Data Readiness
Short definition
A High / Medium / Low verdict on an uploaded lead file, produced before import from format validity, completeness, duplicates and business context.
01In practice
How teams actually use it.
The most expensive moment in a bad import is the hour afterwards, when reps start dialling. Readiness is what you can learn before that point, and it is nearly free. Leadkaun profiles a sample of the file and answers plain questions: how many rows carry a valid Indian mobile, how many companies look like businesses rather than individuals, how many rows duplicate each other, which fields are systematically missing, and whether this is a B2B or B2C dataset at all. None of it needs a model. It is arithmetic on formats and completeness, and a rule you can read is easier to trust than one you cannot. The result is reported as a band rather than a number, because a band is a decision and a number is a debate. The point is not to reject files; it is to know what you are importing while you still have the option not to.
02Worked examples
Three ways it shows up.
- 01
A file where a third of the phone numbers fail Indian mobile validation reads Low. The problem is the file, not rep effort.
- 02
A clean export from a trade portal usually reads High and can be imported as-is.
Go deeper on data readiness
03Check it yourself
How to tell where you actually stand.
Import problems are cheap to find before an import and expensive after.
- 01Take the file you would upload and check three things: duplicate numbers, missing sources, and unusable phone formats.
- 02Count how many rows fail any of the three.
- 03That is the share of your import that will produce noise instead of leads.
04Related terms
Neighbours in the glossary.
Junk Lead
A lead that can never convert because the record itself is invalid, fake contact details, a test submission, a bot fill, or a duplicate of an existing lead.
Lead Quality
How reliable and complete a lead's data is, measured as a 0–100 Quality Score covering completeness, phone and email validity, and junk or duplicate detection.
Data Freshness
How old a lead record is, expressed in ageing bands that keep moving, so a list bought six months ago never presents as new work.
→From definitions to doing
Stop defining. Start scoring.
Leadkaun puts these concepts into practice, A–F grading, Priority Queue, Missed ₹. Setup the same day.