churn signals, in-app onboarding, and scaling CS without linear headcount. Frequent deal initiator for churn-driven purchases. Proof: behavioral health scores feeding the CS platform.
Day-to-Day Champion
Product Operations / Analytics Manager
"Fragmented tools create integration headaches, every new tracking event needs engineering, and I spend more time building reports than deriving insight."
Hook: Lead with retroactive tagging, data accuracy, and no-code builder quality. Runs the evaluation, configures the POC, and becomes the power user who drives adoption from inside the team.
Technical Gatekeeper
IT Director / Enterprise Architect
"Anything that touches our data has to be secure and integrate cleanly. Show me the architecture and the compliance posture, not a slide."
Hook: Lead with enterprise compliance, the integration model, and a single SDK rather than another data silo. The technical gatekeeper who enters during formal evaluation and can block the deal.

Where Pendo wins and where rivals are exposed, benchmarked against the closest comparator set — sourced from the GTM blueprint's competitive analysis.

DimensionPendoAmplitudeUserpilotWalkMe (SAP)
Category position Product experience platform spanning analytics, guidance, feedback, and AI agent analytics; defining a fourth sub-category in agent observability Product analytics platform built for data teams Analytics plus guidance and feedback for PLG teams Enterprise digital adoption platform
Product analytics Retroactive capture means time-to-first-insight in hours; no-code, no engineering dependency Deepest behavioral and funnel analytics for data teams Solid product analytics, lighter enterprise depth Adoption analytics focused on internal enterprise apps
In-app guidance & adoption No-code guide builder unifying onboarding, announcements, and walkthroughs in the same platform as analytics No in-app guidance or adoption layer Strong guides and onboarding flows Dominant on guidance for SAP-centric internal software
Feedback & voice of customer Native feedback and sentiment capture tied to usage data Requires a separate feedback tool Feedback included; lighter at enterprise scale Limited customer-facing feedback capability
AI agent analytics First purpose-built agent analytics; measures agent performance, ROI, and EU AI Act-relevant observability No dedicated AI agent analytics No dedicated AI agent analytics No customer-facing agent analytics
Where they win & where exposed One platform across analytics, guidance, feedback, predict, and agent analytics; eliminates the stitching tax of 3+ tools Deeper behavioral analytics for data teams, but analytics-only Transparent pricing and a tight PLG motion, weaker enterprise depth Owns SAP-centric enterprise DAP, weaker on customer-facing analytics

The sequences are drafted and waiting.

Every account ships with a four-touch sequence — A/B tested, with an opener tied to that account's observed signals. We walk you through the live ones on the call, so you see the channel that produces the pipeline before you commit.

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Paid plays, ready to deploy.

Account-matched ad variants plus the Tier-1 to custom-audience loop that turns your best-fit accounts into a retargeting layer. Shown live on the call — the second half of the second pipeline source.

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The receipts

Two Tier-1s, in depth.

The top two accounts, worked end to end, why they're at the top, the evidence behind the score, and how we'd open them.

Drata
87 / 100 · Tier 1

Why they're at the top

A ~$100M ARR security and compliance platform valued at $2B, expanding fast through the SafeBase and oak9 acquisitions and an August 2025 agentic-AI launch for Vendor Risk Management. The pain is first-party: Drata's own published Amplitude case study describes its prior analytics as "complicated, siloed, and lacking flexibility," documents slow onboarding completion, and credits a 4x feature-adoption lift to finding and fixing those gaps. A Senior Product Operations Manager posting confirms budget is allocated to unify the stack, and the new VRM agent runs with no agent analytics. Amplitude-only analytics plus a Product Ops hire plus documented onboarding friction is the textbook PQS-1 high-confidence pattern.

How we'd open it

Lead with the analytics-to-action gap. Open on where adoption-measurement latency hides after SafeBase and oak9, framed against Brian Elmi's own case-study result. The wedge is consolidation: analytics, guidance, feedback, and agent analytics under one SDK, supplementing Amplitude rather than ripping it out, with low switching friction. Email to the VP Product, with the VP CS multi-thread following on the churn-prediction angle within two weeks.

Clio
84 / 100 · Tier 1

Why they're at the top

A $500M ARR legal-tech platform valued at $5B, having doubled revenue from $250M in 18 months and acquired vLex to deepen its AI portfolio. Clio's own 2026 UK&I Legal Insights Report shows legal-specific AI adoption fell from 58% to 40% despite heavy investment, which is a measurement problem stated in their own data. They are actively hiring a Senior PM for onboarding and activation across every Clio product, Clio Duo shipped with no agent analytics, and reviews flag limited reporting customization. The combination is a clean PQS-1 and PQS-3 hybrid with fully greenfield tooling.

How we'd open it

Lead with the AI adoption gap surfaced by their own research, reframed as activation and in-product guidance rather than a product-capability problem. Email to VP Product Management Michelle Dunlea, then multi-thread to VP Product Design Amy Hedrick on in-app guidance and onboarding UX, with the incoming Onboarding PM as the day-to-day champion. Warm with two to three weeks of LinkedIn engagement first; this is an enterprise cycle with legal-procurement nuance.

The upside

Public data got us here. Yours compounds it.

What we used (public)

All linked in the Verification Log
  • Company press releases and newsroom feeds (funding, leadership, product launches)
  • LinkedIn job postings (Product Ops, Product Analytics, AI PM, CS roles)
  • LinkedIn profiles and recent post activity
  • Built In, Greenhouse, Communitech, and General Catalyst careers boards
  • BuiltWith and Wappalyzer for visible analytics and DAP stacks
  • Tracxn, GetLatka, PitchBook, and Crunchbase for company snapshots
  • G2, TrustRadius, Research.com, and Lawyerist review libraries
  • Vendor case studies and published customer research (Amplitude, company reports)
  • SEC filings and earnings transcripts (for public comparables) and EU AI Act filings
  • Pendo customer and case-study pages (for the exclusion check)

What your systems unlock (private)

8 systems Pendo's revenue org already runs
  • Salesforce or HubSpot CRM — deal stages, pipeline value, contact engagement
  • Pendo's own product analytics — feature adoption, usage paths, retention cohorts
  • Marketo or HubSpot — full campaign and email engagement history
  • Outreach or Salesloft — sequence performance and reply data
  • Gainsight or Pendo's own health scoring — customer-health and renewal risk
  • Intent feeds (Bombora, G2) at the account level
  • Billing and ARR telemetry for expansion-path triggers
  • Trial and product usage telemetry — activation, seat expansion, login frequency
The first 90 days

From signature to a live channel.

No lengthy discovery. The audit gates everything downstream, infrastructure builds in parallel, and by day 90 you're reviewing pipeline against the number you set at kickoff.

Days 1–5

Onboarding

Contract signed. Customised onboarding doc within one business day covering goals, ICP hypotheses, and access. You have five days.

Days 1–21

The audit

ICP and segment analysis, competitive intel, voice-of-customer mining, AEO positioning, and a custom signal catalogue. Full readout + 90-day revenue roadmap at week three.

Days 1–42

Infrastructure

In parallel: CRM hygiene, LinkedIn activation, domain warm-up, signal-to-rep routing, system integrations. Engine live by day 42.

Days 21–90

Execution

Workstreams go live as the audit dictates: signal layer, content, outbound sequences, paid, orchestration. Weekly working sessions keep it moving.

Day 90

Executive review

Pipeline generated and closed-won attribution reviewed against the success criteria agreed at kickoff. Channel ROI ranked. Next quarter set.

Part 4 · The Ask Part 6 · Next Steps

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