B2B Data Tool Stacks: What's Used Together (2026)
We analyzed 1,172,946+ job postings across 113,894 companies to find which B2B data tools appear together most often. When companies hire for one tool, which others show up in the same job description?
Key Findings
Top 20 Tool Pairings by Co-mention Count
When two tools appear in the same job posting, it signals that companies use them together. Higher co-mention counts mean more companies are building stacks around this combination.
| Rank | Tool A | Tool B | Co-mentions | |
|---|---|---|---|---|
| 1 | Power BI | + | Tableau | 3,960 |
| 2 | HubSpot CRM | + | Salesforce CRM | 2,130 |
| 3 | pytorch | + | Tensorflow | 1,952 |
| 4 | Tableau | + | Salesforce CRM | 1,429 |
| 5 | claude | + | Gemini | 1,401 |
| 6 | claude | + | Openai | 1,217 |
| 7 | openai | + | Anthropic | 1,184 |
| 8 | Power BI | + | Salesforce CRM | 1,122 |
| 9 | claude | + | Anthropic | 1,065 |
| 10 | gemini | + | Openai | 941 |
| 11 | Tableau | + | Looker | 898 |
| 12 | openai | + | Langchain | 757 |
| 13 | Salesforce CRM | + | Salesforce Marketing Cloud | 634 |
| 14 | Salesforce CRM | + | Claude | 613 |
| 15 | Salesforce CRM | + | Marketo (Adobe) | 603 |
| 16 | pytorch | + | Langchain | 602 |
| 17 | gemini | + | Anthropic | 597 |
| 18 | Salesforce CRM | + | ZoomInfo | 573 |
| 19 | claude | + | Langchain | 568 |
| 20 | langchain | + | Llamaindex | 568 |
Most Connected Tools
Which tools show up alongside the widest variety of other tools? A high partner count means a tool is central to many different stack configurations, not just one dominant pairing.
| Rank | Tool | Unique Partners | Total Co-mentions |
|---|---|---|---|
| 1 | Salesforce CRM | 210 | 17,469 |
| 2 | HubSpot CRM | 149 | 7,259 |
| 3 | claude | 127 | 9,907 |
| 4 | Tableau | 123 | 9,207 |
| 5 | Power BI | 107 | 8,168 |
| 6 | Looker | 88 | 3,264 |
| 7 | gong | 87 | 2,064 |
| 8 | ZoomInfo | 84 | 2,732 |
| 9 | Zapier | 76 | 1,615 |
| 10 | gemini | 74 | 6,381 |
| 11 | openai | 73 | 8,329 |
| 12 | Clay | 71 | 1,492 |
| 13 | Marketo (Adobe) | 69 | 2,304 |
| 14 | langchain | 62 | 8,003 |
| 15 | G2 | 61 | 1,075 |
What This Tells Us
The single strongest signal in the data is that Salesforce is the center of gravity for B2B tool stacks. It co-occurs with more tools, more often, than anything else. HubSpot is the second most connected, but with roughly half the partner breadth. If you're building a B2B data stack in 2026, the first question is still "Salesforce or HubSpot?" and everything else branches from that decision.
The Salesforce + HubSpot pairing itself is the most common co-mention by a wide margin. That might seem contradictory, since they're both CRMs, but it reflects a real pattern: companies that use Salesforce as their enterprise system of record still reference HubSpot for marketing automation, onboarding smaller teams, or managing inbound leads before they hit the main CRM. It's not "either/or" in practice.
Analytics tools form a tight cluster. Tableau and Power BI co-appear more than almost any other non-CRM pairing, suggesting that companies don't pick one BI tool and stop. They maintain both, often for different teams or use cases. Looker rounds out a three-way analytics stack that shows up across dozens of job postings.
The sales engagement layer (Salesloft, Gong, LinkedIn Sales Navigator) consistently pairs with both Salesforce and ZoomInfo. This is the canonical enterprise outbound stack: CRM for the record, enrichment for the data, and engagement tools for the execution. ZoomInfo's frequent appearance alongside Salesforce, Gong, and LinkedIn Sales Navigator confirms that data providers are bridge tools. They don't replace anything; they feed everything.
AI and ML tools form their own ecosystem. PyTorch, TensorFlow, and Hugging Face cluster together tightly, showing up alongside each other far more than alongside CRMs or sales tools. LangChain and LlamaIndex have become the glue layer connecting LLMs (Claude, Gemini, OpenAI) to the rest of the data stack. These pairings signal a growing but still distinct AI tooling layer in B2B operations.
Methodology
This report is based on 1,172,946+ job postings from companies across the U.S. We detect tool mentions in job descriptions using pattern matching and count how often two tools appear in the same posting. Each unique job posting can contribute at most one co-mention per tool pair.
Limitations: Co-mention doesn't always mean integration. Sometimes job descriptions list tools the company uses across different teams. Tools with very high individual mention counts (like Salesforce) naturally co-occur with more tools. We present raw counts rather than normalized rates to keep the methodology transparent. Read our full methodology.