This article will cover the following topics:
Using the "Accounts Import Wizard", you can import new Account records into Pipeliner as well as update or overwrite existing Account records ⤵
Creating the Accounts CSV file
You need to prepare a CSV file for your records.
To begin, you can download a sample file to use as a basic, default template or you can start from an existing spreadsheet and use the downloaded sample file as a guide.
Click on the “Import” button and then the "Download Sample File" button ⤵
Another useful tip is to Export from the Accounts menu. This will create a file with all of your fields in and you can use this as your “custom” template.
Click on the “Export” button and then choose “Comma Separated Values (CSV)”. You can leave the default enclosure and separator as is ⤵
Click on “Save” to export your data.
Depending on which browser you’re using, you’ll then see the downloaded file. For example, in Chrome it will show in the download bar at the bottom of the screen.
Click to open it in Excel. You’ll also be able to access it from the Downloads folder on your machine.
NOTE: You might want to click on "File" and "Save As" and rename this file so that you can use it for your import file.
NOTE: The downloaded sample file only contains the default (out-of-the-box) Pipeliner fields. If you have added custom fields to your Pipeliner records, make sure to add those to the file as new columns, and, if you're not using any of the default fields, simply delete those columns. Just because a column is in the sample file doesn't mean you have to use it (unless it's a mandatory field) ⤵
NOTE: If you export from the Accounts menu, the file will contain all fields — both default and custom fields.
Whichever option you choose, you’ll need to prepare your data before you can import it.
Preparing your Data
Remember that importing is fundamentally the same as manually creating new records so everything that you need to enter if you click on “Create New” and then “Account” or “Contact” is also required when importing.
However, when importing, you also have to supply values that might auto-populate when creating manually such as Owner and Sales Unit ⤵
Key points to keep in mind are:
Every row must contain data for all mandatory/required fields
Data formats must be valid — check your dates, make sure that all values are valid if you’re mapping to dropdown fields such as Customer Type or Industry
Make sure that your data does not contain duplicate records before you import
All Accounts and/or Contacts must be assigned to an Owner and Sales Unit.
As you build your data for import — whether or not you use the sample file as a starting point — keep checking your data quality. Ensure there are no spaces before and after values in any column, that email addresses are all valid (no "mailto:" in an email address, for example), that everything is in the right column and that your data meets all the mandatory field requirements.
Which fields are mandatory/required for Accounts?
Each type of record in Pipeliner (each entity) has a number of system fields that are required in order to create records ⤵
For Accounts, these default required fields are:
Owner (note that you can just map the current, importing user if your data doesn’t contain Sales Unit or Owner data)
Sales Unit (must exactly match an existing Sales Unit)
Formatting your data correctly
Account name is a text field so can hold any value.
Owner is a user field. Every record in Pipeliner MUST be assigned to an Owner (and Sales Unit). The Owner must be a current, active Pipeliner user. When preparing your data to map to Owner, add a column named Owner and use the user's login email address rather than their name to guarantee a match when importing. If a matching user login cannot be found, or you don’t map to the Owner field, imported Accounts and/or Contacts will be owned by the importing user (i.e. the user who is logged in and doing the actual import!).
Sales unit is a dropdown of the sales units that the Owner is assigned to. When mapping a Sales Unit, you need to be sure that the Owner you’re assigning to each record is also assigned to the Sales Unit you're mapping to. If you don’t map a column to Sales Unit, it will use the default Sales Unit for the importing user.
For example, if your data contains a record where you're mapping to an Owner "firstname.lastname@example.org" and a Sales Unit of "Northeast", Bill must be assigned to the Northeast Sales Unit or you'll get an error when importing.
Most data is fairly simple to work with if you stick to the requirements. If your data is a bit more complicated and contains many different types of fields, there are lots of tips in this article to help with preparing data for import.
NOTE: You don’t have to name the columns in your header row to match the field names in Pipeliner but it’s good practice to do this and it makes mapping much easier!
NOTE: If, as part of your Pipeliner setup, you have made any additional default or custom fields mandatory, every record in your CSV file will need to contain a value for those as well.
Save your file in CSV format when it's ready to import.
Selecting your CSV file
Importing is an easy step-by-step process using the Import Wizard. First, you select your CSV file and then you specify its properties and decide on deduplication settings, next you map the fields in your data to those in Pipeliner (and save it as a “Template” so you can re-use it easily), then you preview the records to be imported (which allows you to check that your mappings are correct and identifies any invalid records) and, finally, you accept the records which complete the import.
NOTE: Once you've selected Accept All, your records will be imported and, if you've made a mistake, you'll need to find and delete the imported records — there is no Undo option.
Click on the "Import" button ⤵
Next click on the “Click here to upload” link ⤵
Click on the “Upload a document” button or drag and drop the CSV file here ⤵
Locate and select the data file you've prepared ready for import. Click on "Open" ⤵
Once you’ve selected your file, click on "Next" to move to the next step ⤵
CSV File Settings
These settings define the properties of your CSV file. You can usually leave these on the default "Auto" and "Auto Detect" settings ⤵
If your data includes any dates though, make sure to click on “Edit” to update the Settings:
Change this from “Auto” only if you selected a specific encoding — such as "Unicode (UTF-8)" — when saving your file to CSV format.
NOTE: If your data includes accented characters, it’s often best to select “Western European (ISO)”
You’ll only need to change this from “Auto detect” if you specifically chose a non-standard enclosure.
Multiple checkbox separator
If you’re mapping column(s) to multi-select checkbox fields in Pipeliner, choose the separator you used in your file. We advise you use the pipe "|" symbol as it’s extremely unlikely to have been used elsewhere in your data!
NOTE: When preparing your data, separate values by your chosen multiple checkbox separator and no spaces — e.g. “blue/green/red” where blue, green and red are options in your multi-select field in Pipeliner.
You should only need to change this from “Auto detect” if you specifically chose a non-standard separator.
If your dates are in the format "dd-mm-yyyy", leave this on "Auto". If not, select an option from the list which matches your date format ⤵
NOTE: If the actual date format in your CSV file is, for example, "dd.mm.yyyy" or "dd/mm/yyyy", choosing "dd-mm-yyyy" will also work (the same principle applies to the other formats).
Column contains headers
Make sure this box is ticked if the first row of your CSV file contains header names for your columns.
Click on “Save” to confirm your settings.
Choose from one of the “Deduplication” options to select which field should be used to de-duplicate the data within the file that you are importing ⤵
Auto — if you leave the default option “Auto” selected, your imported Accounts data will be deduplicated only based on "Name". What this means is that if you have more than one row in your file with the same "Name", the end result will be only one Account record being created in Pipeliner. Data from the first instance of the Account name will take priority over subsequent rows but, if a subsequent row contains data that the first row did not, those values will be added to the imported Account record.
None — if you choose “None”, your data will not be deduplicated and every row in your CSV file will be imported as a separate Account “as is”.
Select from the field list — if you select a specific field from the list of available fields, your imported data will be deduplicated based on a combination of the field you selected and the Account Name.
The available deduplication fields include the following system and default fields:
Account Created Date
Home Page (you’ve probably renamed this Website)
And also, custom (user-defined) Account fields of the following field types:
Date and Time
Why is my choice of deduplication field so important?
Let’s say you’re importing a file of new Accounts i.e. your data contains one row per Account. If you leave the deduplication as “Auto”, unless you are completely sure that your "Account Names" are unique, you’ll end up with fewer Accounts imported than you have in your file as the duplicate names will be treated as a single Account.
Click on “Save” to confirm your settings.
Updating/replacing existing Accounts
You can also use the field you select as your Deduplication field to be the matching field to identify exactly which existing Account should be updated (or replaced) by the data in your CSV file.
If you have created a custom field holding an Account or Customer Code, this would be a great example of a field you could use as this code is usually unique to each Account.
Whichever field you choose, you need to be sure that the data in that field in your CSV file is an exact and unique match to the data in the corresponding field in Pipeliner so that the right record is updated. You'll also need to ensure that you have no blank cells in your file or you run the risk of updating all records without a value that currently exist in Pipeliner.
If we think about Account/Customer Code as our example again, only customers would generally be allocated a code so you could have many Account records in Pipeliner without one (Prospects, Suppliers etc). If you're not careful in your file preparation, you could risk updating all these prospect and supplier records inadvertently.
NOTE: there is no undo option for an update/replace operation that goes wrong!
If you’ve done previous imports, you can choose a saved import template to re-use the same settings, deduplication and field mappings.
NOTE: Your file will need to be the exact same structure and format each time — don’t reorder the columns or insert new ones as you’ll need to redo all your mappings if you do. If you need to add a new column, make sure you put it at the end of your file.
This is an invaluable option when you’re regularly importing data from the same source — e.g. regular Account uploads from a data provider ⤵
If you haven’t saved any Templates, you’ll be able to select from “Empty” or “Default Account Mapping Template” — which will work if your file is the same structure as the downloaded sample file.
You can save a new template on the "Field Mappings" screen.
When you’ve chosen the "Settings" and "Import Template" you want to use, click "Next" to progress to the Field Mappings ⤵
Mapping CSV Fields
If you selected a template, your fields will already be mapped on the Map CSV fields screen ⤵
If you selected “Empty” then you’ll need to start by mapping each field.
Drag each column name from the right-hand panel to its corresponding field on the left. The left-hand side of the screen shows all the fields that are on the Account Form that you’re importing into ⤵
NOTE: If you don’t see a field that you need to map to, you’ll need to cancel your import and adjust your Form from the Admin Module and then begin your import again. If this happens, map all the fields you can and then save it as a template before cancelling so you don’t have to repeat all your steps.
NOTE: This is where it’s a timesaver if you matched your column names in your data to your field names in Pipeliner but it’s not essential to have done that, as long as you know which column should map to which field.
NOTE: You do not have to map every field from your data file to a field in Pipeliner — just leave behind those you don't want to import ⤵
There are a number of system fields on the import form. If you don’t map a column from your file to these fields, they will be populated with default values. As well as Owner and Sales Unit, the other field for Accounts is Account Created Date (which will default to the date you do the import if you do not map a specific date).
To recap, if your data does not contain a valid user email address to map to the Owner field or the name of a Sales Unit to map to Sales Unit, you'll need to leave the option to "Use current user" as the Owner and "Use default value" in Sales Unit (the current user’s default Sales Unit) checked and all imported records will be owned by the importing user (and will be in the importing user's default Sales Unit).
Saving an Import Template
You can save your settings and mappings as an Import Template by clicking on the three dots icon and choosing "Save As" or start a brand new Import Template by clicking on the "+" icon ⤵
Give your template a name and click on “Save” ⤵
Importing your Data
Once you’ve saved your template, click on the “Import” button to move to the Import Preview screen ⤵
You’ll then see a preview of the records to be imported. You can click on any record in the preview to see the actual mappings in the right-hand panel ⤵
The preview will show you if any records are invalid for importing. The row will be highlighted in red in the preview ⤵
If you click on an invalid row you’ll be able to see where the problem is and resolve it ‘on the fly’ by correcting the data or adding missing information ⤵
NOTE: If you have lots of invalid records, check them over to see if there’s a pattern to the problem and then close the import (make sure you have saved your import template) and sort out the issue in your data or by modifying the set up of Pipeliner and then re-do the import.
You can also click on the Filter icon and just choose to see just Invalid records to make them easier to review and fix ⤵
Once you've corrected an individual record, you can click on "Accept" to import just that record immediately ⤵
If you are looking at a record and do not want to import it you can reject the record using the red "Reject" button at the bottom of the record details. This will remove that particular record from the import list ⤵
If you've made a mistake in your mappings, you can use the "Change Mapping" button at the top to change the field mappings and this will return you to the “Map CSV fields” screen ⤵
If you have mapped more fields than the default display includes, then the import page may not show all fields at once.
To view more fields you can select the following button to show all field options ⤵
Accepting Records and Finishing the Import
You now need to select the records to be imported by clicking the checkboxes on the left (or select all by clicking the first checkbox in the upper left). Click on the "Accept Selected" button to finish the import of those records ⤵
As long as there are no duplicates in your data, the import will then complete and return you to the Accounts menu.
Import Options when duplicates are found
Pipeliner will then begin to import your records. As part of the import process, it will check the data that already exists in Pipeliner based on the Deduplication field you have chosen in your Import Settings.
If any of the Accounts that you’re importing has the same value in the selected Deduplication field as a record that already exists, you’ll be able to choose what to do ⤵
Skip duplicates — duplicate records will not be imported and will remain in the import preview once the non-duplicates have been imported.
Create Duplicates — ignore the warning and go ahead and create duplicate records.
Update existing records — data will be updated by the import only when that field is empty on the existing duplicate Contact already in Pipeliner.
Replace existing records — data on the duplicate records will be overwritten by the incoming data (be aware that when you select this option, unless your incoming data contains all fields, data might be lost from your existing records if the field is not mapped as part of this import).
Cancel — cancel the import so you can check the data and decide what to do.
If needed, you can cancel the whole import. If you click on "Close" to abort your import while there are still records in the preview, you’ll be prompted by a message indicating that the import is not finished and checking that you really want to leave.
Click on "Continue" to cancel the import and close the import screen ⤵
Once you’ve chosen your option from “Skip duplicates”, “Create duplicates” or “Replace Existing Records”, the import will complete and you can then check your Pipeliner system to view the newly imported records ⤵
NOTE: If there are no records in your CSV file that already exist in Pipeliner, you won’t receive any prompt and the import will just complete.
What if there’s a problem after the import is complete?
Rarely, but sometimes, despite all your data preparation and care, the imported data can be wrong. As long as you’re based on a user role that allows you to delete, you can remove records by clicking on the Accounts menu, switch to the "List View" and then select the records to be removed. You might need to set up a filter for this — you might use “Account Created Date = Today” as your filter criteria.
NOTE: If you don’t see the "Delete" button, it’s your user role that needs amending.
NOTE: You must be the record Owner in order to delete them. If you’re not, select your records and then click on the Ownership button to make yourself the Owner and, once that’s complete, you will then be able to delete them.
NOTE: If you can’t change the Owner of a record, you need to be assigned Manager rights in the Admin Module.