Harnessing the Power of Data for Easier Partner Onboarding

Contributed by: Chenguang Ma, Product Owner

At Thunes, we are proud of our ability to enable seamless transactions. But when it comes to other processes – for instance, onboarding our customers and helping them start working with Thunes – simplicity and speed are equally important. 

Smooth customer onboarding is a crucial success factor for any SaaS company or B2B platform. Thunes is no different, so getting this process right is vital: for a start, it’s the first touchpoint with our customers, and we can’t afford to get off on the wrong foot. Secondly, successful onboarding enhances productivity across the entire product lifecycle. In today’s highly competitive landscape, even a few days saved in your growth journey can make a massive difference. So our team puts in a great deal of effort to enhance the onboarding experience and boost efficiency. 

This article looks at how we’re streamlining onboarding using data analytics.

The Challenges

Before a customer can start using Thunes’ services, they need to undergo an onboarding process that includes a compliance review, technical integration, and other legal and treasury requirements. And in our world, everything starts and ends with data. 

Here are some of the main items to look at: 

First of all, we need to ensure that the design of the onboarding system stores critical data points. Likewise, if data is stored awkwardly, it isn’t easy to extract into reports for analysis which slows down improvements. The potential impact of untracked data on the team is a loss of focus and failure to attend to important partners, and we risk losing new partners who get frustrated waiting to onboard. As onboarding involves multiple stakeholders, these hindrances also increase the prospect of running into the ‘blame game’, damaging team morale.

The second impediment to onboarding is when customers’ data is spread across multiple systems with no centralised repository. As crucial parameters can vary across different systems, it then takes additional resources to carry out the synchronisation of data. Multiple systems make it harder for us to identify critical bottlenecks, so we can waste hours tackling onboarding from the wrong angle.

Finally, data analytics should be automated wherever possible: manual extraction, processing and repetitive tasks are painful, can cause errors and delays, and should be avoided at all costs. And without properly automated analytic tools, it’s easy to miss the forest behind the trees.

The Solution

We start by defining the primary onboarding parameters to make it easier to benchmark against KPIs and data from different datasets. 

Our team follows a single source of truth (SSOT) framework to ensure that everyone bases decisions on unified customer data when building interfaces across multiple systems. 

We also ensure that we can go deeper into data tracking and view beyond status changes to identify when, who, where, and why the change took place. With a better understanding of the context behind the changes, we can develop targeted recommendations to improve our onboarding process, be it for a specific customer segment or specific geography. 

To tackle the challenge of automation and analytics, we employ modern data analytics technologies such as Data Lake and data visualisation. 

As an example of specific improvements, it used to take us a couple of weeks to update our Excel-based report with new data every month. Now, thanks to Data Lake and automated BI (business intelligence) dashboards, we’re developing dashboards that will display data in real-time. This enhancement will enable us to spend more time discovering customer insights and building solutions to serve our customers better.

And as we keep investing in new technologies, the process is guaranteed to get even faster in the future. 

Like to know how we can fast-track your onboarding journey? 

Chat to our friendly team today.