Picture a go-to-market (GTM) stack assembled one purchase at a time. Sales has a call recorder, an outreach platform, and a CRM. Marketing has automation and account-intent tools. Product has an issue tracker and a feedback board. RevOps has spreadsheets and whatever custom dashboards they've built this quarter.
We call this the Frankenstack — a cobbled-together collection of tools that can each do useful work while leaving the team to connect the pieces.
The Real Cost of Fragmentation
The cost is not just the software licenses. To understand the bill, look at three kinds of work that fragmentation can create:
1. Lost Context
A sales rep records a call. Marketing writes a competitive analysis in a separate document. Unless an integration or a person connects them, the rep and marketer may miss that they are dealing with the same competitor and hearing the same objection.
Lost context means duplicated work, missed connections, and slower response times.
2. Manual Integration Tax
Someone has to stitch the Frankenstack together. That work may land with RevOps: building automations, maintaining custom integrations, and reconciling records across tools. Measure those hours in your own team rather than borrowing a universal percentage.
That's not intelligence work — it's plumbing. API changes, mismatched fields, and failed syncs can turn that plumbing into recurring maintenance.
3. Missed Chances to Reuse Knowledge
Here is the less visible cost: useful knowledge may not reach the next decision. Your CRM can hold call notes, and your content platform may connect to it. But can a marketer trace a proposed headline to buyer language? Can product find the calls behind a recurring request? Stored context is not necessarily reusable context.
The team keeps paying to rediscover what it already heard.
What "Consolidation" Actually Means
We're not saying throw away all your tools. Gong is great at recording calls. Salesforce is great at managing pipeline. HubSpot is great at marketing automation.
Where those connections are missing, an intelligence layer is one approach: a system that can
- Ingest selected data from across your stack
- Extract candidate entities, relationships, and patterns
- Build a connected knowledge graph
- Support questions across the connected sources, with source references for review
This is the aim of GTM Intelligence: make selected knowledge reusable across the stack. It still adds software, integration work, and maintenance. Judge it by the decisions it helps, not the number of tools it claims to replace.
The Compound Alternative
Imagine keeping your specialist tools while connecting selected sources in a knowledge graph that records:
- Relevant people, companies, and products extracted from the sources you permit
- The relationships between them
- How those relationships change over time
- What patterns emerge when you connect sales conversations with marketing campaigns with product feedback
That's the compound alternative. Not a better CRM or a better content tool — a fundamentally different approach to how GTM teams capture and use intelligence.
Making the Shift
You don't need to rip and replace your stack overnight. The shift happens in three stages:
- Connect — Start with selected data you are permitted to use (call transcripts, documents, notes) and a question worth answering
- Review — Check extracted entities and relationships against their sources; correct duplicates and unsupported links
- Reuse — Apply the reviewed knowledge to a battle card, brief, or product decision; keep what helps and retire what goes stale
The Frankenstack problem is not just tool count. It is the missing path from a useful observation to the next person who needs it. Start with one path you can inspect, whether you connect it through software or a better handoff.