Enterprise

How to Automate Master Data Check-Up Up (for PQL and MQL)

Onboarding new customers can be a time-consuming and tedious task. Customer Success Managers need to check customer master data and settings information manually, taking up precious resources. We all know there are two central parts when a new customer comes to your business.

The first part is when they booked a call, filled out a form, or signed up for any free online seminar. What you want to do is you want to know who you are talking to. Therefore, you can use tools like People Data Lab, Clearbit, or Airtable with ZoomInfo.

These tools can be used to enhance your customer's master data and then transmit it directly to your CRM (Customer Relationship Management). This is completely automated and is part of our onboarding Data Check. And the second aspect is that we all want to know if the data collected when a consumer filled out the contract is accurate. We would want to have this company's VAT checked; you can as well use 1SaaS.co to verify a VAT Code All we want to know is whether this firm is located at the address it claims.

Challenges faced by CSMs or BDRs

Before uploading client master data, CSM (customer success manager) must carefully check for accuracy and any duplicates in customer information provided via onboarding sheets. This is a high-stakes task that cannot afford any major errors. However, many CSMs are not Excel savvy which can lead to mistakes in the checking process. Additionally, they need to compare already uploaded settings while they check customer master data which adds another layer of complexity to this process.

Customer Situation with Data Check-ups

Two components of Data Check-ups that are critical for businesses and customers to tackle. First, when a new deal or lead comes in, quantify, and validate the data with external data so that you are well-prepared for your transaction and call. The second step is to assign the contract or send out the offer to ensure that the data is valid. So, we do not want to offer an Excel document to the Customer Success Manager or the Sales Manager when we do this. We wish to show this information in a CRM system like Salesforce, Pipedrive, or HubSpot.  

We want to see if we already know this by checking for duplicates and comparing it to previously uploaded data. So, for example, the corporate name may have changed. After that, we save hundreds of hours of manual research before a sales call. To find the data, you must use LinkedIn or Google, which takes time. You lose five to ten minutes every time a new deal or lead comes in instead of utilizing People data laps or clear bids straight to obtain the facts you want to know about your consumers.

The second stage of data verification comes when you fail to compare and examine the data, we collected for one of our clients. In this situation, they sign up with false info that does not match the VAT number.

Result on Master Data Check-Up Automation (for PQL and MQL)

Consider starting work before receiving an initial payment. You may lose all your earnings if you signed up for a fraudulent customer. We can avoid this from happening for your organization with our Master Data Check, which we give to our customers in special projects. To validate firm data to enrich deals and leads, as well as to immediately integrate this information into any type of CRM system. A contract also confirms that the transaction status and the company they claim to be are correct before a company signs. So, you never take chances.

This tool is now used for every onboarding process. By automating checks for customer data accuracy and eliminating manual processes, CSMs have been able to save 30 minutes per onboarding which adds up quickly over large numbers of customers! In addition, there are fewer errors due to improved accuracy from automated scripts running instead of manual checks done by non-Excel savvy employees.

PQL Vs MQL – what is the difference?

Automating the master data check for PQL and MQL is essential for ensuring accuracy and efficiency. PGL stands for Purchased Quantity Ledger and MQL stands for Making Quantity Ledger — both of which contain important material information used in production.  

Here are the 5 steps to Automate Master Data Check for PQL and MQL:

  • Confirm PGL and MQL records
  • Verify material specifications
  • Cross-check against standard values
  • Identify discrepancies with master data
  • Identify discrepancies with master data

Following these steps will simplify the process of auditing PQL and MQL production operations — saving time and money.

Conclusion on Master Data Check

Onboarding new customers do not have to be an arduous task with time-consuming manual checking processes prone to error. With automated tools, you can streamline your onboarding process while saving time and reducing errors thanks to accurate results delivered quickly through automated scripts! Whether you are just getting started with Airtable or already an experienced user looking for more advanced functions such as scripting automation checks, you will be able to find plenty of helpful tips on our blog about how you can use tools for your business needs!

Feel free to contact Makeitfuture with your challenges and let`s solve them together!

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