In the current climate, SaaS companies need new approaches to big data. The same old processes no longer work for her employees and customers, and new trends are emerging as customers demand more from her SaaS offering. To remain relevant and competitive in his evolving SaaS market, organizations must find innovative ways to leverage big data to understand their customers, needs, and the unique positioning of their products.
Here are three major big data trends in the SaaS industry. These are the trends businesses need to know now to stay ahead of the curve.
Trend 1: Increasing focus on product-led growth
One of the key strategies gaining momentum in the SaaS industry in 2022 is product-led growth. Product Led Growth is his SaaS strategy that uses the product itself to drive new business and customer retention. According to Gainsight’s report, 91% of SaaS companies plan to increase their investment in their PLG strategy in 2022, and 47% plan to double their investment in their PLG strategy. It says it does.
The PLG strategy is effective because it allows the customer to test the product before making the investment. This approach also allows customers to experience different types of software and easily transition between products. Of course, to execute an effective PLG strategy, SaaS companies must leverage big data. Product usage data and customer data are paramount to his effective PLG strategy as they provide key insights into the customer journey. It also helps provide signals about when to intervene on upsell or expansion opportunities.
With the above insights on growing interest in PLG, it is clear that big data will become more important than ever in the SaaS industry. Businesses not only need access to this data to build successful strategies, they also need to be able to draw conclusions from it to communicate the value of their products to their customers.
Trend #2: Reliability remains an across-the-board challenge
As the PLG strategy grows in popularity and SaaS companies increasingly rely on data, reliability issues remain. Collecting data across the customer lifecycle is one thing, but collecting accurate and reliable data that can have real impact is quite another. Although many new tools have emerged in recent years aimed at improving data quality, in many cases the data is still not as reliable as it should be. This challenge with trusted data is preventing SaaS companies from telling prospects and customers a unified, comprehensive story that can ultimately hurt their business.
To unlock the full potential of SaaS products, teams not only need access to accurate raw data insights, but also streamlined and consistent ways to interpret that data. To enable this, organizations must adopt tools that simplify data insight for both employees and customers. This is especially true for customer-facing teams such as Customer Success and Sales who are looking to prove the value of their products.
Trend #3: Data Accessibility and Efficiency Are Non-negotiable
We have established that PLG strategies are gaining popularity in the SaaS industry and access to trusted data is more important than ever. With this in mind, product usage data and customer data not only need to be accurate, but accessible to all necessary parties.
Data is very powerful, especially for customer-facing teams. It can be used to build a business growth strategy and build better relationships with customers. However, if this data is not easily accessible to those who need it most, it can lose its impact. To get the most out of your data, you need:
- Cleaned up and converted to a streamlined format that allows deeper analysis
- Stores more efficiently so large amounts of data can be stored and processed in seconds
- Simplified from a technical and complex format so that more people can use data to draw conclusions, create actionable plans, and incorporate it into tactics
Fortunately, several tools have emerged in recent years that aim to enable all of the above, but many SaaS teams are still trapped in silos of disparate systems. Platforms like Salesforce store vast amounts of data accessible to non-technical users, but these users require additional support and time to turn Salesforce data into actionable insights. It is often said that AI has the potential to fill this gap in the future, but there is still a long way to go. Ultimately, SaaS companies must enable non-technical employees to access, use, and derive insights from customer data in order to remain competitive in today’s landscape.
While it’s clear that big data is essential not only for customer-facing teams’ day-to-day tactics, but also for overall strategy development, strategy-making data alone is not enough to retain customers. To stay competitive in today’s economy, SaaS teams need to easily sift through data to tell a comprehensive story about product value at a glance. However, many teams cannot truncate their data without extensive support from his members of the technical team, limiting overall scalability and productivity.
stay ahead of the trend
Going forward, the next step for SaaS teams is to find easy ways to help non-technical team members transform ambiguous data into clear and compelling stories. This increased access to and trust in big data allows you to stay ahead of the curve, build successful strategies, keep operating costs low, and retain customers year after year.
About the author
Nikola (Nik) Mijic is the CEO and co-founder of Matik. Prior to joining Matik, Customer He worked in various positions and companies focused on helping success teams retain and grow their customers. At LinkedIn, we’ve built internal tools to make presentations more efficient by leveraging LinkedIn data. Nik was the first non-engineer hire at Bluenose Analytics, building a platform that uses predictive analytics to engage with at-risk customers and identify drivers of churn.
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