30 shared accounts discovered from two 100-account lists
Two business partners wanted to see how much of their account base they genuinely had in common. Each uploaded around 100 accounts. OnlyCommon identified 30 shared accounts in about two minutes — and none of them had been top of mind in the partners' earlier account-mapping conversations.
- ~100
- accounts uploaded by each partner
- 30
- shared accounts identified
- ~2 min
- to complete the comparison
- 0 of 30
- were top of mind beforehand
The situation
Two business partners wanted to know whether they actually shared customers and prospects, and how many. They had already discussed accounts the way most partner teams do: in conversation, naming the companies that came to mind on each side.
That conversation gave them context, but it could not tell them how complete their list was. Neither side wanted to hand over a full account export to find out.
What they did
Each partner uploaded their own account list to OnlyCommon independently — roughly 100 accounts per side. Neither list was shared with the other company.
The comparison itself took around two minutes, and produced a single view of the accounts the two lists had in common.
What they discovered
OnlyCommon identified 30 shared accounts across the two lists.
None of those 30 accounts had been top of mind during the partners' normal account-mapping conversations. The overlap that existed in their data was not the overlap they had been discussing from memory.
Why the result mattered
The speed is the least interesting part. What mattered was completeness: a memory-based conversation surfaces the accounts people happen to recall, while a systematic comparison works from the lists themselves.
With the shared accounts in front of them, the partners could move from trying to remember overlap to reviewing it — looking at relationship context account by account and deciding, with the people who own them, which ones deserve attention.
What this example does and does not show
- 30 shared accounts are not automatically 30 co-sell opportunities. A match means both partners have a record tied to the same organisation; whether anything commercial should follow is decided account by account.
- This is one anonymized example, not a benchmark. It says nothing about what overlap any other pair of partners should expect.
- We do not report what happened commercially afterwards. The verified facts are the list sizes, the 30 shared accounts, the time taken, and that none of the 30 were top of mind.
- Company data is messy, so no matching process should be described as perfect. The output is a strong working set to review, not an infallible census.
Each side uploads its own list independently, and each partner sees the accounts the two lists have in common rather than the non-overlapping rows. OnlyCommon is not a CRM and does not replace the systems where your account data lives — it answers one narrow question about where two account sets intersect.
Run the same comparison
If you have a partner and an exported account list, the exercise is short. The editorial write-up of this example is in 100 accounts each, 30 shared, none top of mind, and how OnlyCommon works walks through the steps.