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Importing deals to Outseta fast

We recently decided to use the deals feature in Outseta (our CRM here at crul) to manage our customer interview lifecycle. We found crul to be perfect tool to get our data into the import format expected by Outseta in less than 5 minutes.

Results

Setting the stage

The first step was to create a "Pipeline" in Outseta, which we named Interviews, and added the following stages; Contacted, Interview Scheduled, Interviewed.

We had a Google sheet containing an export of all user downloads (from Outseta) where we kept track of if we had contacted a user, the contact date, any notes, and few other columns.

Sheet

Loading our users.csv into crul

To load our exported Google sheet (as a csv) into crul, we needed to use the cellar. Once files have been loaded into the cellar, they can be thawed into the query pipeline, and we can run other commands to process the data.

Loading

Transforming our data into an importable file

The Outseta deals import structure (for our purposes) relies on 4 main columns; Name, Uid, Stage, Contacts. For the most part, we just need crul to help us rename a few columns, add a Uid column, and do a little filtering. With crul, we can get this done in just a minute!

Import format

Just do this in sheets?

The idea of generating a random Uid column and having to possibly iterate on our import file to match Outseta's requirements made crul seem like an easier flow for us.

The query

thaw users --guid
|| rename 'Contact Date' cd
|| filter "cd == /08.*/"
|| addcolumn Name "$First Name$ $Last Name$"
|| table Email _guid Name
|| addcolumn "Stage Name" Contact
|| rename Email Contacts
|| rename _guid Uid
|| slice Uid 0 9

Query explanation

This query has multiple stages, but is relatively straightforward.

The first stage will thaw the results from our uploaded users.csv and add a guid to each row using the --guid flag.

Next we'll do a rename of our Contact Date column to cd so our filter is easier to constuct.

The filter expression for this query is just looking for a regex pattern. In our original csv, any contacted user will have a date starting with 08 in the Contact Date (now cd) column, so our filter will only include rows whose cd column starts with that value.

The next few stages simply add new columns using the addcolumn command. table our data to only include the desired columns, slice our Uid to the max size expected by Outseta, and do a few renames.

Results

Exporting our file

Once our results look as desired, we can simply export them to csv from our results page!

Export

Uploading to Outseta

We can now upload this deals file to our Outseta Pipeline!

Deals

Just like that we've moved our internal spreadsheet of contacts and interviews to our centralized CRM, where we can better manage follow-ups and more!

Summary

Pretty cool no? Need to run some custom code? No problem, check out the evaluate command!

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