AVA
AI Sales Agent
Turn IRL event investment into activated PLG adoption—by removing onboarding friction and measuring real usage.
Events are our most controlled GTM environment—ideal for clean early-product signals.
Events are our largest discretionary GTM investment—and the one place where we control the environment. Instead of asking "How do we get more leads?", this play asks a better question: How do we turn event spend into activated product usage and high-quality PLG insight?
Identified companies and attendees give clear context.
Task timing is controlled and measurable.
Intrinsic intent reduces signal noise.
Lower noise equals higher quality signals.
Compared to paid/web and sales-led motions, events give us the highest control and cleanest learning quality. Paid/web is noisy and hard to control. Sales-led is biased by human process. Events are where we can measure adoption with less noise.
Establish clean, early-stage PLG signals by isolating onboarding friction from product value.
Once Ava is trained and contextualized, how quickly and how often do users adopt Ava for real sales work?
Users who experience a trained, ready-to-use Ava instance at first interaction will show stronger engagement than users who encounter an untrained, self-serve onboarding experience.
Pre-configured Ava instance activated at an IRL event.
Standard untrained, self-serve onboarding (future baseline).
Hold these constant to keep results clean:
Seller or vendor representative
Post-event lead follow-up activity
0–72 hours post-event
Consistent Ava release across groups
Minutes to active setup
Minutes to initial result
Spontaneous user return rate
Key tasks completed in week one
These metrics tell us whether pre-configured Ava drives faster adoption and sustained engagement versus self-serve onboarding.
Vendor reps responsible for pipeline. Early- to mid-career sellers. High urgency and low tolerance for friction.
0–72 hours post-event. Leads are assigned quickly. Attention is high and follow-up is expected immediately.
Follow up on event leads. High volume, low context. Personalization required—and historically delayed or skipped.
By controlling first-use conditions, we can observe true adoption behavior without onboarding friction distorting results.
Instrument early-cycle usage distinctly from core deal usage. Track time-to-first-output and follow-on usage into post-call moments.
Provide vendor lists and timing for event follow-ups. Coordinate in-person handoff to direct users into the early-cycle entry point.
Endorse this as a deliberate, time-boxed extension of Ava's entry point. Align that early-cycle assistance is a credibility bridge—not a repositioning.
This play does not redefine Ava's long-term value.
AI Sales Agent