Monetization in B2B SaaS industry and optimizing customer segmentation model

Abstract

This in-company project aims to identify the winning monetization strategies in the B2B SaaS industry which Teamleader can potentially tap into, and at the same time, identify the most optimal customer segmentation model through quantitative analysis. Chapter 1 talks about Teamleader as a company, its history, value proposition, product offerings, presence in the EU market, and the direction of the company. This chapter also talks about the evolution of Teamleader from product - platform through the marketplace, and its most recent project launch during 2018's work smarter event, which was the €1M integration fund. Chapter 2 outlines the scope and limitations of the project statement which mainly revolves around monetization and customer segmentation, as these are the main objectives and deliverables of this market research. The project statement also requires a detailed study and report on competitor's monetization strategies as a benchmark, a proposal on new/adapted revenue streams which the researchers would like to further explore on, an interactive revenue model to show its impact, and a quantified customer segmentation model through the use of relative preference analysis and Van Westendorp's price sensitivity meter. Chapter 3 enumerates the 3 different key drivers of SaaS: Acquisition, Retention, and Monetization. This chapter provides both a literature review and internal data from Teamleader on the different strategies that the company has been doing in relation to these drivers. Moreover, a thorough competitor's analysis was also conducted in order to benchmark some monetization strategies which are currently being used in the market. Lastly, the proposed monetization strategies of the researchers were also discussed in this chapter and its foreseeable impact to Teamleader. Chapter 4 displays the interactive revenue model created by the researchers that shows the impact of data enrichment and white-labelling to the MRR of Teamleader. This chapter also highlights the different metrics crucial to a SaaS business. Chapter 5 discusses the current customer segmentation model of Teamleader and why is there a need to optimize this model. This chapter also tackles some business cases relating to the segmentation strategies of other similar companies in the SaaS industry. Furthermore, the jobs to be done framework was also discussed as this is one of the many frameworks which Teamleader is looking into for potentially segmenting its customers. Chapter 6 lists all the different methodologies which the researchers have done in pursuance of the objectives of the market research. Wiki Survey and Qualtrics were the main survey tools that were used in this study and was used accordingly to the target participants. The Wiki Survey was used during the Work Smarter event of Teamleader in Belgium to find out the different JTBDs of both the customers and non-customers of Teamleader. On the other hand, Qualtrics was used as the main survey tool that was sent internally to Teamleader customers through HubSpot. The survey duration and distribution methods were also talked about in this chapter. Chapter 7 puts a more elaborate focus on Wiki Survey and Typeform. In this chapter, the researchers discussed how the survey was designed and how the data was analyzed. From the Work Smarter event, the researchers were able to gather 159 respondents which was an optimal number, as 100 respondents is the minimum number to arrive at a good conclusion. Furthermore, the researchers were able to identify the Top JTBDs that matter to the attendees regardless if they are Teamleader's customers or not. Chapter 8 is the biggest part of this market research as this highlights the 2 main analysis which the researchers conducted towards optimizing the customer segmentation model of Teamleader: elative Preference analysis and Van Westendorp price sensitivity analysis. This chapter talked about literature reviews which indicates the importance and benefits of using such analysis towards segmentation. Moreover, the survey design was also very important as both analysis had very unique ways of asking questions in order to arrive with the desired results. Having said this, chapter 8 also scrutinizes the different variables which the researchers have used in finding the most optimal customer segmentation model. The researchers have opted in performing the customer-based analysis which takes service and service + material and number of users into account, whilst product-based analysis looked at the different modules a customer is using and adding the said variables. Through these different analysis, the researchers were able to pinpoint the unique differentiation among Teamleader users and some potential areas to improve on. The Van Westendorp analysis was also supported by a revenue-demand curve which poses a question to Teamleader's strategy in relation to choosing low price over more customers, or high revenue but low customers. Lastly, chapter 9 illustrates the proposed customer segmentation model made by the researchers. This model was purely based on the data-driven analysis which the researchers have acquired from the previously mentioned chapters. In the end, the researchers were able to merge the most preferred Teamleader features given by the respondents and associate it with their willingness to pay. From experimenting different segmentation factors, the researchers also arrived at a conclusion that a customer-based analysis which is segmented by the number of users is the way to go for Teamleader, instead of a service and service + material segmentation. To summarize, the different literature review, data gathering, statistical techniques, and analysis were all crucial factors in achieving the deliverables and giving a solution to Teamleader's burning management questions. The recommendations given were all a representation for what Teamleader can possibly do in the future.