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You didn't run out of data. You ran out of places to put it before it went stale.
Almost every B2B team already pulls from more than one source to research a prospect before making contact. 89.9% of companies use two or more data tools to do it, according to Gartner data cited in SPOTIO's 2026 sales benchmarks. That's not a bad habit. It's just what building a real target account list requires: firmographic data from one place, contact data from another, and whatever signal tells you the account is actually worth calling right now from a third.
The problem isn't the number of sources. It's where all of that ends up.
Where target account lists actually break
Most target account lists get built the same way. Export a list of companies from the CRM. Run it through a prospecting tool to find contacts. Open a browser tab to check funding news, tech stack, or headcount on the accounts that look promising. Paste all of it into a spreadsheet, and hope nobody changed jobs while you were building it.
The effort compounds at scale. One rep on r/sales described building a list of 2,600 companies and 20,000 contacts over four months, stitching together multiple tools along the way. Another manager on r/b2b_sales was starting each rep at 100 contacts, researched and reached out to one at a time, just to keep the personalization intact.
Marketing teams building account lists for ABM face the identical problem from a different angle. Combining first-party CRM data with third-party intent and firmographic signals is standard practice now, but each source usually means a separate export, a separate login, and a separate format to reconcile before the list is usable, as Madison Logic points out.
By the time that spreadsheet is finished, some of it is already wrong. A contact changed roles. A company raised a round the list doesn't reflect. Nobody notices until a rep is mid-call working from data that was accurate two weeks ago. A marketer on r/b2bmarketing hit that wall three months after rebuilding their ICP criteria from scratch: funding stages had moved on, headcount figures were frozen in time, and a couple of "independent" companies had already been acquired.
Multiple sources were never the issue. The issue is that they don't meet in the same place at the same time.
What changes when the table does the assembling
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Lando's table skips the export-and-paste step entirely. Ask for a list and it pulls from LeadIQ, your CRM, or the open web, whichever source actually has the answer, and lays it out in one live table instead of three.
It doesn't stop at whatever fields it started with, either. Describe a column in plain language, something like whether a company already uses Salesforce or how many open sales roles they're hiring for, and Lando builds it right there, working alongside the conversation instead of sending you off to check somewhere else.
Scale was the next obvious wall, so that moved too. Web app Lando now handles up to 1,000 records in a single run, which covers most target account lists in one pass instead of several smaller batches stitched back together afterward.
None of this means data gets pulled the moment the table exists. Lando builds the table first and leaves contact data locked until you ask for it, whether that's the whole table at once, a single column, or one cell. The list comes together fast. What gets unlocked is still up to you.
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