Creating a playbook for GenAI success in IT SaaS

July 2023 – Oct 2023

🔍 Background

GenAI was no doubt a hot topic in 2023, especially for ServiceNow’s customers since ServiceNow announced its strategic partnership with Nvidia. We had a dedicated AI research team investigating the area. As part of the IT product suite, I and another researcher identified a knowledge gap in buyers’ understanding. We partnered together to investigate how the key decision-makers of ServiceNow customers think about GenAI.

We worked with a vendor to conduct a total of 23 interviews. We summarized our findings as product strategies as well as communication and engagement recommendations to help our IT products build trust and drive adoption.

We presented our findings in front of a room of SVPs, and product area VPs. We then got on a “roadshow” to present our findings to our AI team, UX org, and the broader product org.

🗻 Process

Following the launch of Chat GPT, we had a dedicated AI research team conducting various research on the topic. As part of the IT product suite, we didn’t have too many IT product-specific insights around GenAI. The team realized the gap and I volunteered to partner with another researcher. We tried to figure out our focus centering around the question “What are the key questions needed to get answered to help support the IT product team’s near-term GenAI decisions”.

To piggyback on what has been done, we conducted a mini-meta-analysis of what has been investigated. In parallel, we conducted several internal stakeholder interviews with SVPs in the IT product suite to understand the decisions they would need to make and the bottlenecks they were facing. These prep efforts helped us to find our focus on understanding buyers’ expectations and customers’ readiness for GenAI solutions.

We conducted 23 interviews with key purchase decision-makers from a list of our top 500 customers. We summarized our findings into product strategies and communication and engagement recommendations for our product team. We also called out specific use cases and opportunities to apply GenAI to help individual product teams strategize their offerings.

🔭 Impact

  • Presented in front of our SVP and lead for the IT product suite, his direct reports, and our chief innovation officer. Our learnings immediately got referred to after the presentation in discussions in different individual BUs.
  • Got invited to present in front of our internal AI team.
  • Presented the findings in front of the wider org with over 100 attendees from sales, marketing, design, engineering, and other cross-functional teams. The recording was featured in the internal Workspace.

✍️ Lessons Learned

  • Manage up when facing changing directions. We got a lot of traction from various stakeholders as we were preparing and running this research and we were also running against a tight timeline. We learned how to stay calm when facing the storms and proactively communicate with our stakeholders to manage their expectations and figure out the priorities for our work.
  • Framework sticks! We tried several ways to summarize our findings, and eventually, we went with frameworks, which got our stakeholders excited. The framework also got referred to frequently.
  • Scale up research impact through multiple communication channels. I and the other researcher came up with a roadshow strategy – we identified different possible channels to help us get our research insights to different types of decision-makers in our company. We eventually not only got fans from the IT product suite but a lot more functions and product areas outside IT.