Standardizing fields in your CRM is critical for segmenting and filtering data and personalizing communications with your prospects and customers. With Insycle, you can use pre-built functions for standardizing fields or build your own custom standardization templates.

Let’s go through how to use the Cleanse Data, Transform Data and Magical Import modules can help you to standardize job titles, industries, and locations, in three different powerful ways.

With Insycle, you can:

  • Standardize inconsistent values in the CRM make it difficult to segment data, personalize campaigns, create reports, route and score leads, and more.

  • Standardize job titles. For example — VP Sales, VP of Sales, Vice President of Sales, vp sales.

  • Fix inconsistent state and country fields that break the HubSpot Salesforces sync.

  • Standardize phone numbers

  • Build custom templates for standardizing other fields

Table of Contents

Quick Summary

Standardization is often a multi-step process. In order to understand what standardization changes you need to make, you must know data variations are present in each field. Only then can you identify redundancies and inconsistencies, and standardize them to the correct value in bulk.

Insycle makes all aspects of standardization simple. First, you can use the Cleanse Data module to explore data variations in each field and identify opportunities for standardization. Then, with an understanding of what is in your database, you can standardize your data in bulk using the Transform Data module. Insycle also allows for standardization on import using the Magical Import module.

Let's look at how these modules work together to create deep, effective customer data standardization tools.

Explore Standardization Opportunities, Then Standardize In Bulk

Quick Summary

With Insycle, you can use the Cleanse Data module to explore your data, identify opportunities for standardization, and update the data.

It's simple. First, you tell Insycle what field that you would like to explore. Then you identify all of the different variations that you would like to update within that field and update them using Cleanse Data.

Cleanse Data can be used as both a tool for discovering inconsistencies and standardizing fields in bulk.

Step 1: Review Field-Level Statistics

Select the Cleanse Data module from the main navigation menu on the lefthand side of your screen.

Before standardizing your data, it's important that you have a complete picture of the field that you are working with. A free-text field needs to be handled differently from a picklist, for example.

So first, we will search for the field that we would like to standardize in the search bar of Step 1.

review level stats

In this example, we'll be standardizing job titles, so we will search for the "Job Titles" field. This will generate field-level statistics for the field below.

job title

Step #2: Pick a field to explore its underlying values

Here, we tell Insycle which field that we would like to explore.

There are two ways to do this. First, you could select the field using the checkbox in step #1.

job title

Alternatively, you can select the field in Step #2.

pick a field

Both methods alter the same setting. If you select the checkbox, the field name in Step #2 will be pre-populated.

Once you have a field selected, the underlying values are viewable in the Record Viewer.

buckets

Additionally, you can filter further these options in step #2.

filter

Here we are filtering the Job Title field down to only those records that include the phrases "CEO" or "Chief." We use the bar "|" key to separate values.

Click the Search button and the Record Viewer at the bottom of the page will be updated.

Additionally, you can select one of the buckets by checking the checkbox.

bucket check

This opens up a secondary Record Viewer, allowing you to view individual records contained within that bucket.

record viewer

Step 3: Select groups of records, then choose an action: Update or Delete

Now we can update and standardize our data. You can select entire buckets of records, or you can select individual records, or both, from the Record Viewers on the bottom.

For our example, we are going to standardize everyone with the "Chief Executive Officer" job title down to the acronym, "CEO."

checkbox

Then, we set our function for updating the field.

update

You can see that the button has been updated to say "Update 15 Contacts" because we selected 15 records with the "Chief Executive Officer" title.

When you click the button, you will be prompted to confirm. When you do, the update will go live in your database. Changes can always be reviewed on the Activity Tracker page.

All settings here can also be saved in a Template.

To create a Template, click the Add Template Button (+) to give your template a name, then click the Save Button to save it for future use.

template

Then, you can run similar processes and create Templates for fields like:

  • Industry (for Contacts and Companies)

  • U.S. State

  • Zip Code

  • Area Code

The Cleanse Data module gives you a full top-down view of your data, down to the individual record level.

Standardize Job Titles, Industries, Locations In Bulk

Quick Summary

With Insycle, you can standardize job titles, industries, locations, and any free-text field in your CRM, in bulk.

To standardize records in bulk, use the Transform Data module and select the appropriate template, or build your own custom template. You can build field-by-field instructions for standardizing your data or use one of Insycle's pre-built templates for standardizing common fields.

Here is a step-by-step breakdown:

Step 1: Define filter, then click Search.

Bulk standardization is handled in the Transform Data module.

To get started quickly, explore the default templates. There might be a template that standardizes the exact fields that you are looking to standardize. Additionally, viewing templates can be a great way to learn more about how Insycle works.

address template

These templates can be run separately, or combined into one single master template, and run together automatically on a regular basis.

In Step #1, we filter our database down to only those records that we would update and standardize.

In our example, we will standardize contacts that are from New York.

filter state

With your filter set, a preview of the fields that match this filter will be generated at the bottom of the screen.

record viewer

Here, you can view and select individual records for update using the checkbox.

Step #2: Pick fields, then functions to apply.

Here is where you tell Insycle what fields you'd like to standardize, and what rules to follow in the standardization process. You can use pre-built templates and functions, or build your own custom rule-based templates.

In this example, we are formatting job titles, industries, and locations. To do this, our functions would look like this:

functions

Let's break down how it works, step-by-step.

On the left-hand side, we have the Column Name. This is a column from the CSV file that you are importing and would like to standardize. On the right side, you select a Function for each field. This is where you tell Insycle what to do with the field — In this case, we will be standardizing, so this requires that we use the “Map” Function.

First we are standardizing the "State/Region" field, and standardizing it using the pre-built "Standardize US States, CA provinces" function. This standardizes states to their full name.

  • NY→ New York

  • New york → New York

Then we are using the "Map" function to standardize Job Titles. In the Existing Text field, we input this:

"vp sales|vp of sales|vice president sales|vice president of sales"

In the "New Text" input, we put "VP of Sales," which is what all of the previous job titles will be updated to if they match one of the inputs in the Existing Text field.

This will update your Job title fields:

  • vp sales→ VP Of Sales

  • vp of sales → VP Of Sales

  • vice president sales → VP Of Sales

  • vice president of sales → VP Of Sales

Lastly, we standardize the Industry field. Here we also use the Map Function. Here we are updating "Software," "Tech," and "Computer Software" industries to "Technology."

  • software→ Technology

  • tech → Technology

  • Computer Software → Technology

You can easily add additional job titles and industries to the template for standardization using the Field button. Then, you only have to set your standardization preferences one time, then save it as a template, and will save yourself time on all future standardization updates.

To create a template, click the "Add Template" button (+) to give your template a name, then click the save button to save it for future use.

template

Step 3: Choose Preview or Update Mode

Once ready, you can select individual records from the record preview at the bottom of the module screen, or just click the review button.

First, you'll choose whether you want to run this operation in Update Mode or Preview Mode.

preview or update

In Preview Mode, you'll be able to generate a CSV report that details all of the changes that will be made to your data. Preview Mode does not push any data updates to your live database.

In the Notify screen, you'll be able to put together an email report for your standardization. You can add colleagues and customize the report with additional context as needed.

email notification settings

On the next screen, you choose whether you want to run the module one time, immediately (Run Now), or recurring on a regular, set schedule (Automate).

automate or run now

In Automate, you can choose an hourly, daily, weekly, or monthly schedule for your standardization processes.

Standardize Job Titles, Industries, Locations On Import

Quick Summary

With Insycle, you can standardize job titles, industries, locations, and other fields in your CRM on import.

To standardize records that you are importing from a CSV, use the Magical Import module. To standardize CSV data on import, use pre-built or custom-made functions in Step 3: Prepare Data.

You can save all import standardization settings using Templates. With templates, future import tasks will not need to be reconfigured, saving you time on all future updates, and ensuring your imported data is standardized on entry.

To learn more about the importing process, please visit this help article:

Import new records or update and append to existing from CSV

Let's cover how it works.

Step 3: Prepare Data. Optional Step: Cleanse, format, append, or tweak the data before importing.

In this step, you can prepare and update your data in various ways before importing. For instance, you can format specific fields, cleanse data, and perform other actions to cleanse and organize your data before importing.

For standardization, the Magical Import module offers a simplified version of what Insycle offers in the Transform Data module.

We’ll show you how to standardize job titles, industries, and locations before they are imported into your CRM database.

To do this, select the “Functions” tab. Here, you’ll be able to select a specific field and then a function to apply to that field.

prepare data step 3

In the example above, we are doing three things:

  1. Standardizing specific industries

  2. Standardizing specific job titles

  3. Standardizing US States (or Canadian Provinces)

In the Existing Text field, we put the text that we are expecting to find in our CSV file. In this example, we use “tech” and “Tech.” Then, in the “New Text” section, we tell it what we would like to replace the field with when Insycle finds a match.

So every record with the Industry listed as “tech” or “Tech” will be automatically updated to “Technology & Software.” You can add as many inputs as you would like to the Existing Text field.

Existing Text → New Text

  • tech|Tech → Technology & Software

  • vp sales|vp of sales → VP Sales

  • NY→ New York

Standardizing options are available for any field in your import CSV using the Map function.

The list of functions is long. To find functions that might apply to a specific field, you can use the search feature in the Function dropdown.

phone

Filter

The third tab on Step #3, Filter, allows you to filter data out of your import, based on fields and conditions that you set.

filter

In the example above, we are filtering our .CSV import down to only the included contacts that have a job title that contains the word “Founder.” Because we use “contains,” this will include records that have job titles such as “CEO and Founder,” “Co-Founder,” etc. The term “Founder” just has to be present anywhere in the field.

Preview Changes Before They Go Live

With Insycle, you can always preview the changes that you are making to your data before those changes are pushed to your live database. When you run any module in Insycle, you have the option of choosing between Preview Mode and Update Mode once you click the button.

Automation

You can set up ongoing data maintenance automation with Insycle on the module level using Templates, string templates together using Recipes, or integrate directly with Workflows in HubSpot.

Audit Trail and History

The Activity Tracker lets you review all changes made through Insycle. At any time you can download a CSV report of the operation and records affected.

Customer Data Health Assessment

The Data Health Assessment surfaces data quality issues that negatively impact your marketing, sales, and support efforts, and guides you through the process of fixing them. Here, you can keep an eye out for issues in your data and fix issues by updating in bulk.

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