Why Authority Is the Real Differentiator in PS Delivery

Most implementation teams hire for technical depth. They find the best configurer, the sharpest troubleshooter, the person who knows the product cold. Then that person gets on a call with a CFO and goes silent — agreeing to scope that doesn't serve the customer, deferring to requests that slow the implementation, and defaulting to execution when the moment calls for expertise.

Stacey Milgram Potzka, VP of Operations and Implementation at Actabl, and Amanda Stewart, Senior Director of Implementation at Actabl, joined Propel 26 to share the communication framework — and the AI layer built on top of it — that cut their implementation timeline from 450 days to 7.

Read on for the key takeaways from the session.

The gap between technical expertise and customer authority

Three years ago, Stacey took over the implementation team at Actabl. On paper, the team was exceptional. They could configure anything. They knew the product thoroughly. They understood exactly how to make a customer's instance work.

But on calls, they disappeared.

"They became order takers." Customers would ask for something, and the team would say yes — even when yes wasn't the right answer. 

They'd agree to a scope that didn't serve the customer, defer to requests that would extend timelines, and avoid the expert-level pushback that their knowledge would have supported. They had the skills. They didn't have the authority.

"Technical skills are the baseline. Authority is the differentiator."

The problem isn't unique to Actabl. Most implementation teams are built to configure and execute, not to consult. But as AI compresses the time required for technical work, the human layer of implementation — the guidance, the structured conversation, the relationship — becomes the primary value. 

Teams that can't operate at that level lose customers before the implementation ends. Teams that can build something more durable.

The fix Stacey reached for wasn't a new hiring profile or a new tool. It was a process.

The five-step customer excellence process — built for operators, not salespeople

Stacey adapted a communication framework originally developed for sales — from Mercury International — and rebuilt it for implementation operators. The goal: give technically strong ICs a structure that lets them lead customer conversations with the confidence of an expert, not the posture of an order taker.

The team calls it Customer Excellence. It has five steps.

1. Build rapport and set the agenda. Before covering any content, the team tells the customer what they'll cover on the call and asks if they still have the time they've set aside. It sounds minor. In practice, it resets who's leading — the implementer is running the call, not just showing up.

2. Ask questions — even when you think you already know the answer. Customer priorities shift. What mattered in the kickoff may not matter now. The team is trained to ask open-ended questions before presenting solutions, and to resist the assumption that prior context is still current. 

Rocketlane's AI fills help here: it surfaces what was said in previous interactions, so the team can build on past conversations instead of repeating them.

3. Present using the Value First Framework. Instead of feature-dumping or jumping straight to the solve, the team uses a Why → How → What structure. Why: the customer's actual business outcome. How: the process designed to get there. What: the specific deliverable, translated into the customer's own words. Stacey's example: "I've analyzed the initial discovery notes. It's clear the why for this implementation isn't just about new software — it's about reducing the 20% manual error rate at your front desk. We're here to reclaim that time." The customer hears their own problem reflected back, then the path forward. That's a different conversation than "here's what we're going to configure next."

4. Handle objections with empathy and structure. Using EARS — Empathy, Ask more questions, Restate the problem, Solution together — the team meets pushback without folding or over-agreeing. When the answer is already known, they use feel/felt/found: "I understand how you feel. Many of our customers have felt the same way. We've found that by doing X, we get this result." The framework makes objection handling repeatable instead of improvised.

5. Seal the deal — every time. Every customer interaction ends with clear ownership: who does what by when. Every call rebuilds value. Implementation spans months. Teams that stop reinforcing why the work matters mid-engagement lose the customer before the implementation closes. Partnership has to be re-earned, not assumed.

The results of teaching this at Actabl: customer satisfaction scores consistently above 85% (industry standard: 70%). Escalations that were "out of control" are now at near-zero levels. More than 30% of completed projects generate unsolicited C-suite appreciation. And implementation time dropped from 450 days to 7, with the same team, no new hires, and the addition of Rocketlane alongside this framework.

AI as detective — surfacing what customers don't say out loud

Amanda Stewart built the AI layer on top of the five-step process. The core insight: what customers say on the surface is rarely the full story. Real needs — and the signals that indicate risk or opportunity — are often buried in tone shifts, patterns across interactions, and the gap between what they mention and what they mean.

"AI doesn't replace our human intuition. It sharpens it."

The team uses a custom AI field in Rocketlane called the Customer Excellence Sentiment Summary. After every customer call, the AI performs three actions: it summarizes what was discussed, extracts the underlying need behind the customer's comments, and suggests a precise follow-up question that bridges the current situation to the customer's stated goals.

A concrete example: a customer says they're worried about their Q3 launch timeline. Their tone shifts during the conversation. The explicit need is a deadline concern. The hinted need — surfaced by AI — is bandwidth: they're worried their technical team won't be ready. The AI flags this and suggests asking in the next meeting how Actabl's team can take over the data migration to relieve that pressure. 

The customer never has to say "we're understaffed." The team already knows how to offer the solution.

Partnership language AI fills add another layer. After every interaction, the implementer opens the field in Rocketlane, clicks the Customer Excellence Partnership Language Messaging option, and gets a full call summary written in the language of partnership — "together, we're going to do X" instead of "you need to do X." The difference in customer response rate was immediate. The difference in engagement during implementation was measurable.

The full tech stack: Gong (call recording and briefs), Rocketlane (AI fills, signals, project management), Salesforce (CRM), and Churn Zero (customer health). 

Every tool talks to the others. When a director reaches out proactively mid-implementation under their Director Outreach Program, they come to that call already knowing what happened in the sales process, what the CS team has flagged, and whether there are any open support issues. No blind spots. No reactive scrambling.

4 key takeaways from Actabl's human-led, AI-enhanced delivery model

A new PM at Actabl put it directly: "When you combine a solid communication process with a platform like Rocketlane, you stop being a professional reminder sender and start being a consultant. The AI handles the heavy lifting — summarizing messy notes, updating timelines, flagging risk — so you can actually focus on the person in front of you."

Here are four lessons from how they built it:

• The framework comes before the AI. Actabl requires certification in the five-step process before any team member gets access to the AI tools. They can't lean on AI to compensate for a skill they haven't developed. Clarity first. Acceleration second.
  
  
• Partnership language is operational, not philosophical. "Together, we're going to do X" versus "You need to do X" isn't just softer phrasing — it produces different outcomes. Customers who feel like partners engage differently, complete their responsibilities faster, and generate fewer escalations.
  
  
• Use AI to detect what customers hint at, not just what they say. The teams that extract the most from AI use it to surface unspoken needs and emotional context — the patterns across interactions that a busy implementer would miss in the moment.
  
  
• Escalations are a process failure, not a relationship failure. Actabl went from out-of-control escalations to near zero by changing how every customer conversation was structured — not by managing individual difficult customers better. The structure made the escalations unnecessary.
  

Conclusion

Most PS teams are solving the wrong problem. They invest in product expertise, technical certifications, and process documentation — and then lose customers during the conversations that occur between those milestones.

Stacey and Amanda's argument is simple: the communication process is the product. The five-step framework isn't soft skills training layered on top of real work. It's the structure that makes technical expertise usable when it matters most — when a customer is uncertain, when scope is expanding, when the implementation needs someone to lead and not just execute.

AI makes the framework faster and sharper. It hears what customers hint at. It writes follow-ups in the language of partnership. It surfaces risk before it escalates.

But the human layer comes first. That's what dropped the number from 450 to 7.

Check out the rest of our Propel 26 recaps here for more insights from the industry's best.