Helping B2B buyers research smarter and faster | Host of the B2B Uncovered podcast

I work with high-growth B2B companies where buying is complex, multi-stakeholder, and rarely linear.

After 20+ years in marketing and sales, across startups, scale-ups, and enterprise teams, I kept seeing the same issue:

Most revenue teams can measure activity.
Few can explain whether buying alignment is actually forming inside their target accounts.

* Signals get mistaken for readiness.
* CRM stages for momentum.
* Enthusiastic champions for commitment.

When alignment is misclassified, pipeline feels unpredictable — even when dashboards look healthy.

To address this, I developed the Demand Momentum model: a way of interpreting how accounts move before opportunity creation.

It focuses on:

• Where an account truly sits
• What evidence supports that classification
• What would constitute real progression
• When regression needs to be recognised

GoGTM operationalises this thinking inside defined account universes.

We apply structured classification, buying-group visibility, and signal interpretation to make account movement legible before pipeline is created.

This work is suited to growth-stage B2B companies with meaningful ACV and cross-functional buying groups — where alignment across roles determines outcomes.

If that environment sounds familiar, we should talk.

📍 Based in London. Work globally.

Paul Denham

Philippe Ruttens

I help PE/VC operating partners and founder-led B2B firms fix broken revenue &amp; marketing engines in 90–180 days. Through my revenue &amp; GTM audit followed by a 3–6 month transformation sprint, I clean your CAC/LTV and pipeline metrics investors trust, rebuild GTM and AI‑enabled operations, and embed dashboards and playbooks that boards can rely on.What I deliver:- 90-day Revenue &amp; GTM Audit: Clean CAC/LTV and pipeline metrics, expose leaks, identify 3 key growth levers. Portfolio companies move from hopeful projections to investor-grade dashboards.- 180-day Revenue Engine Transformation: Rebuild ICP, positioning, messaging, GTM plays and AI‑enhanced workflows; embed playbooks so teams run the system after I leave.- Fractional, Interim (Open to Perm) CMO &amp; Board Advisory: 1–4 days/week hands-on leadership linking marketing fixes to valuation, multiples and exit stories.My experience &amp; credentials:- Over 25+ years (Accenture, EY, Tyk, MasterCard and 30+ B2B brands), I've:- Delivered 200–500% proven marketing ROI for B2B clients with clear attribution and board-ready reporting- Achieved 10%+ operational efficiency gains in C-suite-led change programs, improving team performance and budget control- Led and transformed 3-5 marketing teams up to 25+ FTE, modernising GTM stacks for the digital age- Designed and co-delivered demand gen across 10+ countries and 19 websites, spanning inbound and outbound channels- Trained 200+ executives in social branding and selling; improved win rates for 10+ key account teams through ABM- Built marketing &amp; sales intranet for 400 sales managers; established competitor intelligence serving 500+ internal stakeholders- Worked across Big 4 consulting (Andersen/Accenture, EY, Capgemini) plus 12 years as freelance senior consultant and interim/fixed marketing &amp; comms leader- Grounded expertise in 5 years of knowledge management and market intelligence—ensuring a data-driven approach to CAC/LTV, pipeline and GTMRecognition: 45+ LinkedIn recommendations across sectors and rolesFeatured by CMO Alliance as a "CMO to Watch 2025" — as trailblazer shaping the future of B2B marketingLet's turn your investor pressure &amp; lack of autonomy into pipeline—fast. Let's explore your ROI and boost your 2026 performance in a 15-mins call --&gt; www.ruttens.com

Chief Marketing Officer (CMO)

We're on a mission to connect every system in the world.

From USA Today to Tripadvisor, from Vietnam to New York, thousands of businesses are harnessing the power of APIs using Tyk. Over 15 billion “things” are connected to the internet, growing at a rate of a billion per year and APIs are at the centre of this explosion in connectivity. Tyk is committed to enabling interconnectivity between systems and devices and breaking down the barriers to API Adoption.

My goal as CMO is to grow Tyk’s ecosystem, customers and revenue, making Tyk the world’s most loved brand for interconnectivity and API management.

My personal “WHY” is to create stronger & healthier teams, operations and people with a 100% focus on customer-centric growth and measurable impact.

CMOs need to sustainably grow brand demand and revenue pipeline by leveraging data, market and customer insights, user & influencer communities at each stage of their career and journey. My core responsibilities include:
1.	Build a world-class integrated marketing team and customer-centric function 
2.	Grow and report on main marketing & sales KPIs, from brand awareness to full-funnel conversion and velocity 
3.	Align internal product & commercial stakeholders around common goals, operations and buyer journey
4.	Leverage data, analysis and learnings from each touchpoint (customers, partners, prospects, users) to fine-tune targeting, messaging and value proposition(s) 
5.	Develop short- & long-term roadmap for marketing planning and execution
6.	Optimize marketing strategies & campaigns, from messaging and content to channels and dashboards
7.	Oversee development & execution of thought leadership and communications programs at global, regional and local levels

More info on www.tyk.io 
Get Started on https://tyk.io/sign-up/

Most B2B CMOs get stuck: lots of AI activity, very little pipeline causality.

Teams actually improving ROI are the ones who:

1- Tie AI use to 2–3 business KPIs (pipeline velocity, SQO rate, CAC payback), not login dashboards

2- Run incremental tests at task → workflow → revenue level, then kill AI experiments that don’t move margin or cycle time

Boards still ask for “AI adoption” slides, so marketing leaders need a dual view:

A- Visible adoption metrics for governance 
B- Hard cause‑and‑effect story for pipeline and revenue

​Linking promotions to AI logins feels like the perfect case study in Goodhart’s Law: 

When the metric becomes the target, the metric stops telling you anything useful.
​
What I’m seeing in B2B mid‑market and PE‑backed firms is that AI only creates real value when it is wired into:

- Deal and pipeline metrics (win rate, ASP, sales cycle), not generic “usage”

- Clear before/after baselines for specific motions – e.g. qualification, proposal creation, campaign optimisation – prove uplift, not just experimentation

The uncomfortable truth is: if CMOs can’t show AI’s impact on pipeline, CAC and payback, those login charts will look great right up to the next budget cut.

 
FYI more marketing & GTM ROI tips in my THEMARKETAIR newsletter https://lnkd.in/eJqH8Afx
​
Thx again Darlene Newman

📈 I help PE/VC portfolio & founder‑led B2B midsize firms fix broken revenue & marketing engines in 90–180 days | ROI 25 yrs 10+ sectors 45 Recomms | Fractional, Interim, Perm CMO | ex-Accenture & EY 📣 Speaker & Coach

Strategic partner for leaders’ most complex challenges | AI + Innovation + Digital Transformation | From strategy through execution

The AI ROI measurement problem isn't just your problem. It's everyone's problem, even those that claim to be experts in AI.

Accenture tells clients… measure outcomes, not AI usage.

Yet, they just rolled out an internal policy tying senior promotions to weekly AI login frequency.

Take a second with that. Then keep reading… because this isn't about hypocrisy. It's about how hard transformation measurement actually is.

This is the same Accenture that co-published an AI maturity framework with Carnegie Mellon just two months ago… explicitly built around moving organizations beyond hype-driven experimentation toward measurable outcomes.

Two months of telling clients how to measure ROI… yet, their measurement of performance is related to how much a senior leader logs in to an AI tool. Not whether those logins were worth the cost of the tool.

A login tracker doesn't prove usage, doesn't prove innovation, and certainly doesn't prove the work got better.

I'm not dunking on one firm. I'm pointing out what every organization does under pressure… we revert to what's visible. Logins are visible. Adoption dashboards look good in a deck. Activity feels like progress.

Even the best of the best argue for alternatives to checkins:

🔹 McKinsey says winning companies embed AI into workflows and track business KPIs, not deployment counts.
🔹 Gartner called activity metrics out directly… they don't translate to boardroom value.
🔹 Berkeley researchers put it plainly… we're not in an AI failure era. We're in a measurement failure era.

The problem isn't that Accenture, or any other organization is lying about progress in AI. It's that we genuinely don't know how to measure the middle… the space between "tool was accessed" and "business improved."

So we take the easy route.

But there are ways... and it's how innovators always measure... incrementally.

1️⃣ Prove it changes the work

Before anything else, is the task itself different? Time to output. Error rate. Rework cycles. Quality against a baseline. This is your proof of concept at the individual task level. Not "did they log in" but "did output positively change."

2️⃣ Prove it changes the workflow

One person using AI quietly doesn't transform a process. Look at end-to-end cycle time. Handoff friction. Exception rates. Throughput. This is where you see whether AI has actually changed how a team operates, or whether the process around them is still broken.

3️⃣ Prove it changes the business

Now you have causality. Connect it up the chain. Revenue influenced. Cost per transaction reduced. Margin impact. Risk reduction. This is what earns leaders the seat at the table.


Each step builds evidence. Each step tells you whether to keep going. 

If you measure activity, you will optimize for activity, not whether that activity made any positive change. 

This isn't easy by all means. But you need the to measure what's hard to see, not just what's easy to track.

Links to sources in comments.

AI is no longer a “feature experiment” in SaaS...

It’s already moving revenue, seats and margins for incumbents.
​
In 35 recent SaaS earnings calls (Sammy Abdullah Blossom Street Ventures article link in comment), leaders are reporting hard numbers, not hype:

- Atlassian’s AI assistant Robo  passed 5M MAUs and AI users expand seats faster than non‑AI users
​
- ServiceNow has >$600M ACV from Now Assist, with multi‑product AI deals up 10x YoY
​
- Waystar prevents $15B+ in claim denials with AI and drives double‑digit improvement in overturn rates.
​
Two themes I see for VC‑ and PE‑backed B2B software companies:

1️⃣ Your moat is your data, not your model

Executives keep repeating the same thing: their proprietary, trusted data is what makes their AI products defensible and hard to copy.
​
If you sit on rich workflow, billing, usage or customer interaction data and you’re not actively productizing it into AI‑native experiences, you’re leaving enterprise value on the table.

2️⃣ Agentic AI > “chatbot sprinkled on top”

The most interesting stories were not about chat interfaces, but about agents that act: 

Qualys validating vulnerabilities, BILL executing payments, BlackLine supervising an “agentic workforce,” ServiceNow adding kill switches for misbehaving agents.
​
That’s where efficiency, NRR and pricing power start to move meaningfully.

For founders, GTM leaders and boards, this raises three practical questions:

1- Where in your existing workflows can an AI agent safely take action, not just generate text?

2- How will you turn your proprietary data into a product moat your competitors cannot quickly replicate?

3- How do you adapt GTM (positioning, packaging, pricing, sales enablement) so AI is tied to clear revenue, not just a cool demo or just efficiency outcomes?

If you’re a VC/PE‑backed B2B company and want to stress‑test your AI narrative, roadmap and GTM, you need help to focus on: 

Aligning product, revenue, and board expectations around an AI‑powered growth story that actually shows up in your next earnings call.

Happy to share a 30‑minute perspective on how the patterns in these 35 earnings calls map to your own context, just DM me...

Not 2030 but 2035 maybe, fasten your seatbelts;) enjoy the ride & happy Friday all!

Thx Maël Garcia for sharing, made me smile

Directeur conseil @Brainsonic l IA Générative (GenAI) l Social Medial & Influence l Brand Content l Employee Advocacy l l Com Interne

Voici une façon étonnante et maline de parler d'un sujet crucial dans le domaine de l'#IA ! 

Crédit : AiCandy

TEAM Brainsonic
Mathieu Crucq - Baudouin Demanche - Morgan LOIR - Cyril Dhénin - Arthur Dufour - Paul Bouillard

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