The Usage Data Revolution Report, Part 4 of 4: Reigniting Growth for Stalling SaaS Companies

The Research in Brief

The aftermath of the 2022 SaaS crash and the subsequent shift towards profitability has fueled the integration of AI technologies into product strategies. This convergence presents a lucrative opportunity for SaaS companies to monetize artificial intelligence, although only 15% of businesses made progress in this area in 2023, according to OpenView’s SaaS Benchmarks Report. The industry-wide move towards profitability, driven by declining growth rates reflected in the ProfitWell B2B SaaS Index, has prompted SaaS businesses to consider the effectiveness of usage-based pricing models, inspired by successful examples like ChatGPT’s strategy. This aligns with the broader trend of integrating consumption-based approaches to maximize revenue and enhance customer satisfaction. 

In parallel to these trends, our research, presented as a 4-part blog series, explores innovative strategies and trends in the utilization of usage data by enterprise companies and their leaders. Spanning from Q4 2022 to 2023, the study involved 1,364 survey participants from software and media & entertainment sectors, including managers, senior managers, and CXO-level executives, providing valuable insights into leveraging usage data and navigating data complexity for business growth. 

In this blog, you will get a rundown of specific strategies on addressing price sensitivity and executing price adjustments for Vertical and Horizontal SaaS.

Introduction

SaaS is broadly categorized into two types: Vertical SaaS – providing industry-specific solutions, and Horizontal SaaS – offering broad solutions applicable across multiple industries.  

As SaaS offerings continue to expand, businesses face common challenges such as customer churn, risk of stalling, and restrictions on growth caused by the current user base license model. Effective solutions require a targeted and nuanced approach, specific to the unique needs of the two different SaaS categories.

Strategies for Vertical SaaS

The following strategies are particularly effective in Vertical SaaS as they allow for tailored solutions that align with specific industry requirements. 

1. Shift the focus from maximizing revenue from existing customers to serving customers better. 
2. Introduce a freemium version of the software, allowing potential customers to explore and understand its value. 
3. Identify important business areas for customers and prioritize enhancing those functionalities by analyzing service consumption patterns. 
4. Understand usage patterns and preferences of customers through usage data analytics to gather actionable insights for product development and innovation, leading to better customer retention and conversion.

Strategies for Horizontal SaaS

The following recommendations are relevant for horizontal SaaS companies that need flexibility in pricing and licensing to cater to diverse customer needs.

• Introduce automation and digital solutions to streamline data collection processes, optimize data processing workflows, and improve overall operational efficiency.
• Scale their operations more effectively by adopting automation and digital solutions.
• Address the restrictions on growth posed by the current user base license model transitioning to a usage-based pricing model or adopting a hybrid pricing model. 

How to Increase Your Prices AND Win Customers Over

As the cost of living and business operations increase, businesses may hesitate to raise prices due to customers’ reduced budgets. However, presenting a price increase hastily can have a negative impact on customer retention. To effectively manage price sensitivity and minimize these consequences, it is vital to adopt a strategic approach to price increases that considers customer preferences. 

Determining the appropriate timing for a price increase entail gaining a comprehensive understanding of what customers truly value by analyzing their actual usage of a service. Usage patterns may fluctuate throughout the year, but ongoing monitoring through software can provide crucial insights. This enables the company to assess how their offerings are being utilized and evaluate customers’ likelihood of embracing a price increase.  

• Have a deep understanding of service consumption and price sensitivity. 
• Implement a usage-based pricing model – the most flexible and fair pricing model. 
• Put an anchoring effect in motion by presenting a desired offering at a higher price first before offering it at a slightly lower price. 
• Introduce extra features at different price points and draw attention to the extra value that comes with each. 
• Consider incremental price increases so customers aren’t hit with a substantial change in one go. 
• Conduct market research and gather customer feedback to understand price sensitivity. 
• Use different communication strategies for different customer segments. 
• Communicate the need for price increases as early as possible. 
• Use the descriptive nature of usage data to determine the best time to discuss a change in pricing with customers.

Participants in the Study

Research Facilitor DigitalRoute
Target Audience by Role Managers, Senior managers, CXO-level executives
Target Audience by Industry Software, Media & Entertainment
Data Source Online survey
Number of Survey Participants 1,364
Participant Industry Representation Software & IT, Media & Entertainment
Research Span Q4 2022 – 2023
Other Collected Information Participant functions, Company sizes, and annual revenue
Research aims to explore innovative strategies and trends in usage data adoption by enterprise companies and leaders
Research examines prevalence and significance of initiatives in utilizing usage data and navigating data complexity for growth
Survey was utilized to gather data from professionals accessing educational content produced by the company
Responses analyzed using statistical and BI tools  
Primary data collected with participant consent




Limitations of This Research
– The sample for the research is limited to participants who accessed educational content from the initiating company.
– The aforementioned limitation means that the sample may not fully represent the target audience. 
– The survey questions had a limited set of answer options, potentially limiting the capturing of a full range of business initiatives related to data utilization and growth. 
– The survey responses may be subject to response bias based on participants’ industry, function, or company size.