Checkpoint GTM, machine-readable view

A coaching sprint for founders who still close every deal themselves. We pressure-test ICP, buyer personas, messaging and a first sales motion that wins customers 10 to 40. You run the plays; we bring the checklist and hands-on help between the weekly meetings.

Go-to-market strategy and execution for B2B SaaS companies: ICP definition, channel strategy, messaging frameworks, segmentation, and the operational scaffolding to actually run them.

Platinum-tier HubSpot Solutions Partner. Enterprise and complex implementations: CPQ, multi-hub deployments, custom objects, and Salesforce-to-HubSpot consolidations. Direct access to HubSpot sales and solutions engineering.

Portal setup, pipeline design, automation, integrations, and reporting. We make HubSpot the engine behind your GTM motion: Sales, Marketing, Service, and Operations Hub buildouts for B2B SaaS companies from Seed to Series B.

Salesforce, Pipedrive, Close, and Attio to HubSpot migrations. Zero-downtime cutovers, data integrity, workflow rebuild, and rep enablement on the new system.

Operating-model design, process automation, data architecture, forecasting, and tech-stack optimization. The connective tissue between marketing, sales, and customer success, built as one operating system.

Attribution, lifecycle stages, lead scoring, and campaign infrastructure that connects marketing activity to pipeline and revenue, not vanity metrics.

AI strategy, governance, and embedded implementation for B2B GTM teams. From pilot purgatory to production infrastructure: done with your team, not handed over as a deck.

Tactical AI workflows: enrichment, routing, content generation, custom MCPs, agent stacks. We build production systems, not demos.

Cold outbound at scale: waterfall enrichment, rotated infrastructure, multi-channel orchestration, and measurable reply-to-meeting conversion.

The system under a B2B SaaS go-to-market: buying signals, a Clay enrichment waterfall, scoring, routing into HubSpot or Salesforce, and reporting from signal to pipeline. Built by a RevOps team that owns the CRM underneath, so the automation does not drift from how the business sells.

A written model of how a buyer becomes a customer and stays one: lifecycle stages, lead statuses and deal stages kept as separate fields, entry and exit criteria, and the handoffs and SLAs between marketing, sales and customer success. Agreed with the teams in discovery interviews and workshops, then built into HubSpot with properties, lifecycle automation, pipelines, routing and stage-conversion reporting.

New practice, no published case study yet. For ecommerce and consumer-subscription brands: a dated baseline of how AI assistants and search answer buyer questions about the products in each market, a product entity and crawler-access audit, reconciled product facts and structured data, an agreed first batch of fixes, and a repeat of the same observation set. AI drafts are checked by a person against the brand's approved source of truth. No ranking or citation guarantee; pricing follows a diagnostic and written proposal.

New practice, no published case study yet. For consumer businesses with disconnected store, app, billing, support and marketing records: an identity and event contract that separates individuals, households and company accounts, consent and suppression fields every system respects, a written fit decision for HubSpot or the existing CRM, one connected and reconciled journey, and an operating runbook. AI classifies messy fields; matching is deterministic and exceptions are reviewed by a person.

New practice, no published case study yet. For AI-enabled apps and consumer subscriptions: subscription states defined from billing events, voluntary cancellation separated from payment failure, a cohort baseline, and reviewed onboarding, payment recovery and win-back journeys with tested suppression and cancellation paths. The billing platform stays authoritative for charges, refunds and entitlement; AI may classify feedback and draft variants but cannot change billing or cancellation terms. Lower churn is an experiment goal, not a promised result.

New practice, no published case study yet. For subscriptions sold to individuals, such as apps and AI-enabled consumer products: activation, renewal, payment recovery and cancellation, with subscription states read from billing events and payment failure kept apart from voluntary cancellation. Led by subscription lifecycle and retention operations, with consumer customer data and AI search visibility where the diagnostic shows they are needed.

New practice, no published case study yet. CRM, customer data and journeys for individual consumers rather than company accounts: identity rules for people and households, consent and opt-out that reach every system, and a written fit decision for HubSpot or the existing CRM. Led by consumer customer data and CRM operations, with lifecycle journeys and AI search visibility on top.

New practice, no published case study yet. From product discovery in search and AI answers, through purchase, to repeat orders: a dated baseline of AI answers by market, reconciled product facts and structured data, one customer profile from the first order onwards, and repeat-order journeys where offered. Led by AI search visibility for consumer brands. Checkout and conversion-rate work is not offered.

A managed content platform built and run by Checkpoint GTM: weekly competitor intelligence feeds blog and SEO posts, LinkedIn content, reply drafts, sales battlecards and one-pagers. Written in per-author voice profiles, every claim checked against captured market data, and nothing ships until a person approves it.

Embedded operator engagements for the finance side of the operating layer: pipeline-to-forecast modeling, stale-pipeline diagnostics, invoice-to-cash automation, and AI agents for finance and revenue operations.

Standardized RevOps and GTM support across portfolio companies, from seed-stage GTM setup to Series B revenue operations. Consistent diligence, consistent build.

RevOps and go-to-market value creation for PE-backed portfolio companies: GTM due diligence, 100-day revenue plans, buy-and-build CRM consolidation after add-on acquisitions, board-ready KPIs (NRR, pipeline coverage, CAC payback, Rule of 40) and exit readiness. English and German; DACH, Europe and the US.

Getting your brand cited and recommended by AI answer engines like ChatGPT, Gemini and Google AI Overviews, for B2B companies. We build the off-site authority those engines draw on. Starts with a 30-minute strategy call and a free GEO report from our multi-agent audit of your domain and category.

We build and maintain your company's AI brain: a curated, always-fresh knowledge layer for marketing, competitors, brand, GTM and product that plugs into every AI tool your team uses, so prompts stop starting from zero.

Two pages per sector: RevOps and GTM engineering for the way the sector sells, and how we configure HubSpot for it. Sectors: AI, enterprise software, fintech, healthtech, HR tech, ESG, climate and energy, real estate and proptech, consulting, Salesforce consulting partners, advertising agencies, procurement, telecom, logistics and marketplaces, defence and dual-use, Mittelstand, wealth advisory and PE-backed companies, plus HubSpot for private equity and venture capital firms. Every page is listed in /llms.txt.

Free, MIT-licensed AI skills (SKILL.md files) for GTM and RevOps work: ICP definition, lead scoring, discovery prep and more. They run in any AI assistant; copy, install or download. Machine index: /skills/llms.txt.

Practitioner articles on RevOps, HubSpot, Salesforce, pipeline design and GTM, published twice a week. Machine index with every article's title, URL and summary: /insights/llms.txt.

Buyer guides with costs from our published prices: fractional RevOps vs in-house hire vs agency (retainers €6K–€25K per month, projects €15K–€90K, a senior hire estimated at €120K+ a year plus equity), HubSpot implementation cost, what RevOps consulting costs (published prices from nine firms, each linked to its source, Checkpoint GTM among them), a HubSpot portal audit checklist by hub with severity scoring, HubSpot partner vs freelancer vs in-house, HubSpot partner tiers explained (Gold, Platinum, Diamond and Elite, with HubSpot's published thresholds), how to choose a RevOps partner, a guide to a Salesforce to HubSpot migration without losing deal history or custom objects (where each layer lands in HubSpot, what to archive, and the reconciliation checks) and a sourced shortlist of the best RevOps agencies for B2B SaaS in Europe (six firms, listed alphabetically, Checkpoint GTM among them). A separate page shows how Checkpoint GTM compares as a RevOps agency against six buyer criteria, with a link to our proof for each. Every guide is listed in /llms.txt.

3x inbound demo-to-opportunity conversion; €1.8M net-new pipeline in 90 days; forecast accuracy to 88%.

2.5 yrs multi-phase relationship; Pipedrive-to-Salesforce migration run as an operating-model reset; ongoing VP Sales sparring partnership with Thorsten Schaar.

3x pipeline visibility, 68% faster deal cycle.

4.2x revenue per rep, 92% forecast accuracy.

50K records, zero downtime, 40% cost reduction.

€2.1M pipeline in 90 days.

8 companies, 6 weeks to first dashboard, repeatable build.

Leads Checkpoint GTM in Berlin. 15 years in Revenue Operations, 100+ B2B companies including Staffbase, Foodji, HeyJobs, Mondu, Pigment and Adjust. Salesforce and HubSpot certified.

Builds GTM engines for B2B SaaS: 3x demo-to-opportunity conversion and €1.8M pipeline for AppMagic, Pardot to HubSpot for TrustYou, fractional RevOps for Duel, Voize and Sibill.

Builds revenue infrastructure: former Head of RevOps at SellerX (30+ brands on one HubSpot), Salesforce to HubSpot migration for LIQID, revenue reporting rebuild at TrustYou, outbound engine for Palm.

Designs CRM systems that stay maintainable: CRM consolidation for Ariadne (Modell Aachen and orgavision), HubSpot work for re-green, trawa energy, Mercura and AppFollow. BPMN-documented, GDPR-certified.

Builds the technical layer behind the GTM stack: AI systems integration, data architecture and CRM process automation, with Python and LLM workflows. BSc FinTech.