Treading

Cream

A GTM Engineering Consultancy

A team of experienced enterprise sales and semi-technicals who asses, design and guide your GTM engineering strategy.

How Treading Cream supports companies with GTM engineering

evaluating GTM Engineering and require analysis on suitabillity

evaluating GTM tech and require independant advice based on experience

implemented GTM engineering stack and need to accelerate results

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Before you invest in GTM technology, understand the commitment.

We assess how new tools will integrate with your existing sales and marketing operations, identifying conflicts, redundancies, and required process changes before you commit.

What we evaluate:

Your current tech stack and data workflows, where structured CRM data and dynamic sales intelligence intersect, and where gaps exist
Team alignment, how rev ops, sales, marketing, and customer success currently use data, and what needs to change for GTM tools to work.
Implementation readiness, your team's capacity for change, budget constraints, and realistic ROI expectations.

Our deliverable:

A clear assessment of whether GTM engineering fits your business, which tools to adopt, and what organizational changes are required - so you can make an informed decision before spending a dollar.

The GTM tech ecosystem has 100+ tools claiming to solve the same problems - most companies end up overpaying for duplicate functionality.

Data enrichment, sequencing, AI personalization, LinkedIn automation, email warming. Every solution promises a turnkey approach. The reality: you need 5-8 tools working in harmony, but choosing the wrong combination leads to workflow chaos and budget bleed.

What we evaluate:

Your required workflows, from prospect identification through enrichment, personalization, sequencing, and delivery. Where your team needs automation versus human input.
Which solutions are currently necessary, which solutions are nice to have. Future proofing your GTM stack.
Integration architecture, how data flows between platforms like SFDC, Clay, Gong and sequencers. The creation of email.
Total cost of ownership, subscription fees, seat licenses, API costs, and the hidden expenses of maintaining complex integrations.

Our deliverable:

A mapped workflow showing exactly which tools to use for each function, total costs, integration requirements, and implementation sequence - eliminating guesswork and redundant spend before you sign contracts.

You've invested in GTM engineering, but results have plateaued - the problem isn't the concept, it's the execution.

Most stalled GTM implementations fail for predictable reasons: wrong tool combinations creating data silos, semi-technical hires who lack sales context, enrichment tables pulling irrelevant signals, or broken integrations causing manual workarounds that defeat automation's purpose.

What we evaluate:

Your current stack utilization - which tools are underperforming or redundant, where integrations are failing, and what capabilities you're paying for but not using effectively.
Data architecture - whether your Clay tables are structured for scale, if you're enriching the right signals for your ICP, and where data quality breaks down between enrichment and outreach.
Team capability gaps - whether your GTM operators understand sales strategy or just tool mechanics, and what skills need upgrading versus hiring.
Workflow bottlenecks - where manual intervention is slowing automation, which processes can be eliminated versus optimized, and what's blocking your path from 100 to 1,000 accounts per week.

Our deliverable:

A diagnostic assessment identifying exactly what's broken, what to fix versus replace, required team development or hiring, and a sequenced roadmap to unlock the scale you expected - turning your stalled investment into a revenue engine.

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The importance of getting it right

Traditional outbound fails because it's seller-timed, not buyer-ready - and the cost of getting this wrong is wasted spend at scale.

Most outbound campaigns launch when your team has a new feature, quota pressure, or a list to burn through. The trigger is internal. The data source is your CRM - static job titles, outdated contact info, and zero insight into whether prospects are actually in-market.

GTM engineering flips this: campaigns trigger when buyers signal intent through their digital behavior - hiring for specific roles, visiting competitor sites, posting about problems you solve, or engaging with relevant content. The data source is dynamic: web activity, job postings, LinkedIn engagement, tech stack changes.

Pre GTM Engineering

A traditional static data engagement sequence before before implementing GTM Engineering

With GTM Engineering

Know what good looks like

From silo to a single functional objective

Traditional revenue teams operate with conflicting KPIs - SDRs chase meeting quotas, marketing pursues MQLs, RevOps manages processes, AEs focus on close rates. The result: duplicated tech, inconsistent prospect engagement, and metrics that look good in isolation but don't drive revenue.

GTM engineering eliminates silos by making signal-based engagement the single starting point. Signals trigger automation, automation enriches data into your CRM, and AEs receive prospects who are genuinely in-market and properly contextualized.

One functional team. One data source. One objective: converting accounts that match your ICP and exhibit buying signals.

The outcome: KPI conflicts disappear, tech costs reduce through consolidation, prospect experience improves, and revenue increases without adding headcount.

The risk: Most companies attempt this without assessing team readiness or redesigning workflows first - which is why siloed teams resist GTM adoption even when leadership mandates it.

Pre GTM Engineering

With GTM Engineering

A sales support structure after the implementation of GTM Engineering.

Transition from silo to team

Tech we engage with weekly, if not daily.

Schedule a call today

Customers

Know how to implement today