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Episode 12
Data for Subscriptions Podcast

Understanding Enterprise Usage Data Demands in 2023

Guest

Andreas Zartmann

Andreas Zartmann
CEO at DigitalRoute

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Episode description

Understanding Enterprise Usage Data Demands in 2023

In this episode of the Data for Subscriptions podcast, host Behdad Banian and DigitalRoute CEO Andreas Zartmann delve into the findings of the latest global research on the challenges, needs, and strategies of more than 560 enterprises, mainly in the SaaS and media & entertainment industries.

The research examines the three main drivers for businesses: growing the business, improving customer experience, and protecting and optimizing the business. Within these drivers, specific business needs are identified, such as understanding product and service usage, adopting new business models and pricing, strengthening partnerships, managing data complexity, and ensuring regulatory compliance.

 

Highlights

There are two very clear needs that have been basically prioritized by the respondents; improving the business by understanding product and service consumption, and then followed by growing the business by understanding product and service usage. What is your reflection when you see this?

To me, it paints exactly what we’re discussing with our customers. You need to understand how your customers are using your services. You need to have control of your usage data for mainly three reasons; monetizing your insights, delivering a flawless customer experience… (and) optimizing your operations of the services.

Now on top of that, another clear aspect that this research shows is that many of the companies are looking on how to grow their businesses. They are looking on how to expand their businesses, and to do that, they need agility to deliver new packages, new pricing, new business models. Companies today come to a maturity level where they understand that this is data-driven, and specifically usage data-driven.

Why is it so that businesses do not necessarily understand the amount of their (data) complexity? And also, in this case, with issues related to revenue leakage. Why is that?

There are many different answers but let me just phrase a few ones:

First of all, you don’t have an end-to-end process overlook. You have a siloed approach of managing and processing data. Secondly, you’re not really thinking about this as a problem. Any customer interaction we have… and we talk around this–How much revenue leakage do you think you have? Because it’s a subset of what we solve for. It’s an outcome that we bring to the table, and we prove it for the customer as well. No one is really saying “We have a lot of revenue leakage,” because you don’t want to deal with that, or you don’t want to face it. Research says most companies have between 3 and 7%. Data shows that most of our customers have more than 10%.

So, it’s directly related to these two things; You don’t have an overarching perspective of all data processing, end-to-end, for the quote-to-cash process. And secondly, you don’t know what you don’t know.

Why I find this a bit interesting is that from a perception standpoint, is that large companies tend to be seen as slower moving, risk averse, not that agile. While smaller companies, especially the startup likes, are perceived differently; super fast, agile, just testing and learning and having this iterative approach. This research is indicating that the larger the company, the respondents have really put their hand up saying they need to be at the forefront and really drive usage-based consumption models.

There is a well-defined market and it’s a very competitive situation where you need to grow revenues by finding new revenue pockets and you do that by offering new ways of consuming services. And to do so, you need to be very much into your data management. You need to be proactive. They’re automating everything and they’re very much into this data-driven mindset and building automated processes.