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The Need for Speed: How Product Teams Can Onboard Customer Data 90% Faster

Find out how agile product teams streamline customer data onboarding to save time and enable customers to experience their product’s value more quickly.

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You've just gained another customer for your groundbreaking product. As you start onboarding them, teams across the business realize how challenging manually importing customer data from various sources can be. As a result, they often find themselves sorting through spreadsheets—investing substantial time.

Data imports are one of your customers’ first interactions with your software, shaping the entire UX. However, many product teams still rely on rigid spreadsheet templates, manual reformatting, or custom import scripts—blocking resources and slowing down product delivery. Over time, this poor data onboarding experience can limit your growth potential.

To help you better understand how slow data imports can impact customer onboarding, this guide breaks down the key challenges product teams face in onboarding customer data. It also outlines best practices for streamlining your data import processes—helping teams across the organization save time while customers benefit from your product sooner.

Customer data onboarding can be a complex endeavor

To start our journey into customer data onboarding, let's take a closer look at some approaches companies across different industries typically apply to accept customer data:

  • Data onboarding templates can quickly become overly complex, leaving customers with extensive manual reformatting to do. At the same time, customer success or support teams must keep handling incorrect data formats from customers who are not able to meet the requirements.
  • Custom data validation and import scripts may seem like automated solutions, but creating them in-house can keep your engineering teams busy and divert them from improving your core product.
  • Data implementation services are often considered the most convenient approach, especially by established B2B software providers, but demand a substantial investment from customers.

For example, Next One Technology, a Swedish-based construction management platform, relied on a large Excel template for onboarding customer data. With each customer filling out this spreadsheet differently, data quality varied with every upload.

Price lists were a particularly challenging use case. As Eric Lindberg, Product Manager, explained: “The data was so diverse and regularly changing that our onboarding specialists kept stepping in to import it for users. For extra-large price lists, containing tens of thousands of articles, we also had developers split the data into separate files or even import it directly into the database. Still, despite all that effort and time, the imported data was messy and low-quality.”

Key challenges in customer data onboarding for product teams

Although each of the illustrated approaches is different, they all demand significant effort and confront product teams with a common set of challenges:

Messy data collection

Getting the right data from customers or suppliers can be more challenging than you might think. External data often comes from different sources and formats that your software may not support—resulting in messy spreadsheets that give internal teams headaches and frustrate users on the customer side.

Poor data quality

“Garbage in, garbage out”: Even seemingly minor errors, like misspelling a category name, can seriously impact data quality once entered into the target system. Unless you validate and clean the data beforehand, it can be challenging for product teams to make data-driven decisions.

Limited scalability

Managing large volumes of data manually across multiple departments is hardly scalable. Manual data reformatting or developing custom scripts demands significant investments in human resources—typically slow and costly to scale.

Data privacy concerns

Exchanging confidential data via email poses risks of unauthorized access and breaches. When importing sensitive information like customer, employee, or supplier data (e.g., billing details or social security numbers), ensuring a secure data onboarding process is key. 

Failing to protect this data may not only harm your reputation but also expose your organization to violations of data privacy measures like GDPR.

The cost of inefficient data onboarding 

Labor-heavy data onboarding processes can hardly scale and quickly become a roadblock to growth in the evolving global software market. We can better understand their consequences by calculating together:

Imagine a SaaS company specializing in HR management. They currently have 80 customers and manually onboard customer data. With an average monthly growth rate of 7%, they're adding around 6 new clients each month—and this number keeps rising over time.

After receiving customer data from a legacy system, internal teams review and prepare the data for import. They map the data to their system's format, validate, and clean it. This process may need a few revisions, including fixing errors and requesting missing data from customers. Depending on the data set’s complexity, the process can span from a few days to several months.

For our calculation, let's consider a moderate data set, which usually takes about 24 working hours within two weeks. In a year, the scale-up will gather a total of 180 customers. By then, the company will have invested 4,320 working hours in onboarding customer data. At an hourly rate of €30, this adds up to €130,000 spent on managing a process that is both time-consuming and error-prone.

This makes it clear that the company could have better utilized these resources—either by improving the core product or providing customer support on other important matters.

The cost of manual data onboarding

Even more important is that managing data imports usually becomes more complex as the business expands. Each new customer may introduce an edge case, and branching out into new segments can mean dealing with higher volumes of data in more varied formats and structures. That’s why establishing a scalable data import process that meets the business's needs is essential.

Strategies for fast customer data onboarding

Creating efficient processes for onboarding customer data not only streamlines daily operations but also enables you to deliver your product's value to customers more quickly. Let’s dive into some key strategies that can help you achieve this goal.

Streamline data collection

Collecting data systematically in a few key steps can boost both efficiency and effectiveness, saving you time and hassle:

  • Define clear objectives from the start. When you know the purpose of your data, you can focus your efforts and avoid collecting unnecessary data.
  • Automate tasks wherever possible. Using automation tools to clean and validate data before entering your system reduces the need for manual intervention.
  • Enable your product to ingest diverse data effortlessly. This capability ensures that your product handles various types of data—regardless of format, source, or complexity—catering to a broader range of use cases.
  • Encourage self-service data imports. Rather than collecting data from customers yourself, empower them to onboard the data through a self-service data import interface.

Ensure high data quality 

To facilitate data-driven decision-making, relying on a trustworthy dataset is key. For optimal accuracy and consistency across the data's life cycle, it's advisable to:

  • Validate the data to identify inconsistencies, errors, missing values, or outliers.
  • Clean the data to remove duplicates, normalize data, and handle missing values.
  • Standardize the data to ensure consistent formats, structures, and definitions across your organization.

Rely on dependable technology for data onboarding

Each stakeholder brings unique skills to the table. By leveraging dedicated technology solutions for data onboarding, everyone can contribute effectively—regardless of their knowledge.

Designed with non-technical team members in mind and offering user-friendly interfaces, these tools provide product teams with simplicity and versatility to manage data onboarding processes with confidence.

Agile product teams across various industries trust nuvo, a German-based provider of data onboarding technology solutions, to integrate reliable and secure data import capabilities into their software with ease. Let’s see how.

Get your product ready for fast customer data onboarding with nuvo

As we’ve already seen, manual data imports can hardly keep pace with the growing volume and complexity of data in today’s global software market.

For product teams aiming to future-proof their software for growth, it’s key to streamline data import processes with a technology solution without compromising data quality.

nuvo brings innovation in customer data onboarding with its AI-powered Data Importer SDK, designed to simplify the onboarding process for diverse datasets while ensuring the highest possible quality.

With nuvo's Data Importer, you can automatically validate and clean data against your database or third-party services like Google Maps

Whether your teams handle customer data onboarding internally or enable clients to manage their data directly, you can be confident that unpredictable and complex data imports will no longer hold back your product’s growth.

With nuvo's flexible Data Importer SDK, you can trust that:

  • You will effortlessly handle complex data with maximum accuracy, reducing manual formatting to the barest minimum.
  • AI learns your needs after your initial import, streamlining the data import process, so you only need to intervene when absolutely necessary.
  • Your developers won't have to deal with messy data imports anymore and will have more time to build the core product.
  • With automated steps and self-service data imports in place, customer onboarding/success teams can focus more on customer priorities.
  • Your imported data stays safe and secure as it's managed directly in the browser on the end-user side—not on external servers—until the import process is complete.

With all these benefits in mind, the global HR and payroll platform, Lano, could minimize errors and save significant resources by reducing the need for human involvement in data imports. Previously requiring a full working day, data imports now only take one hour with nuvo—an impressive time saving of 90%.

With a seamless data onboarding experience, you will save time and resources to make your product ready to scale and grow for the future while your customers enjoy its value from day one. If you're ready to discover how nuvo can help you on this journey, book a call with our team, and we will be happy to support you every step of the way.

The Need for Speed: How Product Teams Can Onboard Customer Data 90% Faster

 Michael Zittermann
Michael Zittermann
Co-Founder & CEO
Published:
May 27, 2024
Updated:
May 27, 2024
How Product Teams Can Onboard Customer Data 9x Faster

You've just gained another customer for your groundbreaking product. As you start onboarding them, teams across the business realize how challenging manually importing customer data from various sources can be. As a result, they often find themselves sorting through spreadsheets—investing substantial time.

Data imports are one of your customers’ first interactions with your software, shaping the entire UX. However, many product teams still rely on rigid spreadsheet templates, manual reformatting, or custom import scripts—blocking resources and slowing down product delivery. Over time, this poor data onboarding experience can limit your growth potential.

To help you better understand how slow data imports can impact customer onboarding, this guide breaks down the key challenges product teams face in onboarding customer data. It also outlines best practices for streamlining your data import processes—helping teams across the organization save time while customers benefit from your product sooner.

Customer data onboarding can be a complex endeavor

To start our journey into customer data onboarding, let's take a closer look at some approaches companies across different industries typically apply to accept customer data:

  • Data onboarding templates can quickly become overly complex, leaving customers with extensive manual reformatting to do. At the same time, customer success or support teams must keep handling incorrect data formats from customers who are not able to meet the requirements.
  • Custom data validation and import scripts may seem like automated solutions, but creating them in-house can keep your engineering teams busy and divert them from improving your core product.
  • Data implementation services are often considered the most convenient approach, especially by established B2B software providers, but demand a substantial investment from customers.

For example, Next One Technology, a Swedish-based construction management platform, relied on a large Excel template for onboarding customer data. With each customer filling out this spreadsheet differently, data quality varied with every upload.

Price lists were a particularly challenging use case. As Eric Lindberg, Product Manager, explained: “The data was so diverse and regularly changing that our onboarding specialists kept stepping in to import it for users. For extra-large price lists, containing tens of thousands of articles, we also had developers split the data into separate files or even import it directly into the database. Still, despite all that effort and time, the imported data was messy and low-quality.”

Key challenges in customer data onboarding for product teams

Although each of the illustrated approaches is different, they all demand significant effort and confront product teams with a common set of challenges:

Messy data collection

Getting the right data from customers or suppliers can be more challenging than you might think. External data often comes from different sources and formats that your software may not support—resulting in messy spreadsheets that give internal teams headaches and frustrate users on the customer side.

Poor data quality

“Garbage in, garbage out”: Even seemingly minor errors, like misspelling a category name, can seriously impact data quality once entered into the target system. Unless you validate and clean the data beforehand, it can be challenging for product teams to make data-driven decisions.

Limited scalability

Managing large volumes of data manually across multiple departments is hardly scalable. Manual data reformatting or developing custom scripts demands significant investments in human resources—typically slow and costly to scale.

Data privacy concerns

Exchanging confidential data via email poses risks of unauthorized access and breaches. When importing sensitive information like customer, employee, or supplier data (e.g., billing details or social security numbers), ensuring a secure data onboarding process is key. 

Failing to protect this data may not only harm your reputation but also expose your organization to violations of data privacy measures like GDPR.

The cost of inefficient data onboarding 

Labor-heavy data onboarding processes can hardly scale and quickly become a roadblock to growth in the evolving global software market. We can better understand their consequences by calculating together:

Imagine a SaaS company specializing in HR management. They currently have 80 customers and manually onboard customer data. With an average monthly growth rate of 7%, they're adding around 6 new clients each month—and this number keeps rising over time.

After receiving customer data from a legacy system, internal teams review and prepare the data for import. They map the data to their system's format, validate, and clean it. This process may need a few revisions, including fixing errors and requesting missing data from customers. Depending on the data set’s complexity, the process can span from a few days to several months.

For our calculation, let's consider a moderate data set, which usually takes about 24 working hours within two weeks. In a year, the scale-up will gather a total of 180 customers. By then, the company will have invested 4,320 working hours in onboarding customer data. At an hourly rate of €30, this adds up to €130,000 spent on managing a process that is both time-consuming and error-prone.

This makes it clear that the company could have better utilized these resources—either by improving the core product or providing customer support on other important matters.

The cost of manual data onboarding

Even more important is that managing data imports usually becomes more complex as the business expands. Each new customer may introduce an edge case, and branching out into new segments can mean dealing with higher volumes of data in more varied formats and structures. That’s why establishing a scalable data import process that meets the business's needs is essential.

Strategies for fast customer data onboarding

Creating efficient processes for onboarding customer data not only streamlines daily operations but also enables you to deliver your product's value to customers more quickly. Let’s dive into some key strategies that can help you achieve this goal.

Streamline data collection

Collecting data systematically in a few key steps can boost both efficiency and effectiveness, saving you time and hassle:

  • Define clear objectives from the start. When you know the purpose of your data, you can focus your efforts and avoid collecting unnecessary data.
  • Automate tasks wherever possible. Using automation tools to clean and validate data before entering your system reduces the need for manual intervention.
  • Enable your product to ingest diverse data effortlessly. This capability ensures that your product handles various types of data—regardless of format, source, or complexity—catering to a broader range of use cases.
  • Encourage self-service data imports. Rather than collecting data from customers yourself, empower them to onboard the data through a self-service data import interface.

Ensure high data quality 

To facilitate data-driven decision-making, relying on a trustworthy dataset is key. For optimal accuracy and consistency across the data's life cycle, it's advisable to:

  • Validate the data to identify inconsistencies, errors, missing values, or outliers.
  • Clean the data to remove duplicates, normalize data, and handle missing values.
  • Standardize the data to ensure consistent formats, structures, and definitions across your organization.

Rely on dependable technology for data onboarding

Each stakeholder brings unique skills to the table. By leveraging dedicated technology solutions for data onboarding, everyone can contribute effectively—regardless of their knowledge.

Designed with non-technical team members in mind and offering user-friendly interfaces, these tools provide product teams with simplicity and versatility to manage data onboarding processes with confidence.

Agile product teams across various industries trust nuvo, a German-based provider of data onboarding technology solutions, to integrate reliable and secure data import capabilities into their software with ease. Let’s see how.

Get your product ready for fast customer data onboarding with nuvo

As we’ve already seen, manual data imports can hardly keep pace with the growing volume and complexity of data in today’s global software market.

For product teams aiming to future-proof their software for growth, it’s key to streamline data import processes with a technology solution without compromising data quality.

nuvo brings innovation in customer data onboarding with its AI-powered Data Importer SDK, designed to simplify the onboarding process for diverse datasets while ensuring the highest possible quality.

With nuvo's Data Importer, you can automatically validate and clean data against your database or third-party services like Google Maps

Whether your teams handle customer data onboarding internally or enable clients to manage their data directly, you can be confident that unpredictable and complex data imports will no longer hold back your product’s growth.

With nuvo's flexible Data Importer SDK, you can trust that:

  • You will effortlessly handle complex data with maximum accuracy, reducing manual formatting to the barest minimum.
  • AI learns your needs after your initial import, streamlining the data import process, so you only need to intervene when absolutely necessary.
  • Your developers won't have to deal with messy data imports anymore and will have more time to build the core product.
  • With automated steps and self-service data imports in place, customer onboarding/success teams can focus more on customer priorities.
  • Your imported data stays safe and secure as it's managed directly in the browser on the end-user side—not on external servers—until the import process is complete.

With all these benefits in mind, the global HR and payroll platform, Lano, could minimize errors and save significant resources by reducing the need for human involvement in data imports. Previously requiring a full working day, data imports now only take one hour with nuvo—an impressive time saving of 90%.

With a seamless data onboarding experience, you will save time and resources to make your product ready to scale and grow for the future while your customers enjoy its value from day one. If you're ready to discover how nuvo can help you on this journey, book a call with our team, and we will be happy to support you every step of the way.

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