DataPrep enables export of cleansed data into Zoho CRM and it's a game changer


An error and duplicate-free CRM data can make a world of difference for your sales team.

There are many benefits. Here are just the key ones:
  • Your sales person does not have to deal with duplicate entries as and when they spot them.

  • Without errors and duplicates, the assessment of sales funnel becomes accurate. Leads to better understanding and tweaking of sales processes

  • Your sales team can move confidently with consistently accurate prospect information

We're thrilled to announce an update to our Zoho CRM integrator that enables users to create data pipelines. It gives sales teams using Zoho CRM, the benefits listed and a lot more.

DataPrep's CRM connector now closes the end-to-end data pipeline loop: Zoho CRM -> Zoho DataPrep -> Zoho CRM.

Businesses can leverage DataPrep's easy-to-use transformations to cleanse, format, and enrich sales data. They can automate schedules that apply rulesets to datasets and keep CRM data reliable at all times.

[You can also take a look at our comprehensive CRM Solutions powered by Zoho DataPrep.]

Addressing the common issues

Your business brings data into your CRM from multiple touch points. These are different systems gathering data—either online through forms or offline at events. Unfortunately this allows errors and inconsistencies to creep in.

Here are some ways DataPrep can help maintain quality data:

1. Duplicate records

Duplicates are unavoidable while capturing leads. Duplicate entries create multiple headaches for the sales team. The deduplicate transform in Zoho Dataprep is an easy yet effective way of addressing the problem. Watch the video below for a quick primer on ways to address some of these issues with CRM data.

2. Matching and appending datasets accurately

Your CRM data comes from web forms, events data, third-party data, and more.

Zoho DataPrep's data blending will help you blend all this data into a single dataset, ready to be synced with Zoho CRM. Bear in mind here, though, that merging datasets is still a first step. You have to apply transforms and ensure standardization before exporting it to CRM.

3. Dealing with invalid entries: by correcting the value or eliminating the record

Invalid entries in CRM records can be treated two ways: either you salvage the entry using transformations, or delete the records so it doesn't cause concerns later.

Scenario 1:Salvaging the invalid entries using transformations

Let us consider an example where two sales datasets are being merged - a lead-capturing web form and a marketing event database. Though both databases capture similar leads, the way they record it varies: the event database might record customer data as a text type entry like "Converted" or "Not Converted". Similar data in the web-form-based lead capturing records the data as a boolean type entry: "True" or "False".

When the records are merged, the data—though contextually meaning the same—becomes invalid. In such a scenario, the CRM admins can analyze why the data is invalid and use a simple Find and Replace transformation to change all the instances of "Not converted" to "False".

Scenario 2: Where deleting makes sense

There are also times when a business can't salvage its invalid data. Once a database is imported into Zoho DataPrep, users can use the search and filter function and select "filter rows with invalid values" to closely examine the nature of invalid entries.

Let's take the case of a monthly sales record. Some entries in the database show gibberish text instead of the sales figures. In such a scenario, without a valid value to fill in, it's best to delete the data.

Allowing such invalid entries to persist will negatively influence downstream processes, like sales data analytics and forecasting.

4. Standardize entries with ease

It's difficult to capture consistent, standardized entries in your lead forms. For example, different people can enter a location in different ways: "United States", "United States of America", "USA", etc.

Zoho DataPrep's Cluster and Merge operation will help identify different versions of your data and standardize it to the version your business uses. For example, if you prefer to have a standard "United States of America" to denote the country, then Cluster and Merge will replace the instances of "United States" and "The United States of America" with it.

Safeguards while operating the data pipeline

Zoho DataPrep is a tool that enables non-technical users—or specifically people who are'nt data engineers—to perform data wrangling with ease.

We have some safeguards in place to run the data preparation process on sales data without any anxiety:

  • Granular control of how data sync is executed

  • Using target matching to prevent errors

  • Option to rollback sync in case of partial export failure

Granular controls

At the time of export to Zoho CRM, users can choose one of three options: add only new records, only update existing records, or both add and update records.

CRM admins can also contextually determine how to export records.

For example, in case you imported records from your Leads module for deduplication and cleansing, and are exporting them back to the same CRM module, you can choose to update existing records, while also having an option to delete the duplicate records.

Zoho DataPrep also prompts you to review the records that are marked for deletion.

 

Target matching to prevent errors

Zoho Dataprep also has a target matching feature to help users ensure that their prepared data's schema matches that of the CRM module to which the export is being executed.

This is a proactive alert—meaning target matching will alert users, even before exporting, to the errors, such as column mismatch, data type error, and data format errors.

The target match errors dialogue box gives users the option to fix data schema errors beforehand.

Learn more about target matching here.

Rollback in case of errors

There are also times when export might fail partially. This can happen because of extraneous reasons, like network problems—or you may want to undo the export to revisit and course correct your data preparation process.

In such cases, you have the option to roll back the export and restore the records back to their previous state.

We hope you find the latest update useful. You can reach out to us if you want a personalized demo.



 

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