Year two with Apollo: what is ready to compound.
Every conversation in this deck starts from that. Not theoretical. Measured.
Read: your team runs more automation, sends more cleanly, and shows up in Apollo more consistently than most mid-market customers. What compounds from here is a question of which layer we turn on next, not whether the foundation works.
Apr 13 this year, one person on your team activated the AI Research feature trial. That is the signal we are building on. Every AI capability inside Apollo (Research, Sequence Writing, Email Composer, Assistant, Pre-Meeting, Call Summaries, Custom Filters) reads from one shared place: the AI Context Center.
Today that center is empty. Every AI output is written in Apollo default voice, not Power Digital voice. Closing that one gap sharpens seven features at once.
Marco already turned on the Apollo dialer trial. This is the structure that turns it into a 2-week evaluation: connect rate, SFDC sync parity, and workflow trigger coverage measured side-by-side with what you run today. Zero workflow change during the trial. If the data says keep both, the data says keep both.
What's already unique on the Apollo side: every dial writes the call log, recording URL, and disposition into the SFDC Activity object on the right Contact and Opportunity with no separate sync job. That is the piece you stop managing the day you standardize.
Your inbound surface already runs Chili Piper and Clay. This adds a third signal layer: the visitor is identified at the contact level, not just the company level. That contact routes into SFDC with ownership and next-step routing already assigned. It works alongside what you have. It does not replace it.
Apr 13 your team activated AI Research inside Apollo. This is the 2-week structured rollout: which 5 reps, which 50 accounts, which persona definitions feed the Context Center, and how the scoring output shows up in the inbound + outbound routing Marco already runs.
Gong owns your forecasting and full-call intelligence. Apollo CI proposes to run on the pre-stage-2 window only, the discovery-to-demo surface, and pull repeatable objections and unanswered questions out of those calls. That output goes back into Apollo sequence variants. Two different surfaces. Two different call cohorts. No overlap.
Marco and Jessica already think in terms of automation. Apollo's workflow builder lets you turn signals (form abandon, job change detected, intent spike, website visit) into actions (enrich, sequence enroll, Slack notify, SFDC task) without engineering tickets. Three workflows. Two weeks. Measured impact on rep time-to-first-touch.
Your dialer choice does not need to change for Apollo to add value on every call. Two AI research layers plug in at the seams. Your rep keeps the tool they dial with today. Salesforce remains the single pane of truth.
Before a call connects, Apollo AI generates a 5-minute-read brief on the prospect: recent news, signals, technographic fit, persona match, last-touch history from Salesforce. Delivered in the Chrome Extension sidebar on any web-based dialer surface your rep uses.
After the call ends, the recording URL (your current dialer's output) feeds Apollo AI. Back comes a decision + action-item summary, extracted next-step signals, and auto-populated SFDC custom fields on the Opportunity. Zero manual note-taking.
Overlays any web surface your rep dials from.
Current dialer logs call, Apollo reads + enriches + writes back.
End-of-call triggers enrichment + sequence actions automatically.
Four weeks. Five reps. Two hundred contacts each. Each week adds one AI layer. Marco, Jessica, and Diego own the test design and the readout. Week 4 lands one week before renewal close. The data you present to Justin comes from your own sending, not our pitch.
Manual research, standard outreach. 1,000 contacts total. Reply rate + meeting-book + time-per-lead measured.
AI Research brief on every contact. Same reps, same volume. Same measures.
Filter to scored 70+. Measure lift against baseline.
AI Research + Lead Scoring + Personas. Compounded lift. Readout to Justin T-7.
Troubleshoot Context Center first, personas second, scoring model third. The AI is only as sharp as what it reads from. We rebuild with you mid-test.
Six plays on the table. You pick two that fit your team's bandwidth and your renewal question. We build them alongside you in the next four weeks. You present the results to yourself and decide what compounds into year three.
30 min. Marco, Jessica, Justin, Kerri Ann, Allan.
We build alongside your team. Your team owns the readout.
Data in hand. Renewal conversation becomes a working conversation.