Navigating the AI Frontier: How Data Can Drive Customer Success and Product Innovation
By Omid Razavi, CSLN Board Member
AI has the immense potential to revolutionize customer success and product management. With the help of AI-driven insights, organizations can boost collaboration, enhance customer experiences, and propel business growth. From optimizing software development lifecycles to creating unified data intelligence layers, AI enables organizations to make data-driven decisions and tap into new opportunities. As AI evolves, businesses must embrace and leverage its capabilities to remain competitive in today's fast-paced, data-driven world.
The Customer Success Leadership Network, Immersa, and Mayfield, recently convened several leading experts to shed light on how Artificial Intelligence (AI) and data can be harnessed by product and revenue teams to create a competitive edge. Sherrod Patching, VP of Customer Success at GitLab, Steve Wilson, Chief Product Officer at Contrast Security, and Aseem Chandra, Co-founder, and CEO at Immersa.ai. and Gamiel Gran, Chief Commercial Officer at Mayfield, had an insightful discussion. This article identifies some of the key learnings, and you can watch the webinar here.
Utilizing AI in the Development Cycle:
Sherrod Patching shared how GitLab uses AI to enrich the customer lifecycle. They focus on enhancing developer productivity and efficiency through AI-powered code completion, vulnerability detection, and testing procedures. By employing AI throughout the software development cycle, GitLab aims to assist customers in achieving superior results, mitigating security risks, and accelerating product development.
The Power of Data-Driven Decisions:
Steve Wilson underscored the critical role of data in driving decision-making. He advocated the need to go beyond mere data collection and focus on translating it into actionable insights. Analyzing customer data allows businesses to identify risks, prioritize feature requests, and adapt their offerings to meet customer needs effectively. He also pointed out the importance of accuracy when ingesting internal documentation into AI Systems for customer usage, make sure you have validated your content! AI can play a pivotal role in mining valuable insights from complex data, thus empowering organizations to make more informed decisions.
Breaking Down Data Silos:
Aseem Chandra highlighted companies' struggles with fragmented data across different applications and departments. The lack of interconnectedness and context often obstructs organizations' capacity to extract meaningful insights. Immersa addresses this problem by offering a data intelligence layer that amalgamates data from multiple sources, enabling customer-facing teams, such as customer success and product management, to access actionable insights that drive business outcomes.
Enhancing Customer Conversations with AI:
Patching touched on how AI can uplevel customer conversations. AI-enabled language models can help customer success teams conduct more strategic discussions and offer high-level guidance. AI can assist in understanding customer needs, monitoring progress against key metrics, and effectively influencing outcomes. By leveraging AI, customer success teams can augment their capacity to deliver value and foster customer success.
Unlocking New Horizons with AI:
The panelists discussed how AI creates new opportunities and markets for organizations. When asked, “What can you improve by using AI and being more data driven?”, Wilson described four levels of usage that add value:
Acquire more customers using AI tools such as chatbots to become more efficient and develop content more quickly. You can leverage AI tools to understand customer background and context and engage in intelligent conversations with customers helping to build and grow relationships by collecting valuable insights.
Make your customers more successful by organizing and leveraging your own information such as documentation and use cases and making it more readily available to your customers through AI natural language models. Natural language models allow customers to ask complex questions through AI Tools and find the information they want in a self service manner.
Improve your product through instrumentation using AI tools and better understanding of what customers need and what they are doing within your product. Building co-pilots adds value by guiding customers while providing critical usage data back to the product team.
Help to identify new market segments and use cases by adopting AI technologies like large language models. The ability to glean insights from massive amounts of data allows companies to discover new use cases and invent groundbreaking products that expand business and add value.
Make Sure You Consider Security, Privacy and Intellectual Property
A key part of the discussion that followed the webinar centered around how to properly manage the use of emerging technology. As was true in the early days of the internet, social media platforms and other technology advancements, defining policy is critical. Source code and information placed into public AI systems becomes public under many click through user agreements. This has the potential to create many problems for many companies without proper governance.
The group agreed that it is important to protect IP, content and customer data. Developing an internal AI Usage policy that identifies key parameters such as:
What AI products and systems are allowed or not allowed
What is the criteria for proper AI usage for employees and to build into products
What are the proper approval policies
Which information and materials are “off limits” to share in any AI platform (PI, Intellectual Property, etc)
These considerations are simply good hygiene and need to be developed as AI tools become more widely used.
AI is here to stay - we know it will impact us in both positive and negative ways. Let us know your experiences and thoughts about using AI in the intersection of Customer Success and Product Development.
