History skips the retyping
A messy spreadsheet gets mapped and validated rather than manually re-entered row by row, turning weeks of dreaded data entry into a single reviewed import.
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The whole team
Nineteen specialists, each with a defined job and an honest status label.
See all nineteenA business switching from spreadsheets or another CRM can bring their existing contacts and deals into Jeet without manual re-entry, and can always export their own data back out.
Works with
What it does
Jeet accepts a CSV or existing CRM export, maps the columns to its own fields, and validates the data before importing. Businesses can export their full contact and deal history at any time in a standard format.
A freelance interior consultant has three years of client history sitting in a spreadsheet — some rows with phone numbers formatted three different ways, a few duplicate entries from copy-paste mistakes, one column that's clearly meant to be "budget" but got labelled something else entirely — and the thought of manually re-entering all of it into a new system is enough to keep putting off the switch indefinitely.
CRM data import and export handles that spreadsheet directly. It accepts the file, lets the consultant map each messy column to the right field, and validates the data before anything actually gets imported, catching problems rather than silently importing three years of formatting inconsistencies as though they were fine. The same consultant can export everything back out at any time, in a standard format, so switching systems again later never means starting from zero.
Jeet runs this directly on the platforms your customers already use — no separate app for them to install.
How it works
A CSV file or an export from another CRM system is accepted and scanned carefully for structural problems — missing columns, malformed rows — before any actual import step against the live business data ever even begins.
Each column in the uploaded file is matched to the corresponding field in the system — a column meant as "budget" gets mapped correctly even if its original header didn't say so clearly at all, initially.
The data is checked for issues — invalid phone formats, missing required fields — before the import ever commits, surfacing errors to fix rather than silently importing bad data as if it were perfectly clean already, unnoticed.
A full contact and deal history can be exported at any time in a standard format, so the consultant's own data is never locked into the system permanently with no way back out at all.
Why it matters
A messy spreadsheet gets mapped and validated rather than manually re-entered row by row, turning weeks of dreaded data entry into a single reviewed import.
Validation surfaces formatting problems before the import commits, so three years of inconsistent phone number formats don't quietly become three years of unreachable, unusable contacts.
A standard-format export at any time means the consultant's own client history is always retrievable, regardless of what system they might eventually move to next.
The detail
A malformed or oversized file is the most common way an import goes wrong, and the failure mode that matters most is a partial import — some rows succeed and others fail partway through, leaving the contact list in a genuinely inconsistent state harder to untangle than either a clean success or failure would be. This is why validation needs to happen before committing anything, rather than processing row by row hoping problems are rare; a consultant reviewing a summary flagging which rows failed and why can fix the source file and retry, rather than discovering gaps weeks later during unrelated work.
The dedupe question matters just as much here as for everyday lead creation, because an import is really lead creation happening in bulk. If imported records skip the same duplicate-checking logic as a normally created contact, a spreadsheet already containing accidental duplicates — the copy-paste mistakes that accumulate in any old file — gets imported as-is, and the new system inherits and multiplies a mess it could have caught at the door. A trustworthy import checks duplicates against both the existing list and within the file itself.
Exported files deserve the same security thinking as any export of customer data, because a full contact and deal history is a complete copy of every customer's PII the business holds. That file should never be delivered as a plain downloadable link sitting in an email indefinitely — a secure, time-limited link that expires keeps an export from becoming a forgotten copy of sensitive data, accessible somewhere it shouldn't be, months after anyone needed it.
Industry use cases
13 industries where Jeet applies this directly.
A dealership's website form captures an interested buyer's contact details, Jeet creates the lead and assigns it to the on-duty sales rep, and a follow-up task is created if the rep hasn't logged an activity within two days.
See the automotive playbookA software reseller's rep enrolls a shortlist of prospect companies into an email-and-call sequence, and Jeet pauses the sequence automatically the moment a decision-maker replies so the next touch is a live conversation instead of another templated email.
See the b2b sales playbookA financial advisory firm receives an inbound inquiry through its website, Jeet routes it to the specialist covering that product line, and the call recording consent is logged before any call is placed.
See the banking and finance playbookA cosmetics brand's distributor inquiry comes in through WhatsApp, Jeet creates the lead, and a task reminds the rep to send a wholesale price list if no reply has come within a set window.
See the beauty and cosmetics playbookA coaching institute's demo-class signup form feeds directly into Jeet, and the lead's score rises after they attend the demo, moving them to the top of the counselor's call queue.
See the education playbookA freelance designer receives a project inquiry by email, Jeet logs it as a lead automatically, and a task reminds the designer to follow up if the proposal hasn't been opened within three days.
See the freelancers and consultants playbookA wellness center's inquiry about a corporate package is logged as a deal, and Jeet reminds the rep to send a customized quote after the discovery call is marked complete.
See the health and wellness playbookA home-decor studio's client requests a revised quote after a site visit, and Jeet keeps both quote versions attached to the same deal so the rep can see exactly what changed.
See the home decor and furnishing playbookAn agency's referral lead comes in tagged by source, and Jeet's win-loss reporting later shows that referral-sourced deals close at a different rate than cold outbound, informing where the agency invests its business-development time.
See the marketing agencies playbookA broker's site-visit is scheduled through the meeting scheduler, and Jeet automatically creates a follow-up task for the day after the visit so interest doesn't fade before the next contact.
See the real estate playbookA restaurant's catering inquiry for a large event is logged as a deal, and Jeet reminds the manager to confirm the final headcount and menu two days before the event date.
See the restaurants and food playbookA salon's membership inquiry from a walk-in is logged with the phone number, and when the client calls back later, staff see the earlier conversation notes before answering.
See the spas and salons playbookA travel agent's WhatsApp inquiry about a family holiday package becomes a deal, and Jeet tracks when the itinerary PDF is opened so the agent knows exactly when to call and close.
See the travel and tourism playbookMore from Jeet
The business stops losing leads that arrive scattered across WhatsApp, website forms, calls, and marketplaces because every new contact lands in one place automatically.
Learn moreSales owners see exactly where every deal stands and which ones are stuck, instead of guessing from memory or a spreadsheet.
Learn moreReps spend their limited calling time on the leads most likely to convert instead of working the list top-to-bottom.
Learn moreDeals stop sitting untouched in the wrong stage because Jeet updates them the moment a defined event happens, without a rep remembering to do it.
Learn moreNo lead goes cold because they weren't followed up with — the next email, call reminder, or WhatsApp message goes out on schedule without a human remembering.
Learn moreReps make and log calls from inside one screen instead of switching to a phone and then re-typing notes into the CRM afterward.
Learn moreQuestions
Validation runs before the import actually commits, flagging rows with problems — a malformed phone number, a missing required field — so they can be reviewed and fixed rather than imported silently as though they were clean. The alternative, a partial import where some rows succeed and others quietly fail, leaves the contact list in a more confusing state than either a clean success or a clean, informative failure would.
It shouldn't, provided the import runs through the same dedupe checking that applies to any normally created contact — checking against both the existing contact list and duplicates within the file itself. An import that skips this check would import the mess as-is, so it's worth confirming the import process does apply proper duplicate detection rather than assuming a spreadsheet's existing errors get caught automatically without that step.
A full export contains every customer's PII the business holds, so it should be delivered through a secure, time-limited link rather than a plain download sitting in an email indefinitely. This matters because an export left accessible for months after it was actually needed is effectively an unmonitored copy of sensitive customer data sitting somewhere nobody's tracking anymore at all.
Common CRM export formats are supported as optional connectors alongside plain CSV, though the core import process — mapping and validation — works the same way regardless of which format the file originally came from. A consultant switching from a specific previous system should check whether that system's particular export format is directly supported before assuming a CSV conversion step is needed first.
The rest of your stack
No rip-and-replace — move data in and out cleanly works alongside the systems already running your business.
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