My Plays

Finding the account (the churned-account report and hiring signals). Mapping the offices (location and hierarchy data). Reaching people (mobile numbers). The trial (the data itself). Proving value during the deal (G2 integration and website visit alerts). Fitting into their world (native CRM integration and CRM enrichment).

This is a companion piece to the Always-On Outbound Engine.

The system that scores and ranks every account and every contact in our ICP into one list for our SDRs, rebuilt daily.

This playbook is what happens at the top of that list. The warmest of the warm: the contacts we want SDRs hitting first, what a seller actually receives when one lands, and what they do with it.

Last year that team averaged a 2.5% demo booked rate. Since we started sending a full context package with every warm contact, it's 7%.

This playbook walks through the full warm routing path and gives away the context package we deliver.

Scoring runs continuously at both account and contact level. Above the threshold routes to warm - direct to an SDR. Every contact carries a score between 0 and 1, made up of:

• Each recorded signal, individually weighted. Company growth, person and account web visits, person-level intent, social media engagement, marketing activities they have taken part in, past sales engagements and champion moves all feed the same number.

• An initial score, before any behavior is recorded.

• Half-life and decay, applied on top.

• A likely-to-engage modifier, which boosts the total.

Decay is the mechanic worth spending a paragraph on, because it's what makes warm a state rather than a fixed status. A content syndication download from four months ago scores zero. Nobody should be picking up the phone today on the strength of a blog somebody downloaded a third of a year ago, and the score reflects that. 

Warm has to be earned recently, and it has to be re-earned; the list rebuilds every day, and a contact who sat at the top of it last week can be back below the threshold very quickly if the signal/signals reach a point of decay.

Every morning, each segment gets the top 150 to 400 contacts.

We throw the traditional signal based play out the window. A signal-based play works one way: a contact does one thing, that one thing puts them in a sequence. This doesn't do that. We capture everything we know across a contact and use all of it to trigger the outreach, not the single signal that happened to fire last.

So the outreach is customized for the context: the signals hit, who the person is, the company details. And the SDR is given the context too, why this contact ended up in their book of business in the first place.

The ranking decides the order. Rep capacity decides how many names come off the top. Some mornings that's 150, some mornings it's 400, however many the team can actually work that day.

Preparing for a single call used to mean LinkedIn, the CRM, the ZoomInfo record, a web search, then pasting all of it into an LLM to get a talk track. Multiply that by every rep and every call and it becomes the biggest cost in the day.

That’s why it now arrives in one view, built once, automatically, for every contact routed that morning

Why this matters. No tab-hopping, and no rebuilding the account story before every dial. But the prep time is the smaller half of it.

Most reps open a call with a name, a title, and a reason to ring. Ours open with a play the data picked, a competitor the prospect knows who's already a customer, a peer in their segment, and the signal that says this person is in-market right now.

This is what moves you into a commercial conversation, instead of trying to find out if there's a fit.

The play, the opener, the voicemail, the questions and the value prop are all automatically generated FROM the context package. Our reps never start from zero.

• One suggested play, built from contact and account history and context

• Two scripts, one for a pickup and one for no answer.

• Three discovery questions for the call itself, pulled from the context package

• And the value prop framed three ways: tied to the suggested play, tied to the role they're in, tied to the outcome the buyers own

This means reps are never starting from zero, and can move faster to work the warmest leads in our ICP.

The rep works the list. Read the opener, or the voicemail. Run discovery, pitch and book.

The same pack is often used differently across segments. Mid-market often runs closer to point and shoot, higher volume, work down the list, read the opener, leave the scripted voicemail if there's no answer, ask the discovery questions if they stay on the line, pitch and book the meeting. Enterprise treats it as the starting layer: prep time collapses, and the rep spends what's left on tailoring rather than assembling. Neither is the wrong use of it.

What changes is how repeatable the calls are. Before, a good conversation depended on whether that particular rep went and found the right information that morning. Now the base layer is there every time, for every contact, whether or not anyone goes looking. The floor comes up. That's where the productivity and the demo rate come from, not from any single script being read word for word.

Watch Florin utilize this play on GTM Studio

FAQs for the warm path

How is this different from a signal-triggered play?

Most teams build plays as triggers, where one signal fires and one sequence runs. This ranks the entire universe daily and takes the top slice. Everything known about a contact feeds one score, and the outreach is built from that whole picture rather than from the single signal that happened to fire.

How does a contact get onto the daily list?

By scoring above the threshold. The score runs from 0 to 1 and is built from weighted signals, an initial score, half-life and decay, plus a likely-to-engage boost. Out of everything trackable that morning, the top 150 to 400 per segment go to sellers.

What’s actually in the context package?

Everything we want the rep to know in one view: the contact, the account, why them and why today, why they should care, the fit, peers and competitors, and the signal history. The AI then builds on top of it, a suggested play, the opener and voicemail, and the discovery questions and value prop.

Do reps follow the scripts word for word?

We don't enforce that reps follow the scripts verbatim or the exact recommendations. Mid-market is closest to working straight down the list, while enterprise reps self-direct considerably more. What's driven the results is that the base layer is there every time, for every contact, whether or not anyone goes looking. The floor comes up. That's where the productivity and the demo rate increase comes from.

Why 150 to 400 rather than a fixed number?

The list is per segment, and the number moves with what’s genuinely warm that morning. Ranking decides the order, and rep capacity decides how far down the list the day reaches.

This is a companion to the published Always-On Outbound Engine.

The system that scores and ranks every account and every contact in our ICP into one list for our SDRs, rebuilt daily. This playbook covers those who don't meet the threshold for a 'warm' contact: roughly 90% of the universe, who never clear the bar.

Cold here is a state rather than a list. Contacts fall into it when their signals age out, and they arrive in it having never engaged at all. What follows is what the system does with them, and how around 5,000 buyers have crossed back the other way.

The full addressable universe. Every contact a seller would plausibly want to speak to, which comes to roughly 100,000 people.

This isn’t a target list. It’s the population the engine works across continuously, and the problem it creates is the reason the whole system exists: 100,000 contacts, and no way for a rep to know which ones matter this morning.

It’s built from ZoomInfo data and filtered against Salesforce, which strips out existing customers, legal blocks, and any status flagged do-not-contact.

Scoring runs continuously at both account and contact level. Below the threshold routes to cold. Every contact carries a score between 0 and 1, made up of:

• Each recorded signal, individually weighted. Company growth, person and account web visits, person-level intent, social media engagement, marketing activities they have taken part in, past sales engagements and champion moves all feed the same number.

• An initial score, before any behavior is recorded.

• Half-life and decay, applied on top.

• A likely-to-engage modifier, which boosts the total.

Decay is the mechanic worth spending a paragraph on, because it’s what makes cold a state rather than a list. A content syndication download from four months ago scores zero. Nobody should be picking up the phone today on the strength of a blog somebody downloaded a third of a year ago, and the score reflects that.

Two populations end up in cold:

• Decayed. They engaged once, and it aged out.

• Genuinely unknown. Zero contact signals, zero account signals, and they may never have heard of ZoomInfo.

Every cold contact gets copy built specifically for them before anything sends. This is the step teams would often skip on cold, and it’s the one that makes the play interesting. It’s per-contact generation rather than segment-level templating.

The inputs:

• Persona and function

• Account summary, pulled from ZoomInfo

• Contact brief

• Company scoops

• Any prior company-level engagement

A Head of Brand Marketing receives copy about marketing use cases and content. A sales director at the same company receives sales specific content. Company-level context is fed into the copy, or relevant historical information from the contact brief, to build relevance into the messaging.

What’s deliberately not used: Contact-level signals, because there are none, and that’s the definition of cold. Account-level signals can be fed in, so a relevant company scoop could inform the copy.

Five emails, sent on behalf of sales VPs. No SDR involvement at any point.

Sending from a VP alias rather than an SDR does two things. It keeps rep capacity entirely on warm contacts, and it sets up the later handoff. When somebody does convert, the SDR can open on or leverage "I work on his team," which is a warmer entry than a cold dial.

Every CTA points at content, never at a meeting. Nobody sends five emails to a zero-signal contact and asks for nothing, which is exactly what makes it work.

The destinations used are blogs, case studies, e-books and GTM.AI. The reasoning behind that:

• A demo ask against zero signal converts close to nothing, and burns the contact.

• A content click is a signal, and the engine only needs a signal.

• Familiarity is the secondary objective. For many of these contacts, the goal is simply that the name ZoomInfo registers at all.

The sequence isn’t trying to book a meeting. It’s trying to manufacture a data point.

Any signal, from any source, not just this campaign. Contacts don’t have to engage with the sequence to progress, and that detail changes how the whole play should be understood.

There are multiple routes to then evaluate and re-score the contact:

• Campaign-driven. They click, engage or they visit GTM.AI within the hour, and it registers.

• Independent. They start a new job. They visit a competitor's G2 page, which registers as category intent.

Somebody who never opens a single email but shows an unrelated signal still feeds into the system. The sequence runs underneath as support, and the scoring engine is what’s actually doing the work.

Read it accordingly. The cold sequence is there to support the overarching scoring and prioritization of the full ICP, not a conversion mechanism.

The new signal enters the same scoring model described in step 2. Weighted, decayed, added to the total.

There’s no separate cold graduation logic. One scoring model, one threshold, and contacts moving across it in both directions continuously.

The contact crosses the threshold, joins the daily prioritized list, and goes to an SDR. They land in the top 150 to 400 sent to sellers each morning, alongside contacts who were never cold. From this point the Always-On Outbound Engine takes over.

Two details worth keeping in mind:

• A cool-down period runs before an SDR calls. Deliberate, not incidental.

• The talk track references the VP's emails, not the click. "I work on his team, wanted to see if you had any questions" rather than "we saw you visited our site."

Watch Florin utilize this play on GTM Studio

FAQs for the cold path

What makes a contact cold in this system?

A score, not a label. Every contact carries a score between 0 and 1 built from weighted signals, and decay pulls that score down as signals age. Two populations end up below the threshold: contacts who engaged once and aged out, and contacts with zero signals who may never have heard of ZoomInfo.

Why send five emails to someone who has never engaged?

The sequence isn’t trying to convert. It’s trying to produce a data point the scoring engine can act on. A content click is a signal it can use to factor into re-scoring. Familiarity is the secondary objective, since for many of these contacts the goal is simply that the name registers at all.

Why does the sequence never ask for a meeting?

A demo ask against a zero-signal contact converts close to nothing and burns the contact for later. Every CTA points at content instead: blogs, case studies, e-books and GTM.AI. The click is what the system is actually after.

Do contacts have to engage with the emails to move to warm?

No. The engine tracks any signal from any source. A contact who never opens a single email but starts a new job, or visits a competitor's G2 page, still crosses the threshold. The sequence runs underneath as support rather than as the conversion mechanism.

Why send from a sales VP rather than an SDR?

It keeps rep capacity entirely on warm contacts, and it sets up the later handoff. When a contact does convert, the SDR opens with a reference to the VP's emails, which is a warmer entry than a cold dial.