Event Intelligence
Orchestrate At Scale: Turning Signals Into Systems
By Peter Micciche, CEO of Certain
May 28, 2026
For companies today, events represent the highest-fidelity source of buyer intent available. They are the moments where prospects engage, share their pain points, seek understanding, and volunteer their most precious resource: time.
Yet for most organizations, these moments are fleeting and underutilized.
A prospect shares their biggest headache in a breakout session. A late-stage lead attends a small executive dinner and shares their biggest priority for the year. A user provides glowing feedback in a product workshop. These interactions happen, and then they vanish.
What price do you pay for missed opportunities?
Why does this happen?
While most event programs excel in the planning stage and in execution of the event experience, they fall terribly short in what happens with data as attendees engage.
The problem that events surface for teams is not that prospects and customers aren't sharing buying signals at events. Your buyers are actually sending more signals than ever. The problem is what happens between the time a signal appears and a human takes a meaningful action.
Large enterprises run hundreds, sometimes thousands, of events per year across multiple regions, formats, and audiences. In a digital universe, is there a better human to human opportunity to optimize for great business results? Could a CMO change the company's trajectory if those interactions were properly harnessed and transformed?
Without a unified system of orchestration, those signals are lost in the noise of disparate platforms, broken handoffs, and manual processes that can't keep pace with volume. To win in a signal-based go-to-market environment, enterprises must move beyond traditional "event planning" and toward true signal orchestration.
The Three-Pillar Framework In Practice
In earlier editions of The Signal, I laid out a simple structure for event intelligence:
- Capture buying signals
- Deliver those signals in real time
- Orchestrate action at scale across revenue teams
Most teams stop at step two. They capture rich engagement and push it into systems faster than before, although rarely in real-time. But revenue results still lag, and it's clear that context is missing between what happened at the event and all other interactions that are being tracked.
As a business looking to optimize your event channel, you'll only feel the impact of this framework when all three pillars work together. Signal capture, real-time delivery, and orchestration have to operate as one system, not three siloed projects.
Pillar 1: Capture Signals That Actually Matter
You don't need to capture every single action that happens at an event. You do need to capture the signals that reveal patterns of intent, readiness, and risk.
When I review event data with CMOs, I ask questions such as:
- Which behaviors clearly correlate with opportunities created or accelerated?
- What do you need to know at an account or at a buying group level to build confidence in buying readiness, including upsell and expansion opportunities?
- Which signals would your sales or CS leaders drop everything to act on?
It's worthwhile to consider the distinction between "data points" and "signals." Attendance at a session is a data point in isolation. That attendance, paired with sharing pain points in a poll, is a clear buying signal. A pattern of pain points across three stakeholders in a buying group from the same account is a signal.
A useful capture strategy groups event behaviors into four buckets:
- Interest: topic-level curiosity that feeds nurture
- Pipeline: behaviors consistent with an active evaluation
- Readiness: clear signs someone is close to a decision
- Barriers: concerns, objections, and risk indicators
If your event platform and data model do not reflect those categories, orchestration will feel random. Your teams will not trust the alerts they receive. Your teams will treat everyone like the same kind of new lead.
Pillar 2: Deliver Signals While They Still Matter
Speed without context is noise. Speed with context is a competitive edge.
In many organizations, "fast" still means a next-day export. In some, it means an hourly sync. That's before someone takes action, which is often days from then.
McKinsey's work on AI in growth and marketing shows that organizations that implement AI across sales and marketing functions see 10-20 percent improvements in sales ROI within about 18 months. That same research found companies that excel in personalization generate up to 40 percent more revenue from those activities, with 5-8 percent overall revenue lift and 15-20 percent higher customer satisfaction.
The standard I encourage leadership teams to adopt:
- Signals move from event environment to systems of record within seconds
- Signals arrive with context and a short explanation of why they matter now
- Signals land where people already work, not in a dashboard they rarely open
Real-time delivery is no longer optional. It is the baseline that makes effective orchestration possible.
Pillar 3: Orchestrate at Scale, Not by Heroics
In theory, everyone agrees signals should drive fast, consistent actions. In practice, follow-up still lags and relies on individual heroics. An ops leader builds a custom workflow for the flagship conference. A regional marketer keeps a personal spreadsheet for their roadshow series. A sales manager sets up their own "hot lead" Slack channel.
Those one-off solutions do not scale when you run hundreds or thousands of events a year across regions, products, and segments. There's a phrase I think of for this situation: "signals need shared systems."
A scalable orchestration model shares these characteristics:
- Standard plays, regardless of event -- If five late-stage accounts show up to a mid-week webinar, the system already knows the play. Tasks, outreach, and content adjust automatically based on segment, role, and behavior. Nobody is reinventing the process every time.
- Scale-agnostic execution -- A six-person executive dinner and a six-thousand-person user conference both produce high-value intelligence. The orchestration layer should treat both with the same discipline.
- Consistent handoffs -- Marketing, sales, and customer success see the same story. They might act on different parts of it, but the source of truth is shared. No one is trying to reconcile three versions of what happened at the event.
What Orchestration At Scale Looks Like
Let's make this concrete. There are several dimensions of scale that matter for orchestration:
- Format: conferences, dinners, webinars, trade shows, partner events
- Volume: dozens or hundreds of events per year, across business units
- Routing: who receives which signal, in which channel, with which context
- Compliance: regional privacy and data rules that must be honored automatically
- AI: pattern detection across the full portfolio, not only event by event
When those dimensions work together:
- A field event in Germany produces signals that feed the same models as a virtual summit in North America
- Sales leaders see consistent readiness definitions across regions
- Marketing leaders see which formats, products, and topics drive real pipeline, not just registrations
- Customer Success leaders see early warnings and expansion signals for their accounts
- Product Managers gain feedback on solutions and adjust accordingly
This kind of scale enables teams to move from "did this event work?" to definitive direction on the mix of events and content that actually moves business forward. This becomes an entirely different and welcomed conversation in the C-suite.
The Role of AI, Without the Hype
AI's role in orchestration is straightforward. It turns messy engagement streams into consistent, actionable categories.
Applying AI to events is a low-hanging fruit opportunity for AI transformation mandated for every team.
AI easily enables your teams to recognize signals by buying stage such as interest, pipeline, readiness. AI also classifies barrier signals which might indicate that a deal is at risk or a renewal may stall.
AI is fast and effective at analyzing signal sequences instead of just counting isolated moments. Three technical sessions plus a pricing conversation tells a different story than one booth scan.
Forrester's research on insights-driven businesses found that companies that operationalize data and insights into their processes are 8.5 times more likely to report 20 percent or greater annual revenue growth than their peers. That is not because they bought one more AI tool. It is because they wired insights into how teams work every day.
IDC's work on sales management and AI makes a related point. AI and automation reduce the time sales managers and reps spend on administrative work. This frees them to coach, strategize, and engage customers more effectively.
Portfolio Intelligence Instead of Event Autopsies
One of the least productive rituals in marketing is the event autopsy that follows a few days after each event has ended. Teams spend hours debriefing and debating whether a single event "worked," usually based on an inconsistent mix of reports and anecdotal feedback.
Orchestration at scale replaces those debates with portfolio-level questions that can actually be answered such as:
- Across the last quarter, which event formats generated the highest-quality pipeline for enterprise deals?
- Which themes, features, or use cases consistently show up in deals that close faster or at higher value?
- How does time-to-opportunity differ between people sourced from executive programs versus broad awareness conferences?
- Which markets or segments have the highest pipeline creation from events versus digital channels?
When you aggregate signals across the full portfolio, you start seeing patterns no single event can reveal. This fully enables you to make the hard decisions about budget, format mix, and regional focus. It is also how you defend those decisions with evidence when faced with budgetary pressure.
A Simple Next Step
Within the next week, start a dialogue with the leaders from marketing, sales, CS, and operations to answer the following questions:
- Which three event behaviors most reliably predict revenue outcomes for us?
- How quickly do those behaviors reach the person who should take action?
- How does data travel, step by step, and where are the delays, duplicates, or gaps?
You do not need a full redesign in that meeting. You just need a shared view of the current state, the signals that are priorities, and one or two orchestration problems that you commit to fix first.
Events already produce the richest buyer signals you have. The question is whether your systems and teams are ready to respond at the speed and scale your market now expects.
Peter Micciche is CEO of Certain, the leading AI-powered Event Intelligence platform for enterprise B2B companies. Connect with Peter on LinkedIn or visit certain.com to about transforming events into revenue engines.
Sources: Forrester Research, "Use Insights To Unlock New Levels Of Sales Productivity," 2022. McKinsey & Company, "AI-powered marketing and sales reach new heights with generative AI," 2023. IDC, "Empowering Sales Management with AI," 2025.