One of the most important things you can do to smoothly import your contacts is to carefully make sure your Excel spreadsheet (or file from another program) is arranged properly before exporting it to the .csv format.
How to Organize your Excel file (or file from another program):
Tank Track does a great job importing files that are organized as follows:
- Describe ONE Property per row:
Information for each property you service should be arranged on a single row (including contact person info, etc.). No property should have information spread across multiple rows. The Tank Track software will assume during import that each horizontal row is the independent and complete record for 1 property.
- Consistently place each bit of information in its appropriate column:
Information about each property should be organized by having a separate column for each "field" that you want to import into the Tank Track program.
Here is an example of how this might look on a spreadsheet:
You will note that each column has a "heading" at the top that describes a particular piece of distinct information about each property/customer. Down the left side, you will see that each row describes information for a separate customer/property.
When you complete the Tank Track importing process, you will be able to match up the column heading for each Tank Track field with one of your column headers (up at the top). This is how Tank Track will know where to place each piece of information within a the record of a particular property.
It is important to have each component of the property address listed in a separate column. If you have it all combined into one column simply called "Address," you could technically import it successfully by matching your "Address" field with the Tank Track "Property Address 1" field, but the address might be formatted badly for printing on a job form. Also, if you do not have the street address, town, state, and zip code of the property in separate columns, Tank Track will not be able to sort/filter your contact list by property town or zip code, and the Google Maps integration feature will not work.
Tank Track Fields for Matching in Import:
Here is the list of Tank Track fields that you will be able to match your column headers to. You can also add custom fields into Tank Track before you go through the process, so don't worry if you have a few extras. Also, if there are Tank Track fields that you don't need, you can leave them blank. (Note: the order of your columns does not matter.)
- First Name
- Last Name
- Full Name (Complete either this field OR the first two; either way is fine)
- Billing Company
- Billing Address 1
- Billing Address 2
- Billing City
- Billing State
- Billing Zip Code
- Billing City/ State/ Zip [Use this field instead of the separate city, state, and zip code fields above ONLY if the city, state, and zip code are combined into one column in your file.]
- Home Phone
- Cell Phone
- Work Phone
- Contact Notes[private]
- Contact Method [Use this field to indicate the customer's preferred method of contact. In your .csv file, "E" or "email" returns Email, "P" or "phone" returns Phone, "SM" or "snail mail" returns Snail Mail. Entries can be upper or lower case.]
- Property Company
- Property Address 1
- Property Address 2
- Property City
- Property State
- Property Zip Code
- Property City/ State/ Zip [Use this field instead of the separate city, state, and zip code fields above ONLY if the city, state, and zip code are combined into one column in your file.]
- Property Type [In your .csv file, "C" or "Commercial" returns Commercial, "M" or "Municipal" returns Municipal, "R" or "Residential" returns Residential and "O" or "Other" returns Other.]
- Property Notes
- Tank Name
- Tank Capacity
- Tank Notes [Include tank info such as tank depth, location of cover(s), etc., in this field.]
- Date of Last Service
- Service Due Date
- Job Notes [Use this field to describe what needs to be done on the next service due date.]
These are examples of the types of headers you should have in your spreadsheet. If yours is simpler, don't be worried. The main idea is just to keep each small piece of information separated into different columns so that you can take advantage of all of Tank Track's Features.
Q: What should I do if my customer file is formatted incorrectly?
A: It depends on the severity of the problem.
If you have only one customer/property per row (as shown in table above), but don't have as many separate columns as preferred, you will have two choices:
- You could invest time (or invest an employee's time) up front in changing your Excel spreadsheet to match the optimal format. For instance, if you have only one column for property address, it's probably worth the time to go through it and create separate columns for each component (street, town, state, zip) so that your contacts will import properly and you'll be able to use all of the features in Tank Track.
- If the sheer number of contacts is too large for you to fix the file, you could import it as-is, matching your few columns to a few of Tank Track's columns in whatever way you think best. Then you can fix the issues on each individual property's page one at a time, throughout each day, as you open those pages in the course of business. If you choose this option, please understand that some of the printing, list filtering, or mapping features of the program may not work as intended.
If you have MORE than one property per row, OR more than one row per property, you must change your file before importing into Tank Track.
- More than one property per row will result in the combined information being added as a single property in Tank Track. Confusing!
- More than one row per property will result in the information being spread over multiple property pages. Since Tank Track expects to see only one property per row in the imported file, if property information is spread over two or more rows the program will assume that each row represents a separate property.
Unfortunately, this issue does have to be fixed in your Excel spreadsheet or other program file BEFORE exporting it to the .csv format and continuing with the import process.