Scaling Customer Support for International Markets in a B2B SaaS Company
Ilvonen, Tommi (2026)
2026
All rights reserved. This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-202604136283
https://urn.fi/URN:NBN:fi:amk-202604136283
Tiivistelmä
This thesis examines the scaling of customer support for international markets in a B2B SaaS company. The commissioning organization is Linear Oy, a Finnish software company serving the real estate industry, which is currently expanding its operations to European markets. The objective of the thesis is to formulate concrete development recommendations for scaling customer support internationally.
The study was conducted as a development research project during autumn 2025 and spring 2026, combining a theoretical literature review with an empirical survey. The survey was targeted at professionals in customer support leadership roles in international B2B SaaS companies and received 14 responses, which is a significant number given the seniority of the target group. The data were analyzed by thematically coding the open-ended responses and calculating distributions for the structured questions.
The central finding is that customer support scaling challenges are primarily qualitative rather than quantitative: increasing ticket complexity emerged as the dominant challenge (79 % of respondents), while volume growth alone was cited by only 21 %. Artificial intelligence was identified as by far the most important scaling enabler, and its adoption is well-established: 93 % of respondents reported using AI in customer support and 79 % reported it as widely used in their organizations. A high-quality knowledge base emerged as an essential foundation for AI solutions, while insufficient documentation directly undermines the reliability of AI-generated responses.
The development recommendations for the commissioning company are structured around five areas: (1) a phased AI and automation strategy in which knowledge base development precedes AI deployment, (2) systematic knowledge base development using a docs as code approach, (3) an international operating model combining a standardized global framework with market-specific adaptations, (4) a structured collaboration model with product development for systematic root cause identification and resolution, and (5) a KPI framework to support scalability monitoring. The recommendations are applicable beyond the commissioning company to other B2B SaaS companies at a similar stage of growth.
The study was conducted as a development research project during autumn 2025 and spring 2026, combining a theoretical literature review with an empirical survey. The survey was targeted at professionals in customer support leadership roles in international B2B SaaS companies and received 14 responses, which is a significant number given the seniority of the target group. The data were analyzed by thematically coding the open-ended responses and calculating distributions for the structured questions.
The central finding is that customer support scaling challenges are primarily qualitative rather than quantitative: increasing ticket complexity emerged as the dominant challenge (79 % of respondents), while volume growth alone was cited by only 21 %. Artificial intelligence was identified as by far the most important scaling enabler, and its adoption is well-established: 93 % of respondents reported using AI in customer support and 79 % reported it as widely used in their organizations. A high-quality knowledge base emerged as an essential foundation for AI solutions, while insufficient documentation directly undermines the reliability of AI-generated responses.
The development recommendations for the commissioning company are structured around five areas: (1) a phased AI and automation strategy in which knowledge base development precedes AI deployment, (2) systematic knowledge base development using a docs as code approach, (3) an international operating model combining a standardized global framework with market-specific adaptations, (4) a structured collaboration model with product development for systematic root cause identification and resolution, and (5) a KPI framework to support scalability monitoring. The recommendations are applicable beyond the commissioning company to other B2B SaaS companies at a similar stage of growth.