Data Onboarding

What is Customer Data Onboarding? And How to Automate Your Process

Written by 
Katrina Kirsch
September 27, 2021
6 Benefits of Automating Your Customer Data Onboarding 1. Faster time-to-value 2. Free up internal resources 3. Ingest clean, structured data 4. Reduce costs 5. Empower end users 6. Increase revenue

You've just signed a new customer, and it's time for their data onboarding. As the first meaningful interaction with your brand, this is the moment to make a great first impression.

But most of the time, customer data onboarding isn't a smooth process. In fact, over 90% of customers feel that businesses "could do better" when onboarding new customers.

That's because data onboarding usually involves emailing CSVs back-and-forth with customers to get the right data. Then your customer facing teams have to wait on the data and engineering team to clean, validate, and ingest the data into your operational systems. This whole process can take weeks or even months to complete.

Instead of a seamless process, the time-to-value for customers is delayed often leading to frustration, and ultimately, a poor customer experience.

If your team is ready to enhance its customer data onboarding experience, it's important to understand how the right approach makes onboarding data faster, better, and more streamlined.

Let's take a look at the details of B2B customer data onboarding and six benefits of automating your process.

What is Customer Data Onboarding?

Customer data onboarding is the process of bringing clean external data into applications and operational systems so customers can use the platform, product, or software. This data can arrive from various sources, such as CRMs, databases, or spreadsheets. But the goal is to exchange data between your customer's system and your own so they can start using your products, have that “aha” moment and see the value immediately.

The faster the data onboarding, the better. Nearly two-thirds of customers say that onboarding support is an important consideration when deciding whether or not to buy. So upholding any promises and making this valuable touchpoint seamless is essential for a stress-free experience.  

One of the biggest challenges is populating your product with your customer's live data as quickly as possible. The thing is, importing external data is typically a complex process. Most companies have reduced the problem to the lowest common denominator of trading FTP+CSVs then manually uploading data files into their system—a terrible experience for all parties involved.

manual customer data onboarding is painful
Manual customer data onboarding is painful

Relying on these archaic, manual processes leads to internal bottlenecks, data quality issues, and delaying revenue. These issues take shape in a number of ways:

  • Manual data imports: Before importing data, it needs to be cleaned and mapped to match the destination schema. Manual data wrangling and cleansing delays the onboarding process and takes time away from engineering and data teams. 
  • Finding errors: Poor quality data is expensive. IBM estimates that bad data costs the US $3.1 trillion per year. But finding and fixing errors in datasets is time-consuming work. People in data transformation face extreme deadlines and often only have time to make corrections without tracing errors back to the root cause—and preventing them from happening again.
  • Managing issues: Data silos, custom python scripts, slow communication, and unsecure back-and-forth emails all slow down the data onboarding process. Correcting these challenges not only involves your customer service, engineering, and data teams but your customers' teams as well.
  • Being retroactive instead of proactive: Would you rather have a team that's constantly putting out fires or creating innovative solutions for customers? If your data onboarding isn't streamlined, your customer service, data, and engineering team will have to spend time on tasks that are important at the moment, but do little for the bottom line. 

All of these sticking points slow down data onboarding, which often results in a confusing and frustrating process for customers.

There is a better way to import customer data. Turn one-time data onboarding into a health data relationship with Osmos Pipelines. Using an AI-powered data transformation tool, your customers can easily share structured data between their system and your own.

6 Benefits of Automating Your Customer Data Onboarding

6 Benefits of Automating Customer Data Onboarding

1. Faster time-to-value

A quick data onboarding shows that your team is capable and credible. It both improves the customer experience and immediately builds trust. With time and trust on your hands, it's easier to create value for your customers. This could mean helping customers provide their users with a great data sharing experience or use the structured data to customize an upcoming campaign.

The ability to quickly prove your value makes a good impression, which can lead to long-term loyal customers. Deloitte found that a positive customer experience can increase spending by 140%. On the other hand, 89% of people have switched to a competitor after having a poor customer experience with a company. 

The faster the data onboarding, the more time you have to create value for new customers and grow your business.

2. Free up internal resources

Data onboarding requires time and effort from both your team and your customers or partners. Months can be spent gathering, cleaning, transforming, and ingesting data. Not surprisingly, research firm Ovum found that approximately 40% of enterprises take over 30 days to onboard a new trading partner. That time and pain compounds if you have hundreds—even thousands—of trading partners, plus onboarding new customer data.

With automated data onboarding, everyone gets time back. Engineers, data, and customer support teams can focus on high-impact tasks instead of putting energy into fixing errors or managing bottlenecks. Without custom scripts, there's also less maintenance and manual data mapping.

For Mosaic, a resource management software that gives companies greater visibility into their projects, building a smart data uploader would have taken up to a year to complete. By using Osmos Uploader, the team simplified data onboarding and prioritized their own product strategy. 

"Building an uploader for Mosaic with the kinds of validations and customizations we needed was going to be a 6-12 month engineering roadmap. Osmos Uploader gives us all the features we need to provide our end-users a delightful data sharing experience, and I get the time back to focus on our core product," said Nima Tayebi, the CTO of Mosaic.

Ultimately, freeing up internal resources helps you stay focused and competitive in the market.

3. Ingest clean, structured data

If two people speak different languages, it's tough to communicate seamlessly. Data is no different.

Using an automated data onboarding system is like having a translator. It smooths out communication by transforming datasets into a standard format that both systems understand. You can ingest data from nearly any source—log files, CSVs, or JSONs, for example—and get it into a usable, structured format with a few clicks, not code.

Osmos takes the pain out of importing messy external data into your operational system

For Aaron White, the CTO of Blissfully, translating sources and schemas was an agonizing process. 

“Our SaaS platform allows customers to understand their data. But we can only do that if we integrate and translate a very long tail of sources and schemas—a painful engineering challenge. Osmos bridges the integration gap, and their AI even automates the majority of schema mapping," he said.

Structuring and cleaning data with no-code data transformation cuts down the time needed to prep data for comparison, aggregation, and analysis. With Osmos, two different systems can talk to each other as easily as sending a Slack message (in a common language, of course). 

4. Reduce costs

Beyond the opportunity for increased revenue, an automated data onboarding tool also reduces the effort associated with data wrangling and building data pipelines.

For Rahi, an IT company that increases the efficiency of business operations, the cost of data transformation was impacting client budgets. 

"Osmos saved us over 60% on delivery costs with our largest clients by simply removing tedious copy-paste and manual data wrangling activities. Osmos Pipelines has become a strategic enabler of our global platform, making it easier to bring solutions to our customers, partners, and distributors," said Matt Robinson, the CTO of Rahi.

The opportunity to help customers impress their clients is priceless. But continuing to use manual data onboarding processes can cost your company its clients. Instead of focusing on providing value, you're keeping an eye on costs.

5. Empower end users 

Say goodbye to placing the burden on data and engineering to handle all of your customer data onboarding and maintenance activities. Now internal teams can easily onboard data into your operational systems in minutes, without writing code. With a few clicks, you set up automated data pipelines that can quickly ingest your customer’s data and accelerate their time to value with your products.

osmos no-code data pipelines

6. Increased revenue

Customer data onboarding solutions like Osmos can drastically reduce data onboarding time from months to minutes. This drives a very important company benefit: your company can begin using your customer’s data and they get to achieve the results they want with your product. In turn, customer satisfaction improves and reduces churn.

Automate Your Customer Data Onboarding with Osmos

All of your customers are impacted by your data onboarding experience, so you want to make sure it's simple, delightful, and secure. Using low-code data onboarding solutions like Osmos will leave a good first impression—one that your customers will remember as smooth, efficient, and stress-free.

Should You Build or Buy a Data Importer?

But before you jump headfirst into building your own solution make sure you consider these eleven often overlooked and underestimated variables.

view the GUIDE

Katrina Kirsch