Dan Jiao, VP RevOps at Aircall, has now moved two companies from a global functional model to regional GMs — at Signifyd and again at Aircall. He joins Janis to explain what actually changes when four business units each own their P&L, and why RevOps becomes the glue that keeps one company from quietly becoming five.

We cover:

• Global functional vs. regional GM model — and what stays centralized
• The revenue scale where a regional split starts to make sense
• Running RevOps as a product org: the global go-to-market operating system
• Who owns segmentation vs. who co-designs territories
• Embedding regional business partners as de facto chiefs of staff
• One global scoring model, multiple regional calibrations
• Why capacity ratios differ market by market
• RevOps as the neutral referee in budget and headcount debates
• Holding one global forecasting standard across four business units
• Buyer-verified exit criteria instead of rep-filled fields
• Sharing best practices when there's no global head of sales

Dan Jiao on LinkedIn: https://www.linkedin.com/in/danjiao/
Aircall: https://aircall.io
Janis Zech on LinkedIn: https://www.linkedin.com/in/janiszech/Philipp Stelzer on LinkedIn: https://www.linkedin.com/in/philippstelzer/WeFlow: https://www.weflow.ai/Join the RevOps Chat Community: https://www.weflow.ai/community
Subscribe to the RevOps Letter: https://www.weflow.ai/revops-letter

Book recommendation: Switch: How to Change Things When Change Is Hard by Chip & Dan Heath

Chapters:
(00:00) Intro & welcome to Dan(02:33) Dan's path from sales to RevOps(04:46) Global functional vs. regional GM(08:12) When a regional split makes sense(11:18) Who owns segmentation and territories(14:04) The hybrid model and regional business partners(17:43) Account prioritization and scoring(20:49) Capacity planning across regions(25:53) RevOps at the budget table(27:52) One global forecasting standard(30:31) Buyer-verified exit criteria(32:43) Sharing best practices without a global sales lead(34:50) Book recommendation & close

Mollie Bodensteiner, VP RevOps at ZoomInfo and returning guest, joins Janis to break down how AI is reshaping RevOps roles, team structures, and career paths. RevOps used to report on the business — now it builds and governs the systems that run it. Mollie shares what the go-to-market engineer role actually is, why career ladders are turning into portfolios, and why she stopped doing case studies in hiring.

We cover:

• From reactive help desk to building and governing the systems that run the business

• AI sprawl: why "give everyone access" now creates a governance problem

• What a go-to-market engineer really is — beyond the LinkedIn hype

• Agent ops: monitoring drift, QA, and cost like DevOps monitors uptime

• Why it's a skill set, not a new job title

• The analyst shift from firefighting to proactive intelligence

• Who should own AI: centralized, federated, or center of excellence

• Flatter orgs, wider spans, and horizontal layers replacing functional silos

• Career paths becoming portfolios instead of ladders

• Why Mollie killed case studies in her hiring process

• Skill vs. will — advice for early-career operators

Mollie Bodensteiner on LinkedIn: https://www.linkedin.com/in/molliebodensteiner/ ZoomInfo: https://www.zoominfo.com Janis Zech on LinkedIn: https://www.linkedin.com/in/janiszech/ Philipp Stelzer on LinkedIn: https://www.linkedin.com/in/philippstelzer/ WeFlow: https://www.weflow.ai/ Join the RevOps Chat Community: https://www.weflow.ai/community Subscribe to the RevOps Letter: https://www.weflow.ai/revops-letter

Book recommendation: The Accountable Organization by John Marchica

Chapters:

(00:00) Intro & welcome back to Mollie

(03:26) How RevOps jobs have changed

(05:30) AI sprawl and the governance problem

(08:43) The go-to-market engineer role

(12:06) Agent ops and the digital workforce

(16:25) What happens to the analyst

(20:30) Who owns AI in the org?

(24:19) Flatter teams, wider spans

(28:20) Making RevOps impact measurable

(31:43) Why case studies are dead in hiring

(34:11) Skill vs. will: advice for operators

(37:07) Book recommendation & close

Colin Gerber, VP RevOps & Strategy at Socure, breaks down 17 years of CPQ evolution — from Zuora's billing-wrapper days to today's consumption-ready, platform-agnostic tools. He shares how Socure pressure-tested its pricing in Excel for a year before building anything, and how a new entitlements object now ties CRM, CPQ, and billing into one source of truth.

We cover:

• CPQ's three eras: Zuora → Salesforce CPQ → platform-agnostic tools like DealHub

• Pressure-testing pricing in Excel before implementing CPQ

• Socure's shift to à la carte, consumption-based pricing across 35 modules

• Common CPQ mistakes: over-complication and workflow bloat

• Scaling SKUs across ~170 countries

• RevOps' role: guardrails, deal desk, pre-deal margin modeling

• Using AI to auto-generate Solution Readiness Documents

• A bi-directional entitlements object unifying CRM, CPQ & billing

• Automated entitlement capture for PLG motions

• A preview of consumption-based forecasting

Colin Gerber on LinkedIn: https://www.linkedin.com/in/colinsgerber/ Socure: https://www.socure.com Weflow: https://www.weflow.ai/ RevOps Chat Community: https://www.weflow.ai/community RevOps Letter: https://www.weflow.ai/revops-letter Janis on LinkedIn: https://www.linkedin.com/in/janiszech/ Philipp on LinkedIn: https://www.linkedin.com/in/philippstelzer/

Book recommendation: Team of Teams: New Rules of Engagement for a Complex World by General Stanley McChrystalChapters: (00:00) Intro & welcome to Colin (01:51) Colin's background (04:23) The three phases of CPQ history (10:00) CPQ challenges with consumption-based pricing (14:12) Common CPQ implementation mistakes (19:03) The role of RevOps in CPQ (21:19) Using AI in CPQ (25:21) Where's the system of truth? (32:26) Direct vs. self-service/PLG (34:44) Teaser: consumption-based forecasting (36:44) Book recommendation & close

Markus Jaensch, Head of RevOps at Aiven, joins Janis and Philipp to unpack what consumption-based pricing actually means for a RevOps team running a $100M+ ARR business. Aiven — the open-source data platform behind managed Kafka, Postgres, OpenSearch, and ClickHouse — recently crossed $100M ARR, and Markus walks through how the forecasting model, comp design, and territory setup have evolved over 4.5 years to deal with the fundamental problem of consumption: a "win" doesn't equal revenue, and the next 12 months can swing either direction.

We cover:

• Why consumption ARR is structurally harder to forecast than SaaS bookings
• Why Aiven moved away from pure ARR forecasting and back to bookings + finance-modeled ARR
• The three forecast buckets: new business, add-on, and commit contracts
• Using MEDDPICC with mandatory mutual success plans and CRM score as a red-flag signal
• T-shirt sizing (S/M/L/XL) with solution architects to anchor opportunity size
• The two non-negotiables to close-won at Aiven: valid payment method + 3 consecutive days of consumption
• Why RevOps owns the close-won gate — and the tradeoff of being a controlling function
• The Farmer/Hunter evolution: from split, to mixed, to dedicated Inside Sales + named-territory Field reps
• Comp design: bookings as a sanity metric, ARR as the paid metric, with new-ARR ramp-to-size
• Stack: Salesforce + data warehouse, and why Aiven switched from spot ARR to a 30-day average
• Building the process around the customer first, not internal convenience

Markus Jaensch on LinkedIn: https://www.linkedin.com/in/markus-jaensch/

Aiven: https://aiven.io

Weflow: https://www.weflow.ai

RevOps Chat Community: https://www.weflow.ai/community

RevOps Letter: https://www.weflow.ai/revopsletter

Janis on LinkedIn: https://www.linkedin.com/in/janiszech

Philipp on LinkedIn: https://www.linkedin.com/in/philippstelzer

Book recommendation: The Café on the Edge of the World by John Strelecky

Chapters:

• (00:00:00) Intro & Welcome to Markus
• (00:02:14) Why Consumption ARR Is the Topic — and Aiven Crossing $100M
• (00:03:39) Why Consumption ARR Is So Hard to Forecast
• (00:08:30) Bookings vs. ARR Forecasting — and Aiven's Evolution
• (00:12:53) MEDDPICC, Mutual Success Plans & Deal Hygiene
• (00:16:21) T-Shirt Sizing with Solution Architects
• (00:18:01) The 3-Day Consumption Rule for Close-Won
• (00:22:28) Modeling the ARR Ramp After a Booking
• (00:26:27) The Farmer/Hunter Evolution & Inside Sales Motion
• (00:29:37) Comp Design: Bookings, ARR, and Ramp-to-Size
• (00:31:00) Stack: Salesforce, Data Warehouse & 30-Day Average ARR
• (00:34:34) Final Learnings on Consumption Forecasting
• (00:36:29) The Customer-First Principle
• (00:38:02) Book Recommendation & Close

In this episode of the RevOps Lab, Janis sits down with Andy Smidmore — a 15-year RevOps and SalesOps veteran whose résumé reads like a tour of high-growth West Coast SaaS (Confluent, Cloudera, Docker, most recently Ditto). Andy is also the author of a popular LinkedIn article series on RevOps fundamentals, including the piece that anchors today's conversation: Forecasting Is a Trust Problem Before a Math Problem. Janis and Andy unpack why the magic forecast number leadership wants is just the surface, why broken sales stages quietly leak forecast accuracy, and why mixing deal reviews into your forecast call destroys the very trust your reps need to be honest with you.

We cover:

• Why forecasting is a trust problem first, a math problem second

• Why the "how much are you committing?" question on day one of a forecast call is the wrong starting point

• Building sales stages around the buyer's journey, not your selling process — and why misaligned stages are a leaking bucket

• The danger of performative deal progression and the false hope it creates for leadership

• Why deal reviews and forecast calls should be two separate motions

• "I'm not questioning you, I'm asking questions" — the subtle reframe that changes the whole room

• Crystal-clear definitions for pipeline vs. commit, kept short (5 bullets, not essays)

• What a true commit actually requires: technical sign-off, legal redlines, procurement engaged, stakeholder alignment

• Why a consistent week-in, week-out forecast format builds rep trust over time

• Treating forecasting as a team sport — and why punishing reps swings them toward concealment, not honesty

Links:

• Andy Smidmore on LinkedIn: https://uk.linkedin.com/in/andy-smidmore-3aab0556

• Andy's article series on RevOps & forecasting (LinkedIn)

• Janis Zech on LinkedIn: https://www.linkedin.com/in/janiszech/

• Philipp Stelzer on LinkedIn: https://www.linkedin.com/in/philippstelzer/

• WeFlow: https://www.weflow.ai/

• Join the RevOps Chat Community: https://www.weflow.ai/community

• Subscribe to the RevOps Letter: https://www.weflow.ai/revops-letter

• Book recommendations:

• Disrupted by Dan Lyons

• The Girl with Seven Names by Hyeonseo Lee

Chapters:

• (00:00) Intro & welcome to Andy

• (00:51) Andy's 15-year journey through Confluent, Cloudera, Docker, Ditto

• (03:08) Why forecasting is the topic — and the article that started it

• (04:03) Why every forecast framework is unique to its company

• (06:15) Intelligence tools haven't replaced the foundational framework

• (08:13) "How much are you committing?" — the surface-level forecast call

• (10:01) The top forecast process problems Andy keeps seeing

• (11:33) Sales stages built around the buyer journey, not the seller

• (12:24) The POC stage problem: what does "done" actually mean?

• (14:25) When poor stage definitions destroy trust between reps and leadership

• (15:43) Creating an open, honest forecast call environment

• (18:17) From gut-based reviews to data-backed conversations

• (20:22) Why deal reviews and forecast calls must be separate motions

• (23:25) "I'm not questioning you, I'm asking questions"

• (25:00) The cadence: clean pipeline Thursday, deal review Friday, forecast Monday

• (28:32) Building a clear forecasting methodology — pipeline vs. commit

• (31:34) What actually constitutes a commit deal

• (35:21) Closing thoughts: stages, enablement, cadence, culture

• (39:35) Book recommendations & close

In this host-only episode of the RevOps Lab, Janis and Philipp take stock of what three years of building a forecasting tool — and hundreds of conversations with sales leaders, RevOps teams, and CROs — have taught them about getting to a reliable, repeatable forecast number. They unpack why forecasting is a process (not a number), why AI only works on top of a clean data foundation, and how the best companies combine roll-up, dynamically weighted, and AI-predicted forecasts into a single operating cadence.

We cover:

• Why forecasting accuracy is the output of a well-run sales org, not the input

• The operating cadence: weekly meetings, deal reviews, and stakeholder alignment that make forecasting work

• Building the data foundation: activity capture, multi-threading signals, conversation intelligence, and CRM autofill

• Why deal hygiene and shared qualification criteria (SPICED, MEDDIC) are non-negotiable before you forecast

• Splitting the forecast into new logo, expansion, and renewal — and why bookings ≠ consumption

• The three-pillar forecast: dynamically weighted + bottom-up roll-up + AI prediction (with corridors, not single numbers)

• How to run a roll-up motion: baseline vs. best case, rep forecast vs. independent manager forecast

• Why running roll-ups in spreadsheets breaks down at 50+ reps

• Calculating dynamic stage probabilities by rep tenure or team — and when it's worth doing

• Why AI predictions are only as good as the data foundation underneath them

Links:

• Janis Zech on LinkedIn: https://www.linkedin.com/in/janiszech/

• Philipp Stelzer on LinkedIn: https://www.linkedin.com/in/philippstelzer/

• WeFlow: https://www.getweflow.com

• WeFlow RevOps resources: https://www.getweflow.com/revops

• Join the RevOps Chat Community: https://www.getweflow.com/community

• Subscribe to the RevOps Letter: https://www.getweflow.com/revops-letter

• Operating Cadence master deck: ping Janis or Philipp on LinkedIn to request

Chapters:

• (00:00) Intro: Has AI fundamentally changed forecasting?

• (01:34) Why forecasting is a process, not a number

• (02:25) What an operating cadence actually looks like week-to-week

• (04:23) The data foundation: why CRM alone isn't the system of truth

• (06:53) Anchoring deal conversations on a shared qualification methodology

• (08:42) How AI adds an objective layer through automated capture and CRM autofill

• (09:29) Stage entry/exit criteria and deal signals for deal health

• (13:06) Why "comparable deals" matters as you scale past 50 reps

• (14:23) Forecasting as the end result of a well-functioning sales org

• (16:05) Splitting forecasts: new logo, expansion, renewal, bookings vs. consumption

• (17:22) The three-pillar forecast: dynamically weighted, roll-up, AI prediction

• (18:50) Roll-up forecasting: baseline vs. best case, rep vs. manager numbers

• (24:07) Anatomy of a roll-up: hierarchy, gap-to-quota, pipeline coverage, deal-by-deal

• (26:43) Why spreadsheets break down for roll-up forecasting at scale

• (28:07) AI prediction models: aggregate vs. deal-by-deal scoring

• (29:02) Dynamically weighted forecasts and rep-level stage probabilities

• (32:44) Why AI predictions only work on top of clean data foundations

• (34:27) Book recommendation & close

In this episode of the RevOps Lab, Janis and Philipp sit down with Robert Kaiser and Christoph Dünhuber from Tacto — the Sequoia- and Index-backed AI procurement platform powering 300+ industrial customers across the German Mittelstand. Robert leads revenue functions, Christoph leads RevOps. Together they unpack how Tacto scaled to 130 employees by making customer value the center of gravity across every revenue function — from BDR to renewals — and why "customer-centric" only works when it is operationalized, not just stated.

We cover:

• Why customer value (not org design) is priority #1 in a scaling revenue org

• How webinars with 200–500 weekly attendees became Tacto's top-of-funnel engine

• The "Customer Internship" program: every new hire spends 2–3 days embedded with a customer

• Why marketing and outbound are converging — and how to make cold outreach feel warm

• Selling to dual personas: the procurement team (user) vs. the MD/CFO (economic buyer)

• How forward-deployed Customer Value Managers (ex-BCG, ex-Roland Berger) drive renewals and expansion

• Why 70–80% of new Tacto customers speak to an existing customer before signing

• Building a value-engineering motion that makes ROI tangible inside the sales cycle

Links:

• Tacto: https://tacto.ai

• Robert Kaiser on LinkedIn: https://www.linkedin.com/in/-robert-kaiser/

• Christoph Dünhuber on LinkedIn: https://www.linkedin.com/in/christophduenhuber/

• Janis Zech on LinkedIn: https://www.linkedin.com/in/janiszech/

• Philipp Stelzer on LinkedIn: https://www.linkedin.com/in/philippstelzer/

• WeFlow: https://www.getweflow.com

• Join the RevOps Chat Community: https://www.getweflow.com/community

• Subscribe to the RevOps Letter: https://www.getweflow.com/revops-letter

• Book recommendation: The Qualified Sales Leader by John McMahon

Chapters:

• (00:00) Intro & welcome

• (01:36) Meet Robert & Christoph — their paths at Tacto

• (03:13) What Tacto does and the $500M procurement opportunity

• (07:47) Why customer-centricity is a two-sided coin (users + economic buyers)

• (10:24) The Tacto customer journey: from webinars to account management

• (15:44) Org design for scale: renewals, upsells, expansion leads

• (17:00) Selling to procurement vs. selling to the managing director

• (19:43) How outbound stays customer-centric when brand and webinars lead

• (23:24) Customer Internships: every new hire embeds with a customer

• (28:00) Hiring for cultural fit and the "warm calling" academy

• (29:35) Referrals and why 70–80% of new customers speak to existing ones

• (31:10) Dual-persona strategy: power user vs. economic buyer

• (32:49) How a CX mindset reshaped Tacto's entire sales motion

• (35:21) Org design deep dive: SEs, Value Engineers, CVMs

• (37:39) Book recommendation & close

Eric Portugal Welsh, Head of RevOps at PlanetScale and returning guest on the RevOps Lab, joins Janis and Philipp to share how he went from leading a team of six to operating as a solo RevOps function — and how AI is making that possible. Eric walks through his full AI stack, his vibe coding journey, and the specific agents and workflows he's built to automate everything from pipeline reviews to stakeholder communication to onboarding himself at a new company.

We cover:

• Going from a RevOps team of six to a team of one — and why that's the PlanetScale model

• The full AI stack: Claude, Cursor, Cowork, Gemini, Notion AI — and when to use which

• How Eric onboarded himself in days instead of weeks using Claude and Notion agents

• Vibe coding a full pipeline dashboard from a single Salesforce history report in 90 minutes

• Why PlanetScale's head of finance hasn't opened Excel in months — everything is vibe coded

• Building agents for weekly status updates, pipeline prep, and Slack-based Q&A

• A communication agent that mirrors the COO's tone and preempts his questions

• The Monday morning pipeline agent: auto-generated executive overviews before the 8:30 call

• Why VPs of sales and CROs are the heaviest AI users — not the reps

• How the CRM interaction model is shifting from reports and record pages to chat interfaces

• Practical vibe coding tips: build an acceptance criteria doc first, then prompt the build

• The scaling challenge: why open data works at 65 people but breaks at 500+

• RevOps as the orchestration layer for AI-powered go-to-market workflows

Eric Portugal Welsh on LinkedIn: https://www.linkedin.com/in/ericwelsh1/ 

PlanetScale: https://www.planetscale.com 

Weflow: https://www.getweflow.com 

RevOps Chat Community: https://getweflow.com/community 

RevOps Letter: https://www.getweflow.com/revopsletter 

Janis on LinkedIn: https://www.linkedin.com/in/janiszech 

Philipp on LinkedIn: https://www.linkedin.com/in/philippstelzer

Chapters: 

(00:00:00) Introduction & Eric's Return to the Pod 

(00:00:53) From Deputy to PlanetScale: RevOps Team of One 

(00:03:45) The Full AI Stack: Claude, Cursor, Gemini, Notion AI 

(00:05:05) Self-Onboarding with AI: Days Instead of Weeks 

(00:08:40) Claude vs. Gemini vs. ChatGPT: What Works Best 

(00:11:45) Vibe Coding a Pipeline Dashboard in 90 Minutes 

(00:12:20) PlanetScale's Head of Finance: Zero Spreadsheets in Months 

(00:13:25) Getting Started with Vibe Coding: Tips for RevOps 

(00:17:55) Practical Tip: Build Acceptance Criteria Before Prompting 

(00:19:15) More AI Use Cases: Cloning Yourself as a Team of One 

(00:21:05) Weekly Status Agents & Notion-Based Slack Q&A Bots 

(00:23:10) The Monday Morning Pipeline Agent 

(00:24:20) Communication Agent: Matching the COO's Tone & Style 

(00:25:45) Context: 65-Person Company, 85% Engineers, Open Data Culture 

(00:27:10) Why This Will Come to Every RevOps Team — and the Scaling Challenges 

(00:29:20) Agentic Content Creation for Outbound Sequences 

(00:31:30) Why VPs of Sales Are the Heaviest AI Users 

(00:33:45) The Future: Chat-Based CRM Interaction Over Reports and Record Pages 

(00:36:00) RevOps as the AI Orchestration Layer 

(00:37:05) Book Recommendation & Wrap-Up

Stephen Diorio, author of "Revenue Operations" and a go-to-market strategy veteran with decades of experience — from co-founding one of the first GTM strategy firms in 1993 to serving as a Gartner analyst — joins Janis and Philipp to unpack the math of growth. Stephen explains why the financial systems behind most B2B organizations fundamentally fail to measure what actually drives revenue, and how RevOps can close the gap between what the business spends on growth and what it actually gets back.

We cover:

• Why traditional accounting treats all go-to-market spend as expense — and why that's fundamentally wrong

• Growth assets: databases, brands, digital channels, content — and why no one measures their value

• The bow tie model: what it captures, what it misses, and why the back end is where CFOs get scared

• Why a third of closed deals originate from actions taken 12–18 months earlier

• The 25 post-booking variables that can double or halve lifetime customer value

• Why "cost to sell" has 100 definitions across 100 companies — and none are right

• The dark funnel and LLM search: why 90% of the buying process is invisible

• Forward-looking vs. backward-looking signals: product telemetry, adoption, and renewal prediction

• The nine customer behavior changes that every growth investment ultimately drives

• Why documenting assumptions — not just measuring outcomes — is the key to continuous improvement

• Treatment models and customer experience: why no one can answer "what does a good CX cost?"

• Share of wallet and account penetration: the massive untapped opportunity most orgs can't quantify

Stephen Diorio on LinkedIn: https://www.linkedin.com/in/stephen-diorio-1339011/

Revenue Operations (Book): https://www.amazon.com/Revenue-Operations-Stephen-Diorio/dp/1119871115 

Weflow: https://www.getweflow.com 

RevOps Chat Community: https://getweflow.com/community 

RevOps Letter: https://www.getweflow.com/revopsletter 

Janis on LinkedIn: https://www.linkedin.com/in/janiszech 

Philipp on LinkedIn: https://www.linkedin.com/in/philippstelzer

Chapters: 

(00:00:00) Introduction 

(00:00:32) Stephen's Background & Why He Wrote the RevOps Book 

(00:02:45) The Math of Growth: Why It's One Big Equation 

(00:03:25) Growth Assets: Brands, Data, Channels — and Why No One Values Them (00:05:10) Why Financial Accounting Fails Go-To-Market 

(00:07:10) Cost to Sell: 100 Companies, 100 Definitions 

(00:09:35) Walking Through the Bow Tie: Top of Funnel to Post-Sale 

(00:11:40) Why We Overplay Conversion Rates and Underplay the Dark Funnel (

00:13:00) The Back End of the Bow Tie: Where CFOs Get Scared 

(00:15:10) Reliable Cash Flow as the North Star Metric 

(00:16:00) Account Penetration & Share of Wallet: The Untapped Opportunity 

(00:18:10) Treatment Models: What Does a Good Customer Experience Actually Cost? 

(00:20:05) Reliable vs. Accurate Revenue: Why Sandbagging Kills Forecasting 

(00:22:30) The Scientific Method: Document Assumptions, Then Test and Adjust 

(00:26:35) Dark Funnel, LLM Search & Why 90% of Buying Is Invisible 

(00:30:05) Forward-Looking Signals: Product Telemetry and Adoption Data 

(00:32:05) The Nine Customer Behavior Changes That Every Growth Investment Drives 

(00:35:25) Brand as an Asset: Touch Points, Awareness, and Future Option Value 

(00:37:05) Book Recommendation: The Goal by Eli Goldratt

Franco Anzini, a seasoned revenue operations leader with experience across companies of all stages and go-to-market motions, joins Janis and Philipp to talk about a principle that doesn't show up on any dashboard: stay close to where the money changes hands. Franco shares why RevOps professionals need to step away from the data, get into the field, and understand the art behind the science — and how that context is what ultimately separates tactical operators from strategic leaders.

We cover:

• What "stay close to where the money changes hands" means in practice for RevOps

• Why data alone doesn't tell the full story — and how field context fills the gap

• Practical ways to get into the field: joining sales calls, attending QBRs, shadowing reps

• Why salespeople are almost always thrilled when RevOps wants to join their meetings

• How understanding the customer journey end-to-end makes RevOps more strategic

• The churn example: when health scores looked great but customers still left

• Why the current market shift — from ZIRP to AI-first — demands even more field context

• Career pathing from RevOps to COO or CRO: why business context is the missing ingredient

• When to roll up your sleeves vs. when to step back: signals and time management

• Using conversation intelligence and transcripts as a complement — not a replacement — for field presence

• Why conferences are the fastest way to absorb dozens of live sales interactions

Franco Anzini on LinkedIn: https://www.linkedin.com/in/francoanzini 

Weflow: https://www.getweflow.com 

RevOps Chat Community: https://getweflow.com/community 

RevOps Letter: https://www.getweflow.com/revopsletter 

Janis on LinkedIn: https://www.linkedin.com/in/janiszech 

Philipp on LinkedIn: https://www.linkedin.com/in/philippstelzer

Chapters: 

(00:00:00) Introduction 

(00:00:35) Franco's Background in Revenue Operations 

(00:02:12) What "Stay Close to Where the Money Changes Hands" Means 

(00:05:40) Tactics for Getting Into the Field 

(00:09:00) Why RevOps Should Join Sales Calls — and Why Reps Love It 

(00:11:45) Understanding the Full Customer Journey as RevOps 

(00:14:00) Career Pathing: From RevOps to COO and CRO 

(00:15:55) Real Example: When Health Scores Lied About Churn 

(00:19:00) The Changing Market Context: ZIRP to AI-First Era 

(00:21:30) How Field Context Makes RevOps More Strategic 

(00:22:45) When to Roll Up Your Sleeves — and When Not To 

(00:25:20) Time Partitioning: SKOs, QBRs & Natural Touchpoints 

(00:26:50) Conversation Intelligence as a Complement to Field Presence 

(00:27:45) Fast Track: Join Salespeople at Conferences 

(00:28:45) Advice for Overwhelmed RevOps Teams 

(00:30:50) Book Recommendation: Legacy by James Kerr