Nina Wilkinson

AI has helped us identify weak spots within our overall post-sales program. Despite our already strong 97% CSAT scores, AI helped us identify specific areas within that program that could use improvement.  For example, by analyzing our customer feedback and usage data, we discovered our integration training needed a major overhaul. We've since restructured our approach, leveraging our Apollo Academy content to create standalone and live webinars for users onboarding and separating admin training ...Read More

AI is incredibly powerful and changing the way we interact with customers but we must thoughtfully balance its potential with its environmental impact (I live in California, after all). When looking at which tools to select and how to integrate AI into our workflows, I balance usefulness against those considerations. I'm adamant that our team must continue thinking independently and not become overly reliant on AI for decision-making. We use AI to help us craft better outreach strategies, rapidl ...Read More

We've all experienced frustrating support interactions where automated systems fail to provide the human connection we need. Think about those moments when you're repeatedly pressing "0" or saying "AGENT!" to bypass automated menus, even when the system seems to know your entire purchase history. This illustrates a critical point: personalized AI cannot replace genuine human empathy and understanding. Instead, AI should be a powerful tool that empowers CSMs to be more effective. By quickly synth ...Read More

For me, without a doubt, it's Logo Retention (LRR), especially in the SMB/MM space. While everyone's chasing that shiny Net Revenue Retention number, many leaders are using expansion revenue to paper over cracks in their core retention. LRR is the ultimate truth teller: it tells you if customers are sticking with your product purely because of the value it delivers. In the current market where teams are having to reduce headcount, LRR will tell you whether they value your product and your team's ...Read More

Vitally's AI capabilities offer us powerful integrations across our customer success tech stack (highly recommended). It summarizes all call transcripts via its native integration with Gong and creates tasks and action items based on calls. It also incorporates all of our support tickets from Intercom, our emails, product adoption, and CSM notes into one account summary that provides: Detailed account health assessments Risk identification Potential expansion opportunities It’s been immensely he ...Read More

While it’s still a bit early for us to fully measure the multi-year impact of AI on our CS processes, we have seen significant improvements in our overall understanding of our customers, their needs, and the stakeholder hierarchy within our accounts.  Specifically, as we expand upmarket and seek to engage cross-functionally, AI has become crucial in helping us map complex organizational landscapes. Previously, we struggled to identify key decision-makers: the executives with budget authority and ...Read More

With our expansive customer base of millions of users, traditional monitoring methods often miss critical sentiment signals. AI has empowered the CS team in our ability to detect subtle indicators of customer satisfaction and potential churn risk. By comprehensively analyzing our entire customer feedback ecosystem—including NPS scores, CSAT data, support tickets, and email communications—we've developed a 360-degree view of customer sentiment that goes beyond surface-level interactions. Traditio ...Read More

Admin time previously consumed a large portion of our CS team’s overall bandwidth. A year ago, our team would have to do extensive handoff/transition notes from Onboarding Managers to the CSM, and between CSMs when we did book cuts. Those notes took extensive time to create to ensure a smooth transition between ICs that captured all sentiment and minutiae about the account, champions, main POCs, et al.  Including Vitally’s new AI summary function into our set up has enabled us to reduce our over ...Read More

I've actually seen founders make two costly mistakes when building their CS team. Hiring: Too early (burning cash on overhead you don't need) Too late (watching churn rates climb while you're heads-down on product development) Building your CS team is a balancing act between those two. And no, there isn't a magic number on when you should hire. The answer isn't "at 50 customers" or "at $1M ARR." The real trigger is founder pain and business complexity. I recommend starting the hiring process whe ...Read More

It depends on stage. The KPIs change as the team matures. Early stage teams (under ~$10M ARR): anchor on GRR and LRR. You’re proving the product is sticky and that customers want to stay with you even when their headcount or budget changes. Later stage teams: shift to NRR and LRR plus expansion opportunities created or Closed Won. You’re proving CS contributes to growth, not just retention. For tooling, here’s what I’d actually recommend: Vitally: my go to. Easy to implement, strong dashboards, ...Read More