Sixth Insight - The Hidden C in Data

Sixth Insight - The Hidden C in Data

The Wheels of Ticketing - Desk Stories

The Hidden C in Data

[Importance of clean data]


Data cleaning

Data cleaning ensures ticketing systems' data is accurate, consistent, and complete. This process includes eliminating duplicates, fixing errors, and addressing missing information.
Quote
Clean data is happy data.

Why is data cleaning so important?

Data cleaning eliminates errors, inconsistencies, and duplicates within data, resulting in increased accuracy. Tools are available to help you swiftly address data issues. Enhancing accuracy enables the extraction of reliable insights. Inconsistent or inaccurate data can lead to misleading results, poor decision-making, and ineffective strategies.

Data hygiene

Data hygiene in a ticketing system refers to the processes and practices involved in maintaining accurate, complete, and consistent information. This is crucial for ensuring that customer support operations run smoothly and effectively.


  • Data accuracy
  • Data completeness
  • Data consistency
  • Data deduplication
  • Regular data audits


By prioritizing data hygiene, organizations can improve the efficiency of their support teams, enhance the quality of customer service, and gain valuable insights from reliable data analytics.

A story for better interpretation

Scrub your data clean

Once upon a time, a small but dedicated team in a tech company managed customer support through a ticketing system called "HelpNow." As the company grew, so did its customer base, leading to an overwhelming influx of support tickets. Although the team worked diligently, the increase in tickets created clutter. 
 
Once efficient, the HelpNow system became cluttered with old tickets, unresolved issues, and duplicate requests. Customer satisfaction started to decline as users waited longer for their problems to be resolved. Frustration lingered not only in the hearts of customers but also within the support team, which they found increasingly challenging to navigate through the cluttered ticketing system.
 
One day, the team lead, Joey, called for a meeting to address the urgent situation. "We need to scrub our data clean," he announced. The team discussed various strategies, but he had a vision of what needed to be done and a systematic approach to decluttering their HelpNow system.
 
The initial step entailed thoroughly reviewing and categorizing all existing support tickets utilizing a custom view. The team reached a consensus to archive tickets over six months old and lacked follow-up, as these were likely associated with resolved issues. To ensure efficient progress, they established a clear deadline for this undertaking, fully aware that collaborative effort and focused teamwork were essential for effectively addressing the backlog. Their strategic approach aimed to organize the current workload and foster a more streamlined process for ticket management.
 
Joey organized a “Scrub-a-thon” a week later, encouraging everyone to join forces. Each team member was assigned a category of tickets to review. Deleting duplicates became a friendly competition. Teams found ways to delete tickets using mass updates and automation, rewarding those who could clear the most entries. They quickly learned that many tickets had been created multiple times due to customers submitting the same request across different channels.
 
During this process, the team discovered an unexpected treasure trove of information. Many old tickets contained insightful feedback about the product, creating a new FAQ section that addressed common user questions. They also realized that some bugs needed urgent attention, leading to prioritized fixes for the product.
 
As the Scrub-a-thon continued, the team also acknowledged the importance of customer communication. They crafted an email update to inform customers about their efforts to improve support quality. Customers appreciated the transparency and felt confident that their concerns were being taken seriously.
 
After two weeks of hard work, their system was transformed. The volume of tickets had been dramatically reduced, and the remaining tickets were prioritized and categorized effectively for quicker solutions. Customer agents could easily navigate the system and focus on resolving issues rather than wading through a digital maze.
 
Reports generated from the cleaned data helped Joey and her team identify trends in customer inquiries and revamp their product support resources accordingly. Inspired by their findings, they implemented a new self-service help widget to empower users with immediate solutions. 
 
The results were incredible: response times dropped, customer satisfaction surged, and the support team thrived in their more organized environment. The HelpNow system became a case study in transforming mess into clarity, demonstrating the power of scrubbing away the unnecessary to unveil the valuable.

Best practices

Scheduled data audits

Scheduled data audits are the systematic process of regularly reviewing and analyzing data within a specific timeframe to ensure accuracy, compliance, quality, and relevance. This practice is essential for businesses and organizations to maintain the integrity of their data, identify errors, and ensure adherence to regulations and standard policies.

Removing inaccurate data entries

Removing inaccurate data entries means eliminating incorrect, erroneous, or misleading information entered into a system. These inaccuracies can occur for various reasons, including human error, technological glitches, data migration issues, or a lack of standardized procedures. 

Setting up field validations

Setting up field validations is crucial in ensuring data integrity and enhancing the user experience in any application. Field validations check users' input to ensure it meets specific criteria before being processed or saved. Validation rules in Zoho Desk help you overcome this problem by arresting incorrect data even before it can enter your help desk. Refer here for more details.

Detecting duplicate data

Duplicate data detection is crucial for maintaining data integrity and accurate records. The deduplication feature in Zoho Desk helps you find duplicate records in bulk and merge them.  Refer here for more details.

Addressing data security

Addressing data security involves implementing measures and practices to protect sensitive information from unauthorized access, breaches, and other cyber threats. Encryption takes the final stand against attempts to steal your data. It completes data protection by ensuring your data can neither be damaged nor stolen in the unfortunate event of a security breach.. Refer here for more details.

Inactive record management

Inactive record management involves managing records that are no longer in active use or required for daily operations. This encompasses outdated documents, files, or data that must be preserved for prospective reference, even though they do not require frequent access. In Zoho Desk, ticket management is simplified by automating the archiving of follow-up-less tickets over six months old by a deadline.. Refer here for more details.

Integrate data with analytics

Data analysis helps identify inconsistencies. Data analytics can automatically identify and flag inconsistencies within datasets. This helps agents quickly pinpoint errors or anomalies that might go unnoticed, improving the overall data quality. Data analytics can assess the quality of the data in real-time. It can provide metrics on completeness, accuracy, and consistency, giving agents the insights needed to ensure that the data they are working with is reliable. Refer here for more details.

Summing up

Ensuring a clean and accurate database is crucial for the effective operation of Zoho Desk. Data cleaning is not simply a one-time task; it requires a continuous effort to maintain the integrity and reliability of customer information. 


Establishing clear protocols and guidelines for data cleaning will ensure that agents understand their responsibilities and take accountability for upholding data quality. Mastering data cleaning practices will enhance your success.


Please stay tuned for more Desk Module stories.

 

Cheers,

 

Kavya Rao

The Zoho Desk Team

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