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It’s time for businesses in the SaaS industry to rethink how they utilize and access data. As the economic climate is shifting in 2023, customers are rightfully demanding higher levels of service, customization, and proof of product value. With these changes taking place, SaaS companies need to reevaluate and fine-tune how they use data to prove product value and navigate the competitive landscape.
In this blog post, we’re exploring three data-driven trends that companies in the SaaS industry need to get ahead of in order to remain competitive in 2023.
A trend that gained momentum in 2022 and will likely continue in 2023 is a focus on product-led growth. Product-led growth, or PLG, is a strategy in which SaaS companies use the product itself to drive customer acquisition, retention, and expansion. Last year, 91% of SaaS companies planned to increase their investments in PLG, and these investments are likely to continue in 2023.
PLG strategies are helpful because they enable customers to try products before they invest in them. With PLG strategies, the product sells itself. This method makes it easier for customers to experience the product. Data is an essential part in developing and understanding the success of PLG strategies. Companies that continue to emphasize product-led growth in 2023 will need to be data-driven in order to understand the customer journey, measure the effectiveness of their strategies, and recognize opportunities for expansion.
As mentioned above, SaaS companies need to be data-driven in order to drive successful strategies in 2023. However, in order to get the most out of data, it has to be reliable. Insights that come from inaccurate or inconsistent data may present a whole new set of challenges and unearth more questions than answers. As SaaS organizations bring more data to the forefront of conversations with customers, they must also find ways to improve its quality and reliability.
In order to do this, SaaS teams need to improve the processes behind gathering data. Teams should have access to accurate data and should be able to easily translate it into data-driven presentations and narratives to share with customers. This will enable them to prove product value more effectively, which in turn will improve customer retention and trust.
As mentioned above, reliable data is essential for SaaS companies that wish to build PLG strategies and prove product value. But accuracy isn’t enough—this data also needs to be accessible by all necessary parties in order to scale processes.
Ultimately, data isn’t as effective as it can be if the right people don’t have access to it. Data needs to be organized and streamlined so that team members can gather key insights and deliver them to customers as needed. It also needs to be stored in an efficient manner. SaaS teams that house their data efficiently will be better equipped to gather actionable insights from data, build data-driven stories, and share them with customers. When these processes are scalable, entire teams will be able to utilize data in every stage of the customer journey. If an entire organization is data-driven rather than just a few individuals, they’re likely to experience better retention rates, increased customer loyalty, and stronger customer relationships.
In recent years, many tools and software platforms have emerged to make data more accessible and scalable. While many organizations have improved processes by housing large amounts of essential data in CRM platforms, it’s often difficult and time-consuming for non-technical users to navigate and make sense of it all. Many SaaS companies rely on technical team members, like data and insights teams, to obtain, utilize, and tell stories with customer data. However, this is not the most scalable and effective method. Instead, SaaS companies need to empower their non-technical team members to be able to access data and tell stories with data on their own.
In 2023, SaaS companies need to implement processes and tools that enable their CSMs, sales reps, and other customer-facing teams to access the data they need to do their jobs, without relying on other teams. This will eliminate data silos, streamline processes, and enable each team member to be more data-driven in their interactions with customers.