Push and Pull: The Intelligence Model Sales Teams Actually Need

There are two ways information can reach a sales rep: it's pushed to them, or they pull it themselves. Every sales tool you've ever used falls into one of these camps. And every one of them is incomplete because of it.

Let's break this down.

Push: intelligence that finds you

Push means the system is watching — constantly monitoring CRM data, email threads, call transcripts, calendar changes, stakeholder movements, competitive mentions, deal velocity — and delivering the things that matter directly to the rep. In Slack. In Teams. Via SMS. Wherever they already are.

The rep doesn't go looking for insights. The insights come to them.

Here's what push looks like in practice:

• Monday morning, 7:45 AM. Before the rep opens their laptop, they get a Slack message: "3 deals need attention this week. Your champion at DataFlow just accepted a new role at a different company. The procurement team at Meridian hasn't responded in 11 days. And the competitive deal at Vertex has a Gong call scheduled with your competitor tomorrow."

• Wednesday, 2:15 PM. Between meetings: "The CIO at NovaTech just published a LinkedIn post about modernizing their data infrastructure. This aligns with your open opportunity. Here's a suggested angle for your next touchpoint."

• Friday, 4:00 PM. End of week: "Your pipeline moved $340K forward this week. Two deals progressed to technical evaluation. One deal is trending negative — engagement from the economic buyer dropped 40% over the past two weeks. Recommended action: schedule an executive alignment call."

None of this required the rep to open a dashboard, run a report, or check a tool. The AI did the watching. The AI did the analysis. The rep got the outcome.

This is fundamentally different from how most "intelligent" sales tools work. Clari can tell you a deal is at risk — if you log in and look at the deal. Gong can show you that a competitor was mentioned — if you review the transcript. The data is there. The delivery mechanism is broken.

Push fixes the delivery mechanism. The AI monitors 24/7 and only surfaces what's worth the rep's attention. No noise. No alert fatigue. Just the signals that change what the rep should do today.

Pull: intelligence on demand

Pull is the other half. It's what happens when a rep has a specific need and wants help right now.

Pull means the rep can talk to their AI agent conversationally and get substantive, context-aware answers. Not generic ChatGPT responses. Answers grounded in their actual pipeline, their actual accounts, their actual deal history.

Here's what pull looks like:

• "Prep me for my 2 PM call with Acme Corp." The agent pulls together the deal history, recent communications, stakeholder map, open action items from the last call, and competitive context. Two minutes. Done. What used to take 30-45 minutes of tab-switching is handled before the rep finishes their coffee.

• "Draft a follow-up email to the VP of Engineering at TechCo. Reference the security concerns from last week's call and tie it to our SOC 2 compliance." The agent writes a draft that sounds like the rep, references actual conversation points, and is ready to send or edit. No templates. No generic copy.

• "What's the competitive landscape for the Vertex deal?" The agent synthesizes mentions from call transcripts, email threads, and CRM notes to build a competitive picture specific to that deal — not a generic battlecard, but what's actually happening in this opportunity.

• "Which of my deals are most likely to slip this quarter?" The agent analyzes engagement patterns, deal velocity, stakeholder activity, and historical close rates to give an honest answer. Not a dashboard — a conversation.

Pull turns the AI into a working partner. It knows the rep's book of business, understands context, and can do real work — not just answer questions but draft, research, analyze, and recommend.

Why you need both (and why one alone fails)

Here's the critical insight most sales tool builders miss: push and pull aren't two features. They're two halves of a complete intelligence model. Remove either one and the whole thing breaks.

Push without pull: the dead-end alert

Imagine you get a Slack notification: "Your champion at DataFlow just left the company."

Great. Now what?

Without pull, the rep has to figure out the response on their own. Who else do they know at DataFlow? What's the deal status? Should they reach out to the former champion at their new company? What's the risk to the deal? Who internally should they loop in?

The signal identified the problem. It didn't help solve it. The rep is back to Alt-Tabbing through five tools to piece together a plan.

Push without pull is a smarter notification system. Useful, but it leaves the rep stranded at the point of action.

Pull without push: the blind spot machine

Now imagine you have a great AI agent you can ask anything — but it only works when you ask. It never reaches out proactively.

The rep preps brilliantly for the calls they know about. They draft great emails when they remember to. But the deal that's silently dying because the economic buyer went dark three weeks ago? Nobody asked about it. The competitive threat that emerged in a call the rep didn't attend? Nobody flagged it.

The most dangerous risks in a pipeline are the ones reps don't know to ask about. Pull is reactive by definition. It requires the rep to have the question before they can get the answer.

Pull without push creates blind spots — well-researched blind spots, but blind spots nonetheless.

Both together: the closed loop

When push and pull work together, you get something qualitatively different:

1. Push surfaces the signal. "Your champion at DataFlow left."
2. Rep engages via pull. "Who else do I know there? What's the risk to the deal?"
3. Agent delivers context and recommendations. Stakeholder map, relationship strength, suggested next steps, draft outreach.
4. Rep acts. Sends the email, makes the call, adjusts the strategy.
5. Outcome feeds back into the system. The AI learns what signals led to action and refines future push.

This is a closed loop. Signal → context → action → learning. It's how a great sales manager would work with a rep, except it scales to every rep on the team simultaneously and never forgets a deal.

The market's blind spot

Look at any sales tool through the push/pull lens and the gap becomes obvious:

Tool	Push	Pull	Problem
Clari / People.ai	✗	Partial (dashboards)	Manager-focused. Rep has to go look.
Gong	✗	Partial (search)	Conversation data only. No proactive signals.
Outreach / Salesloft	Partial (sequences)	✗	Pushes actions, not intelligence. No conversation.
Apollo	✗	Partial (search)	Top-of-funnel only. Pipeline blind.
Generic AI (ChatGPT)	✗	Generic	No pipeline context. No CRM integration.

Every tool is strong on one axis and weak or absent on the other. The push tools don't think. The pull tools don't reach out. And none of them are built around the individual rep's actual pipeline.

What the right model looks like

The intelligence model sales teams actually need has three properties:

1. Push is signal, not noise. The AI doesn't alert on everything. It monitors everything and alerts on what matters. This requires real understanding of deal context, not just threshold-based rules. "Deal stuck for 14 days" is a rule. "Economic buyer engagement dropped 40% while your competitor scheduled a meeting with the technical team" is intelligence.

2. Pull is contextual, not generic. When the rep asks a question, the answer should reflect their specific deals, accounts, relationships, and history. "Prep me for my call" should produce a brief grounded in actual CRM data and recent interactions — not a generic framework for how to run a discovery call.

3. Both live where the rep lives. If the intelligence requires a new tab, a new app, or a new login, adoption dies. Push and pull both need to meet the rep in their existing workflow. For most teams, that's Slack or Teams. Not another dashboard. Not another portal.

The bottom line

Sales reps don't need more tools. They don't need more dashboards. They don't need more automation that fires without thinking.

They need an intelligent system that watches their pipeline and tells them what matters (push), and an AI partner that helps them act on it (pull). Both. Together. In the tools they already use.

That's not a feature list. That's a fundamentally different model for how sales intelligence should work.

Push and pull. Signal and action. Watching and helping.

It's the model sales teams have needed for years. It's finally here.