Manual vs Automated Data Maintenance: Don't Rely On Manual Maintenance

Data is the fuel that powers businesses, driving critical decisions, strategies, and operations. Companies that leverage accurate and up-to-date customer data enjoy a huge competitive advantage over those that don't. But maintaining data quality is a never-ending challenge that many companies struggle with.

From inconsistent data entry practices to integrations to constantly changing customer information, numerous factors can contribute to the degradation of data quality over time. Incomplete records, duplicate entries, formatting inconsistencies, missing connections between associated records, and outdated information can quickly accumulate, leading to inefficiencies, missed opportunities, and damaged customer relationships.

To combat these data quality issues, organizations have traditionally taken one of two main approaches: manual data fixes within their CRM interface, or Excel-based cleanup.

The manual approach involves identifying and correcting data errors one by one, often through tedious and time-consuming processes that weigh teams down and hurt morale. Fixing issues through Excel, using advanced formulas, is not much better. A single field may have a number of different variations, requiring many Excel formulas to clean them all up.

On the other hand, automated solutions like Insycle offer a more proactive and efficient method of maintaining data quality through continuous monitoring and automated cleansing routines, freeing employees from monotonous data updates and allowing them to focus on more strategic tasks.

Manual CRM Data Updates vs. Data Automation With Insycle

The gap between manual data maintenance and updates in your CRM and automation is gigantic.  

Let’s compare some of the common outcomes of the two approaches.

Automation changes the game for companies in terms of data quality and the reliability and usability of data in their system.

“With the automations and training, the frequency of use will decrease, which is what you want with this tool. Onboarding team super accessible and helpful.” - Julie L., G2 Review

The Manual Approach to Fixing CRM Data: Temporary Fixes and Endless Effort

The traditional method of manually identifying and correcting data issues one record at a time is a labor-intensive and continuous battle. This approach typically involves teams of data specialists meticulously combing through databases, spotting errors, then manually updating each record individually.

But many CRMs build their interfaces for general ease of use, without considering how cumbersome that might make updating data. Sometimes, fixing a single small issue can mean clicking through a handful of screens, or even having multiple tabs open so that you can get the additional context that you need from other screens in your CRM.

Not only is this process incredibly time-consuming, but its inefficiencies are compounded as data volumes continue to grow. What may have been a manageable task with a smaller dataset quickly becomes an overwhelming challenge as the size and complexity of the data increase. Organizations can find themselves allocating significant resources and personnel solely dedicated to manual data cleansing efforts. If they don’t, they must find a way to deal with all of the problems caused by those data issues.

Further, the manual data fix approach is highly susceptible to human error and inconsistencies. Even with rigorous training and standardized procedures, the monotonous nature of manually updating record after record leaves ample room for mistakes to slip through.

Perhaps most crucially, manual data fixes provide only a temporary reprieve from data quality issues. As new data is continuously added and existing records are updated, new errors, duplicates, and inconsistencies immediately start to accumulate again. This creates a never-ending cycle of manual data maintenance in which organizations must constantly play catch-up as they strive to maintain data integrity.

In an era where data is a crucial asset for business success, relying solely on manual, one-time fixes is unsustainable and inefficient.

“The support team at Insycle is some of the best in the technology industry. (This is not an exaggeration) I am comparing this to Hubspot itself (which is high class as well).” - Erik G, Business Owner, G2 Review.

The Automated Advantage: Continuous Data Quality Assurance

In contrast to the manual approach, automated data maintenance solutions like Insycle offer a paradigm shift. Rather than relying on periodic, one-off fixes and endless manual effort, organizations can maintain high-quality customer data using Insycle’s continuous, hands-free data cleaning capabilities.

At the core of Insycle's offering is its ability to monitor data quality constantly, identifying issues as soon as they arise. Through seamless integration with popular CRMs like Salesforce and HubSpot, Insycle can detect errors, duplicates, inconsistencies, and outdated information, and fix them on an ongoing basis.

Then, Insycle templates can be scheduled to run on a set schedule. For example, you might clean and deduplicate your database daily, so that your sales team has a clean slate to work with each day.

This proactive approach to data maintenance ensures that organizations can maintain a perpetually clean and accurate database, free from the plaque of accumulated data quality issues. By addressing errors and inconsistencies as they occur, Insycle eliminates the need for resource-intensive manual cleansing efforts, saving valuable time and resources.

Additionally, Insycle's automated processes significantly reduce the human error that plagues manual data fixes. With predefined rules and standardized protocols, Insycle can consistently apply data quality standards across the entire database, ensuring a level of accuracy and consistency that is impossible to achieve through manual efforts.

As data volumes grow, the scalability of automated solutions like Insycle becomes increasingly valuable. While manual data maintenance efforts quickly become overwhelmed by the sheer size and complexity of large datasets, Insycle's automated processes can handle even the most massive data volumes with ease, providing a future-proof solution for data quality assurance.

Example 1: Automate Advanced Deduplication and Avoid Sales Rep Overlap

CRM duplicates are a problem that cause many revenue-limiting issues throughout an organization.

Often in CRMs, you are severely limited in how you can identify and merge duplicates. Usually, CRMs identify duplicates in precise ways, using a few specific fields to match potential duplicates, with no way to customize which fields are used. This means they can’t identify the many duplicates in your database that can only be matched using non-standard fields.

Additionally, most CRMs are only able to match two duplicate records at once. You have to analyze the detected duplicates by hand to ensure that they are truly duplicates before merging them. Post-merge, most CRMs give you little-to-no control over which data is kept from which duplicate record.

This highly manual process is time-consuming, error-prone, and inefficient.

With Insycle, you can merge duplicates in bulk and automatically, using any field in your database as a matching field.

Insycle is super-flexible, allowing you to use any field in your database as a duplicate matching field. You can also set rules for how Insycle will evaluate the data within the fields that you choose. Then, you can schedule your deduplication template to run on a set schedule—hourly, daily, weekly, or monthly.

With Insycle’s Merge Duplicates module, you can also control how data is retained from the merged records. You can set rules for retaining data for individual fields, settings rules for determining which data to retain or even collating all of the data from a group of duplicates, ensuring that you never lose important data during the merging process.

For example, you can retain all values in multiple checkbox fields in HubSpot. In contrast, using HubSpot’s default data retention during the merge rules, you are only able to retain the selections from the most recently created record in your CRM database.

Insycle makes powerful deduplication automation simple, while giving you full control over how the merge takes place.

Example 2: Automatically Standardize Location Data for Accurate Reporting

With Insycle, you can automatically standardize addresses, states, zip codes, and other location-based fields on a set schedule, allowing you to do more accurate reporting.

For example, using Insycle, you can standardize U.S. states easily, formatting the field for full state names or abbreviations, eliminating additional variations for all fifty states.

Here’s how they would look using the U,S, state formatting template:

Or, you could standardize country names, ensuring that you always have consistent country data for routing leads, segmenting, reporting, or analyzing your CRM data.

Here’s how the changes would look using the Stadardize: Country Name To Code2 template.

You can also Standardize street addresses to ensure that they are properly formatted, capitalized, and ready for use in reporting or marketing campaigns.

Here’s what the changes made by this template would look like in your CRM:

Then, you can schedule any of these standardization template to run automatically, on a cadence of your choosing. That way you can ensure that your reporting is accurate and the decisions that result from that reporting are sound.

Example 3: Automatically Link Associated CRM Records for a Complete Account View

Associating CRM records is critical for developing a full view of every lead and account. You need to be aware of how contacts relate to companies and deals to be able to provide stellar service to each one.  

With Insycle, you can associate contacts to companies and other record types automatically. You can identify missing associations flexibly, using any field in your database as a matching field.

For example, you can associate contacts to companies using the contact’s email domain and the company’s website domain.

You can also associate records using multiple similar, related fields. For example, you can match associations using a phone number field and mobile phone number field.

Additionally, Insycle can identify missing associations by evaluating existing associations. For example, a contact, company, and deal should all be associated with one another. But often, one of these links is missing, such as that between the contact and the deal. In such a situation, Insycle will complete the triangle by associating the contact with the deal.

Then, any association template can be scheduled to run hourly, daily, weekly or monthly to ensure that a complete overview of the accounts is consistently maintained.

With Insycle, you aren’t limited to contact-to-company association, either. You can associate any contact, company, deal, or custom object amongst themselves, in any of Insycle’s supported CRMs. Additionally, some specific platforms, like HubSpot, allow you to associate other objects such as HubSpot ticket association.

HubSpot users can also inject association templates into HubSpot Workflows. This is a significant upgrade, as you cannot set associations in HubSpot Workflows using the default features.

With automatic associations, you can ensure that your sales and marketing teams have a full understanding of all records pertaining to a specific account or deal, making them more effective in the way that they engage with customers, and delivering better experiences.

“Keeping a clean database as your system of record is critical for reporting and analytics. Having this data cleaned up in the CRM is also important because when we’re making decisions for the business, with the way our economy is going, it is more important than ever to tackle this situation head-on versus letting it continue to pile on.” - Bill Martinez, Director of Business Operations, The Guarantors

Embrace Automation, Unlock Perpetual Data Excellence

Insycle’s automated, continuous data cleaning solution frees companies from the downsides of manual data maintenance, allowing them to provide better experiences to customers and employees alike.

Automatic data cleaning lays the foundation for dependable data quality and smooth operations. With data maintenance automation, organizations can future-proof their operations, mitigate risks, and position themselves for growth.

Want to learn more about how Insycle can help you flip your HubSpot data management practices on their head, freeing you to focus on more strategic tasks across your organization? We invite you to learn more about Insycle for HubSpot.