How to stop clients sending incomplete Excel spreadsheets
You send a spreadsheet with everything you need. The client sends it back with half the fields completed.
Instead of discovering missing information after the spreadsheet has already been returned, you can collect the data against a defined structure and validate it before the final CSV is produced.
Why do clients send incomplete spreadsheets?
Usually, the problem isn't that your client doesn't want to provide the information. They simply don't know which fields are important, or they don't notice that something has been left blank.
In a normal Excel template, a blank cell often looks exactly like a field that doesn't need to be completed.
By the time you open the completed spreadsheet, the client may have already moved on to their next task.
Blank fields
Important information is left empty because it wasn't obvious that it was required.
Invalid values
A field is completed, but the value isn't in the format your system expects.
Partial rows
Some records are complete while others are missing important information.
Manual checking
Someone has to inspect the spreadsheet before it can be imported.
The spreadsheet correction loop
A simple request for information can turn into several rounds of email.
The frustrating part is that the missing information is often discovered only after the client has finished their part of the process.
Highlighting required cells helps — but it isn't validation
You can use colors, comments, instructions, and formatting to make required fields more obvious in Excel.
That's useful, but it still relies on the person completing the spreadsheet noticing and following the instructions.
The client still has to notice and follow everything.
Problems can be addressed before the dataset is ready.
Make required information actually required
If a field is critical to your workflow, it shouldn't be possible to accidentally leave it blank and discover the problem later.
Define which columns are required and give users feedback when information is missing.
BEYOND REQUIRED FIELDS
Complete data isn't necessarily correct data
A client can fill every cell in a spreadsheet and still give you information that your system can't use.
Email addresses
Identify values that don't match the expected format.
Duplicate IDs
Prevent multiple rows from using the same identifier.
Quantities
Check values against the rules your workflow requires.
Row validation
Identify problematic records before they are exported.
What if the client already has a spreadsheet?
They don't necessarily need to start again from scratch. An existing CSV can be brought into the workflow and mapped against the structure you've defined.
This means you can combine the convenience of an existing spreadsheet with the validation and structure of your workflow.
Browse CSV guidesWITH IMPORT BUILDER
Catch problems before you receive the final spreadsheet
Import Builder gives you a structured CSV workflow where you define the fields and validation rules before your clients provide their data.
Define your fields
Choose exactly which information your clients need to provide.
Require important fields
Make critical columns required instead of discovering missing information later.
Validate values
Apply validation rules while users are entering or reviewing their data.
Review rows
Give users a spreadsheet-style interface for checking their records.
Import existing data
Bring existing CSV data into the workflow instead of requiring manual re-entry.
Download when ready
Produce a CSV once the dataset is ready for your next workflow.
Spreadsheet chasing
Structured collection
Stop chasing incomplete spreadsheets
Define the information you need, validate it as it's entered, and produce a clean CSV when the data is ready.