For B2B SaaS firms, leveraging AI into day-to-day operations and embedding AI into existing products can increase market appeal, create scalable growth potential and boost valuations. At Savant Growth, most of the investment prospects we look at are not core AI platform components or AI tools, and our VC friends are largely waging those battles. The founder-led, bootstrapped businesses we fund are typically 3+ years old, created before the AI craziness kicked into full gear. No surprise, just like the not-so-distant days of big data and machine learning, every B2B SaaS pitch deck has an AI spin integrated into it. We get it.
However, what does one do if the business does not have at its center a proprietary database with great interfaces and integrations, tailor-made to pair with an LLM?
Harnessing AI for Operational Efficiency and Enhance Customer Experiences
Incorporating AI into your existing SaaS products doesn’t mean reinventing the wheel. Start by identifying parts of your platform that could benefit most from automation, personalization, and predictive capabilities. For workflow-focused products, this often means streamlining repetitive tasks, enhancing user interaction, and offering actionable insights from data. Providing a migration path or modernization solution leveraging AI might be the way to go.
While the AI landscape remains fluid, it is somewhat clear that the cost savings/efficiency ROI driver is out in front while the revenue enhancement use cases are just starting to germinate. B2B SaaS businesses with a strong cost savings ROI should be incorporating AI features into their products ASAP. In terms of applications, customer experience and support are very active. Many businesses are leveraging microservices architectures to add smart agents/co-pilots, content generators, prediction engines in short order and at very low cost. Vertical B2B SaaS businesses are in prime position to leverage their domain expertise with AI.
- Intelepeer, a communications automation platform, has landed 8-figure contracts to reduce costs in call-centers by expanding their Communications workflow with a voice AI application.
- Experience.com, a customer experience platform targeting the financial services vertical, improves agent and company search ranks with a feature that manages customer reviews with ChatGPT.
- Conversica, a sales conversational AI platform, provides a hybrid migration path that allows companies to gradually enhance their generative AI sophistication over time.
Set Realistic Expectations for Sustainable Success
It’s no surprise that bootstrapping inherently limits resources and requires execution focus to be successful. Investing in AI is most effective when done in stages, allowing your company to scale capabilities in line with customer needs and available resources. Founders need to be careful not to lose focus chasing an ambitious, half-baked AI strategy. Starting with low-complexity automations, such as smart agents or response generation can provide quick wins while giving your team time to build out more complex functionalities.
Many firms are also leveraging cost-effective nearshore and offshore resources to kickstart their AI programs, such as our DevSavant team, which provides B2B SaaS companies with skilled, affordable, and highly qualified talent across Latin America. A straightforward automation feature might only require collaboration with a skilled AI consultant, while deeper capabilities like predictive analytics or advanced personalization could require a data science team.
With the guidance of a skilled team and a phased implementation approach, even smaller B2B SaaS organizations can achieve AI-enabled success. Incorporating these advanced features can dramatically improve your product’s value proposition, increase customer loyalty, and position your company as a leading player in its market.
