---
title: "Turning Sales Teams Into High-Performers with AI"
episode: 45
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Yogi Punjabi"
guest_title: "Founder & CEO, PeopleLens"
date_published: 2025-10-29
date_modified: 2026-07-22
duration: 00:29:20
word_count: 4310
topics: ["sales-enablement", "ai-in-gtm", "sales-leadership", "revenue-operations", "gtm-strategy"]
canonical_url: https://leanscale-knowledge-hub.netlify.app/podcast/yogi-punjabi-high-performers-ai/
source: "LeanScale Podcast Knowledge Hub — https://leanscale-knowledge-hub.netlify.app"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# Turning Sales Teams Into High-Performers with AI

_Yogi Punjabi on building PeopleLens — an AI layer that makes every rep a better performer and every manager a better coach_

**Episode 45 · The LeanScale Podcast**  
Yogi Punjabi, Founder & CEO, PeopleLens · Hosted by Anthony Enrico  
Published October 29, 2025 · Updated July 22, 2026 · 00:29:20  
Canonical: https://leanscale-knowledge-hub.netlify.app/podcast/yogi-punjabi-high-performers-ai/

**Topics:** Sales Enablement · AI in GTM · Sales Leadership · Revenue Operations · GTM Strategy


## Executive summary

Most sales-improvement conversations obsess over the customer and the number. Yogi Punjabi — founder and CEO of PeopleLens — argues the missing variable is the rep. After a career that zig-zagged from strategy consulting through sales, marketing, product, people, and IT, he landed on a thesis he now builds a company around: sales performance is not just a revenue problem, it's a people problem. This LeanScale Podcast conversation with Anthony Enrico is part origin story, part live product tour, and part clinic on how AI should actually be pointed at a sales org — at making humans better, not at replacing them.

The origin came out of pain. At Palo Alto Networks in 2018-2019, a new CEO set out to turn a single-product firewall company into a cybersecurity giant, buying 17 companies in five quarters. The stock doubled — then the company missed its number two quarters in a row and the stock fell straight back to where it had started. More sales ops, more strategy consultants, and more customer insights didn't fix it. Yogi's boss, on the people team, told him to 'put on your people lens' and focus on the rep and the manager. Stitching together calendar, CRM, and enablement data on a struggling AE named Mike revealed exactly where he needed help — product knowledge, consultative skills, mindset. Coached on those, Mike went from a $50K box seller to a seven-figure SaaS seller. That turnaround became the product.

PeopleLens does four things: it unifies the siloed data scattered across every rep touchpoint (CRM, conversation intelligence, enablement systems, calendar, engagement), runs proprietary models over that structured and unstructured data, renders a persona-specific lens for execs, managers, and reps, and then pushes personalized performance nudges into the tools where reps already live — Salesforce, the calendar, Slack. In the demo, a manager sees not just that a rep is struggling but why (a late economic buyer in the MEDDPICC cycle) and the size of the prize (bring buyers in earlier, close ~15% higher, roughly $100K more next quarter). The exec lens stack-ranks the team and surfaces the 'massive middle' — the B-pool where the biggest, cheapest gains hide.

The throughline is a reframe of how leaders make people decisions. Grow-or-go calls are usually driven by anecdote in a QBR, not by facts about where each seller actually breaks down. Yogi's mission — 'help reps grow as opposed to letting them go' — is grounded in hard math: cutting a rep is roughly 18 months of lost and rebuilt revenue once you count recruiting, ramp, and enablement. Anthony reinforces it from LeanScale's growth-modeling work, where sales-team attrition is the most-overlooked driver of capacity. On AI, Yogi is bullish but pointed: data exploded while insight only trickles in, so the win is synthesizing what's already there and delivering it as an in-workflow nudge — not adding another dashboard.

Who should listen: sales and enablement leaders who want to coach the middle instead of firing it, RevOps and systems leaders drowning in a 30-plus-tool GTM stack whose data never connects, CROs and revenue executives who make grow-or-go decisions, and founders weighing when to invest in real coaching infrastructure. The practical answer to 'when' — when a new methodology or a new leader arrives — plus a fast, pilot-first adoption path (lenses live in about a day, a 30-day pilot to build the business case) make this a concrete playbook for turning a whole team into higher performers with AI.


## Key takeaways

1. **Sales performance is a people problem, not just a revenue problem** — Yogi's founding insight, forged at Palo Alto Networks when more sales ops, strategy consultants, and customer insights failed to reverse two missed quarters. Only when his team 'put on the people lens' — focusing on the individual rep and their manager and stitching their data together — did they find and fix what was actually broken.
   _Why it matters:_ When results slip, instrument the seller and the coaching relationship, not just the pipeline. The lever most orgs never pull is diagnosing the individual with the same rigor they apply to the customer and the funnel.
   _For:_ Sales Leaders, Revenue Executives, RevOps Leaders

2. **The value is insight, not more data — unify the silos** — Data sets have exploded while insights only trickle in. Reps' signal is scattered across CRM, conversation intelligence, enablement/LMS, calendar, and engagement systems, and nobody has time to triangulate three open tabs. PeopleLens' first job is to be the connective tissue that brings those systems together.
   _Why it matters:_ Don't buy another point tool that adds a data set; the unmet need is synthesis. Prioritize the layer that turns systems you already own into one pointed answer about where a rep needs help.
   _For:_ RevOps Leaders, Sales Leaders, Founders

3. **Bring the 'forgotten rep' into the equation** — For decades GTM data centered on the customer — spouse's name, pet's name, a gazillion fields. Yogi's first-principles model puts the customer on one side, the product at the center, and the rep on the other, instrumenting every attribute, skill, competency, and time allocation to model where the seller struggles.
   _Why it matters:_ Give each rep their own data lens, the way you built one for the account. The competency and time-allocation signal is where ramp speed, win rate, and coachable growth actually live.
   _For:_ Sales Leaders, RevOps Leaders

4. **Coach the 'massive middle' instead of cutting it** — In most orgs the biggest opportunity is the B-pool — the massive middle between the stars and the strugglers. The exec lens stack-ranks the team and surfaces each rep's top drivers so leaders can lift the middle with personalized coaching rather than making grow-or-go calls on anecdotes in a QBR.
   _Why it matters:_ Reframe the quarterly people decision from 'who do we fire' to 'where do we coach.' The middle is where a manager, armed with the specific driver, can move the top-line needle fastest.
   _For:_ Sales Leaders, Revenue Executives, RevOps Leaders

5. **Letting a rep go is the most expensive math in sales — ~18 months** — Yogi calls cutting a rep the most expensive math in sales: roughly 18 months of revenue once you account for recruiting, ramp, and enablement. Anthony reinforces it from LeanScale's growth models, where sales-team attrition is the most-overlooked driver of capacity — teams model new hires and ramp but forget good-leaver/bad-leaver risk.
   _Why it matters:_ Price attrition into your capacity plan and treat retention-through-coaching as a growth lever. Every rep you keep and improve is far cheaper than the backfill you'd otherwise fund.
   _For:_ Revenue Executives, Founders, RevOps Leaders

6. **Meet reps where they live — nudge inside Salesforce, calendar, and Slack** — Insight only counts if it changes behavior in the flow of work. PeopleLens surfaces the next best action inside Salesforce, sends it to the rep's calendar, or drops it in Slack as a nudge, then tracks the full cycle — active nudge, completed nudge, and how completing it moved an outcome like quota attainment.
   _Why it matters:_ Deliver coaching as an in-workflow nudge, not another dashboard the rep has to remember to open. Closing the loop from insight to action to outcome is what makes the coaching stick.
   _For:_ Sales Leaders, RevOps Leaders

7. **Diagnose at two levels: the deal and the rep 360** — PeopleLens works at the deal-level aggregate — bringing calls and emails together to find where a rep drops off in a specific deal — and at the rep 360, isolating the competency or skill a seller most needs to lift across their journey. The same engine also explains ramp: a few drivers (e.g., time with SEs for a technical product) predict how fast a new hire gets productive.
   _Why it matters:_ Separate 'help this deal' from 'grow this rep,' and design your coaching cadence to hit both. The deal fixes this quarter; the competency fixes every quarter after it.
   _For:_ Sales Leaders, RevOps Leaders

8. **Marry conversations to a methodology to measure adoption per rep** — When a leader rolls out a methodology — MEDDPICC, SPICED, value selling — most teams can only track adoption in aggregate. PeopleLens reads calls and emails against the framework and surfaces, at the individual level, exactly which element a rep is missing (Whitney's economic buyer arriving late in the cycle), so coaching conversations aim at the real gap.
   _Why it matters:_ A new sales methodology is a natural trigger to add PeopleLens: it turns a broad framework into per-rep, per-element adoption data your managers can actually coach against.
   _For:_ Sales Leaders, RevOps Leaders, Revenue Executives

9. **Fast time-to-value beats heavy integration** — PeopleLens has APIs against a few dozen systems and can stand up exec, manager, and rep lenses in about a day by pulling from Salesforce, conversation intelligence, enablement systems, and the calendar. It runs 30-day pilots — visible on day one, then tuned as the models sharpen — so customers avoid expensive integrations and implementations before proving value.
   _Why it matters:_ Insist on a pilot-first, low-lift adoption path for coaching tooling. Value you can see in a day and prove in a month is how you build the business case for a long-term investment.
   _For:_ RevOps Leaders, Founders, Revenue Executives

10. **Your GTM stack has 30+ tools and none of them talk** — Anthony notes that at Series B/C, the go-to-market tech stack alone commonly exceeds 30 tools — not counting core email and Slack. Customers keep wanting to add data sets, but when asked how they use the data already in their backyard, the honest answer is that it sits siloed.
   _Why it matters:_ Before buying the 31st tool, get value from the 30 you have by connecting them. The scarce resource isn't data — it's the connective tissue and the personalized insight on top of it.
   _For:_ RevOps Leaders, Founders


## Frameworks

### Put On Your People Lens (03:16)

**Definition:** Reframe underperformance as a people problem, not just a revenue problem: focus on the individual rep and their manager, and stitch together the data (calendar, CRM, enablement) that reveals where each is struggling.

Born at Palo Alto Networks when more sales ops, strategy consultants, and customer insights failed to fix two missed quarters. Focusing on a struggling AE (Mike) and his manager — and serving them the specific gaps in product knowledge, consultative skills, and mindset — turned a $50K box seller into a seven-figure SaaS seller and became the PeopleLens thesis.

### Unify → Model → Lens → Nudge (05:33)

**Definition:** PeopleLens' four-step loop: (1) unify siloed rep-touchpoint, org, and people data into one connective tissue; (2) run proprietary models over structured and unstructured data; (3) render a persona-specific lens (exec, manager, rep); (4) push personalized performance nudges and agents to the front line.

The design answer to 'data sets exploded but insights only trickle in.' The value isn't more data — it's synthesizing what's already scattered across CRM, conversation intelligence, enablement, and calendar into a pointed, in-workflow action for the person who has to execute.

### Three Persona Lenses (Exec / Manager / Rep) (07:07)

**Definition:** The same underlying data rendered three ways — an exec lens for strategic bets and stack-ranking, a manager lens that diagnoses why a specific rep is struggling, and a rep lens that gives each seller a 360 view of their own outcomes, competencies, time allocation, and nudges.

Focus is on the front line where execution happens. The manager lens surfaces the driver of a rep's performance (a MEDDPICC element, time with customers, email response time); the rep lens closes the loop from nudge to completed action to a moved outcome like quota attainment.

### First Principles: Customer, Product, Rep (13:21)

**Definition:** For decades GTM data centered almost entirely on the customer (spouse's name, pet's name, endless fields). True first principles put the customer on one side, the product at the center, and the rep on the other — bringing the 'forgotten' rep into the equation with their own data lens.

PeopleLens instruments every rep attribute, skill, competency, and time allocation, then models where the seller struggles and surfaces the specific muscle to flex — the same investment orgs historically made only in understanding the account.

### Coach Reps, Don't Cut Them (the Massive Middle) (17:29)

**Definition:** Grow-or-go decisions are usually driven by anecdote in a QBR, not by facts about where a seller breaks down. The biggest, cheapest ROI is the 'massive middle' B-pool; because letting a rep go is roughly 18 months of revenue, personalized coaching that lifts the middle beats cutting.

The exec lens stack-ranks reps and surfaces each one's drivers so the CRO/RevOps/enablement conversation shifts from 'who do we fire' to 'where do we coach' — changing both the narrative and the math on the most expensive decision in sales.


## Quotes

_Speakers inferred from an undiarized transcript — verify before attributing._

> "My boss said, 'We've got to do our bit. This is our problem. And you've got to put on your people lens.' And that's when we began to focus on the rep, focus on the manager."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (03:16)

> "We saw Mike go from that world of 50K box seller to the world of a seven-figure SaaS seller. And in that pain, the world of PeopleLens came to life. Our mission is really to make every rep a better performer and a manager a better coach."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (04:07)

> "People who go into sales don't go into sales to lose. So they're highly competitive, highly interested in self-improvement and becoming the best salesperson they can be."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 45 (04:52)

> "Data sets have really exploded, but insights continue to only trickle in."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (05:33)

> "It's really about helping reps grow as opposed to letting them go."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (06:25)

> "When we bring the economic buyers in earlier, deals close at 15% higher, giving Whitney the impact and the opportunity to lift her game to do another 100K in revenue as she goes into next quarter."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (08:50)

> "The customer on one side, the product at the center, and the rep on the other. We're trying to bring that rep into the equation — they were a forgotten part — and begin to serve them with their own lens."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (14:10)

> "The most expensive math in sales is when you let reps go. It's almost 18 months of math if you think about revenue coming in."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (17:29)

> "There's an opportunity to change that narrative, to change that math, and to begin to think about coaching reps and not cutting reps."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (18:21)

> "One of the biggest missing attributes that people overlook is sales team attrition and how that impacts your capacity."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 45 (19:10)

> "In a day we can get this going, so companies don't have to really invest or care about expensive integrations or expensive implementations."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (22:25)

> "The ecosystem has gotten rich with more systems, with more data, but that insight is lacking, and there's a need to personalize those insights for the managers and the reps."
>
> — Yogi Punjabi, The LeanScale Podcast Ep. 45 (23:12)

> "At series B, series C stage, the average number of tools is over 30 in your go-to-market tech stack alone."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 45 (23:59)

> "I think of the sales managers as the coaches of the team. How do they help the B players become A players?"
>
> — Anthony Enrico, The LeanScale Podcast Ep. 45 (27:11)


## Practical advice by role

### Sales Leaders

- Diagnose why a rep is struggling before deciding grow-or-go: get to the specific driver (a MEDDPICC element, time with customers, email responsiveness), not a leaderboard rank in a QBR.
- Coach the massive middle. The B-pool is where the biggest, cheapest top-line gains hide — personalized coaching there beats cutting and backfilling.
- Deliver coaching as an in-workflow nudge (Salesforce, calendar, Slack) and track the full cycle — active nudge to completed nudge to a moved outcome.
- Use a new methodology rollout (MEDDPICC, SPICED, value selling) as the trigger to measure adoption per rep and per element, not just in aggregate.

### RevOps Leaders

- Get value from the 30+ tools you already own before buying the 31st: the unmet need is connective tissue and synthesis, not another data set.
- Instrument the rep the way you instrument the account — attributes, competencies, time allocation — so coaching is driven by data, not anecdote.
- Insist on a pilot-first adoption path: lenses that stand up in about a day and prove value in a 30-day pilot before any heavy integration commitment.

### Revenue Executives

- Reframe the quarterly people decision from 'who do we fire' to 'where do we coach' — cutting a rep is roughly 18 months of lost and rebuilt revenue.
- Validate your blockers with data. A new CRO's hypotheses about what's broken should be confirmed against per-rep driver data before you place strategic bets.
- Align enablement and RevOps programs to the drivers the data surfaces (e.g., MEDDPICC adoption, technical skills) so strategic investments track real gaps.

### Founders

- Price sales-team attrition into your growth and capacity model — it's the most-overlooked variable behind ramp and new-hire planning.
- Invest in coaching infrastructure when a new methodology or a new sales leader arrives; those inflection points are where per-rep insight pays off fastest.
- Don't outsource rep success to the luck of your managers' talent — give the front line a data lens and personalized nudges to standardize good coaching.


## AI takeaways

**Thesis:** AI's highest-leverage use in sales isn't replacing reps — it's coaching them. PeopleLens unifies siloed data, models where each seller struggles, renders it as a persona-specific lens, and nudges the fix into the rep's workflow, so AI makes managers and reps better rather than fewer.

- **Insight, not more data** — Data sets exploded while insight only trickles in. The AI job is to synthesize CRM, conversation intelligence, enablement, and calendar into one pointed answer — not to add another dashboard.
- **Coach, don't cut** — Models stack-rank the team, surface the 'massive middle,' and name the specific competency to lift — turning grow-or-go from anecdote into evidence and avoiding the ~18-month cost of replacing a rep.
- **Nudge where reps live** — Performance agents push the next best action into Salesforce, the calendar, or Slack, then track active-to-completed nudges and the outcome moved — closing the loop from insight to execution.
- **Read conversations against a framework** — AI reads calls and emails against MEDDPICC/SPICED/value selling to measure methodology adoption per rep and per element, so coaching aims at the real gap (e.g., a late economic buyer).
- **Fast to value** — API connectors stand up exec/manager/rep lenses in about a day; a 30-day pilot proves the case, so AI leverage doesn't require an expensive integration project.

**Agent & automation ideas**

- A performance-nudge agent that watches a rep's activity and deal signals and pushes the single highest-impact coaching action to both the rep and their manager, in-workflow.
- A methodology-adoption agent that scores every call and email against MEDDPICC and flags exactly which element (e.g., late economic-buyer engagement) is capping win rate.
- A ramp-diagnosis agent that identifies the three or four drivers (like SE time for a technical product) predicting fast ramp and routes each new hire accordingly.
- An attrition-risk model feeding the growth/capacity plan — flagging good-leaver risk and coach-vs-cut candidates before they hit the forecast.


## Operations takeaways

### Revenue operations

- **Connective tissue over new tools.** The scarce resource isn't data — it's synthesis. Connect the 30+ GTM tools you already own before adding the 31st.
- **Instrument the rep, not just the account.** Give each seller a 360 data lens (attributes, competencies, time allocation) so coaching and grow-or-go run on facts, not anecdotes.
- **Pilot-first adoption.** Insist on lenses that stand up in ~a day and a 30-day pilot to prove value before any heavy integration or implementation spend.
- **Attrition is a capacity variable.** Bake sales-team attrition into the growth model alongside hiring and ramp — good-leaver/bad-leaver risk is the most-overlooked driver of capacity.
- **Align programs to drivers.** Point enablement and RevOps initiatives at the drivers the data surfaces (methodology adoption, technical skills) so strategic bets track real gaps.


## Metrics mentioned

| Value | Metric | Context |
| --- | --- | --- |
| 17 acquisitions in 5 quarters | Palo Alto acquisition spree | Under a new CEO and board, the single-product firewall company bought its way into a cybersecurity portfolio, leaning on homegrown reps for go-to-market. |
| 2 missed quarters → stock back to pre-acquisition price | The reversal | After the stock doubled, two consecutive misses at the end of 2019 erased the gains and sent it right back to where it started. |
| $50K box seller → 7-figure SaaS seller | Mike's transformation | Stitching calendar, CRM, and enablement data exposed Mike's gaps (product knowledge, consultative skills, mindset); coaching them closed the gap and seeded PeopleLens. |
| +15% close rate | Economic-buyer timing | PeopleLens research: engaging the economic buyer earlier in the cycle lifts win rates ~15% — for the demo rep Whitney, roughly $100K more revenue next quarter. |
| ~18 months | Cost of letting a rep go | Yogi's 'most expensive math in sales' — the revenue lost and rebuilt to replace a cut rep once recruiting, ramp, and enablement are counted. |
| ~1 day; 30-day pilot | Time to value | API connectors surface exec/manager/rep lenses in about a day; PeopleLens runs 30-day pilots to build the business case before a long-term commitment. |
| 30+ tools | GTM stack size | Anthony: at Series B/C, the go-to-market tech stack alone commonly exceeds 30 tools, not counting core email and Slack — and the data usually sits siloed. |


## Entities mentioned

- **PeopleLens** (company) — Yogi Punjabi's company (he is founder & CEO); an AI platform that unifies siloed GTM data into exec/manager/rep lenses and nudges to make every rep a better performer and every manager a better coach. · https://leanscale-knowledge-hub.netlify.app/company/peoplelens/
- **Palo Alto Networks** (company) — Where the PeopleLens idea was born: as a single-product firewall company under a new CEO it did 17 acquisitions in 5 quarters to become a cybersecurity giant, doubled its stock, then missed two quarters and gave it all back — prompting Yogi's team to 'put on the people lens' on struggling reps. · https://leanscale-knowledge-hub.netlify.app/company/palo-alto-networks/
- **Tableau** (company) — Named as one of three tools a sales-enablement leader keeps open (alongside Gong and Salesforce) and struggles to triangulate — the siloed-data problem PeopleLens sets out to solve. · https://leanscale-knowledge-hub.netlify.app/company/tableau/
- **Yogi Punjabi** (person, guest) — Founder & CEO of PeopleLens; ex-Palo Alto Networks people tech/analytics, with a career spanning strategy, sales, marketing, product, and people. · https://leanscale-knowledge-hub.netlify.app/guest/yogi-punjabi/
- **Anthony Enrico** (person, host) — Co-founder of LeanScale and host of The LeanScale Podcast. · https://leanscale-knowledge-hub.netlify.app/guest/anthony-enrico/
- **Salesforce** (tool, CRM) — The CRM where PeopleLens surfaces insights and nudges in-workflow, and one of the three tabs an enablement leader triangulates between.
- **Gong** (tool, Revenue Intelligence) — Cited as the conversation-intelligence system an enablement leader has open alongside Salesforce and Tableau; PeopleLens jumps into those calls and marries them against a sales methodology.
- **Slack** (tool, Team Messaging) — One of the channels where PeopleLens delivers performance nudges to meet reps where they live, alongside Salesforce and the rep's calendar.


## FAQ

**Q: What is PeopleLens?**

A: PeopleLens is an AI platform founded by Yogi Punjabi that helps sales teams perform better by focusing on the individual rep, not just the number. It unifies siloed go-to-market data (CRM, conversation intelligence, enablement systems, calendar, engagement), runs proprietary models over it, and renders a persona-specific lens for execs, managers, and reps — then pushes personalized coaching nudges into tools like Salesforce, the calendar, and Slack. Its mission is to make every rep a better performer and every manager a better coach.

**Q: What problem does PeopleLens solve for sales teams?**

A: Sales data has exploded across dozens of tools, but insight only trickles in and sits siloed. Leaders make high-stakes grow-or-go decisions on anecdotes rather than facts about where each seller actually breaks down. PeopleLens acts as the connective tissue across those systems and surfaces, at the individual level, the specific driver a rep needs help with — turning scattered data into pointed, coachable action.

**Q: How does PeopleLens help managers coach reps?**

A: In the manager lens, a leader picks an outcome (like quota attainment), sees the leaderboard, and drills into a struggling rep to learn not just that they're behind but why — for example a MEDDPICC gap where the economic buyer enters late in the cycle. PeopleLens quantifies the opportunity (bring buyers in earlier, close ~15% higher) and delivers the next best action as a nudge inside Salesforce, the calendar, or Slack, then tracks whether completing it moved the outcome.

**Q: What are the three lenses in PeopleLens?**

A: PeopleLens renders the same underlying data three ways. The exec lens stack-ranks the team, surfaces the 'massive middle,' and ties reps' drivers to strategic bets. The manager lens diagnoses why a specific rep is struggling and what to coach. The rep lens gives each seller a 360 view of their outcomes, pipeline, competencies, time allocation, and active/completed nudges. The focus is the front line, where execution happens.

**Q: How does PeopleLens integrate with an existing GTM tech stack?**

A: PeopleLens has APIs built against a few dozen systems and pulls from Salesforce, conversation-intelligence tools, enablement/LMS systems, and the rep's calendar. Because it's a data layer rather than a heavy implementation, it can stand up exec, manager, and rep lenses in about a day and runs 30-day pilots — value is visible on day one, then the models tune and sharpen — so customers avoid expensive integrations before proving value.

**Q: When is the best time to bring on PeopleLens?**

A: Two moments stand out. First, when a leader rolls out a new sales methodology (MEDDPICC, SPICED, value selling): PeopleLens measures adoption at the individual level and pinpoints where each rep struggles. Second, when a new leader or CRO arrives with hypotheses about what's broken and wants to validate them with data before making strategic bets. More broadly, any time you're serious about coaching the team is a good time.

**Q: Why is letting a rep go the most expensive math in sales?**

A: Yogi Punjabi estimates that replacing a rep costs roughly 18 months of revenue once you account for recruiting fees and time, enablement and training, and the quarters it takes a new hire to ramp and build pipeline. That makes coaching an underperforming rep — especially one in the 'massive middle' who may just need the right help — far cheaper than cutting and backfilling, which is why PeopleLens frames its mission as helping reps grow rather than letting them go.


## Timeline

- **00:00** — Intro: meet Yogi and PeopleLens
- **00:44** — The origin: from strategy consulting to 'people lens'
- **02:25** — Palo Alto Networks: 17 acquisitions, then the miss
- **03:16** — 'Put on your people lens': the Mike turnaround
- **05:33** — What PeopleLens does: unify, model, lens, nudge
- **07:07** — The manager lens: Leila and Whitney
- **08:50** — Nudges in Salesforce, calendar, and Slack + the rep lens
- **10:51** — Deal-level vs. rep 360; why reps take long to ramp
- **13:21** — First principles: customer, product, and the forgotten rep
- **14:50** — The exec lens: the massive middle and grow-or-go
- **17:29** — The most expensive math in sales + attrition
- **20:31** — Integrations: connective tissue across 30+ GTM tools
- **24:39** — The best time to bring on PeopleLens
- **27:11** — Wrap-up and how to reach Yogi


## Related episodes

- **Ep. 95: Why AI Means More RevOps Hires, Not Fewer** (Jimmy O'Halloran) — Sales enablement as the 'secret sauce' and the argument that AI should grow the team, not shrink it — the operator's mirror to Yogi's coach-the-rep thesis. · https://leanscale-knowledge-hub.netlify.app/podcast/jimmy-ohalloran-new-relic-revops-consumption-revenue/
- **Ep. 85: Why AI + GTM Engineers Can't Replace RevOps** (Tessa Whittaker) — The sibling case that AI augments the human operating layer rather than replacing it — parallel to PeopleLens making managers better coaches. · https://leanscale-knowledge-hub.netlify.app/podcast/tessa-whittaker-ai-gtm-engineers-revops/
- **Ep. 88: Why AI Won't Close Your Biggest Deals** (Michael Kiernan) — A CRO's view on the limits of AI in enterprise selling; pairs with Yogi's 'point AI at coaching the human, not replacing them.' · https://leanscale-knowledge-hub.netlify.app/podcast/michael-kiernan-nextdoor-ai-wont-close-deals/
- **Ep. 15: Where Should RevOps Report?** (LeanScale) — Org-design context for who owns the coaching, enablement, and systems layer that PeopleLens plugs into. · https://leanscale-knowledge-hub.netlify.app/podcast/cameron-legge-where-revops-report/
- **Ep. 6: Why Your Forecast Is Broken** (LeanScale) — The planning-and-capacity companion to Anthony's point that sales-team attrition is the most-overlooked driver of forecastable capacity. · https://leanscale-knowledge-hub.netlify.app/podcast/why-your-forecast-is-broken/


## Full transcript

_Machine-transcribed and not diarized; speaker attribution is inferred._  
_Transcript only, as a separate file: https://leanscale-knowledge-hub.netlify.app/podcast/yogi-punjabi-high-performers-ai/transcript.md_

### 00:00 — Intro: meet Yogi and PeopleLens

**[0:00]** (logo whooshing) Today we have founder, CEO of People Lens. Yogi, thank you so much for being here today. So stoked to dive into your platform. The experience that you take from a real eclectic background of business and sales and go-to-market expertise, I think is really shown in the way you've crafted the product. I don't think there is anyone that we work with at LeanScale or anyone who listens to this channel that doesn't believe that there's a lot of opportunity to improve how the sales team is performing. And I think your AI powered approach to coaching and improving sales performance is a really powerful way to help increase results

### 00:44 — The origin: from strategy consulting to 'people lens'

**[0:44]** on the revenue side of the business. So thank you for being here. Excited to dive into the product. Before we do that though, I always love to hear what gave you the inspiration to start People Lens and how did you get everything kicked off? - Absolutely. Anthony, thank you for that introduction and just delighted to be here. Congratulations on that swanky setup there. The studio looks really cool and I'm a fan of the part. Really see the value that this adds to your clients and what you do to bring innovation to the community and to the world. My journey goes way back. So I was a strategy consultant and did that for a while. As I left that world,

**[1:35]** I got lost in tech land and I bounced around a bunch. And each time I changed companies, I changed functions. So I went from the world of strategy to the world of sales, from there to the world of marketing, from there to the world of product. And I was really fortunate along that journey to find great set of folks, great set of mentors to guide me. And I continued on that journey, went from product to people to IT. I was at Palo Alto Networks 2018, 2019, new CEO, new board. We were a very successful company at that point, a single product, firewall company. New CEO came with a vision like, we need to be a cybersec giant

### 02:25 — Palo Alto Networks: 17 acquisitions, then the miss

**[2:25]** and off we went on the acquisition trail, 17 acquisitions, five quarters, really buying our way into that portfolio. With each acquisition we brought in the product team, the engineering team, but for go-to-market we'd lean on our homegrown reps and the story began to play out. Stock doubled in a pretty short span of time, revenue grew at a nice clip. But then as we were wrapping up 2019, stuff hit the fan. And we missed our numbers two quarters in a row. The stock literally fell off the cliff. It went back to exactly where it was before the first of those 17 acquisitions and-- - Oh man. - We began to, yeah, it was all hands on deck.

### 03:16 — 'Put on your people lens': the Mike turnaround

**[3:16]** And we began to try a few different things, more sales ops, more strategy consultants, more customer insights, nothing seemed to quite play out. And my boss, I sat in the people team, leading people tech and people analytics. My boss said, "We've got to do our bit. "This is our problem. "And you've got to put on your people lens." And that's when we began to focus on the rep, focus on the manager. And as we dug in, as we began to stitch those data sets, we saw Mike, that AE was struggling. He had grown up as a box seller, a hardware seller. He did that 50K deal month after month after month. But in this new construct, in this new portfolio,

**[4:07]** he was struggling. And as we began to see where he needed help, as we again brought those data sets, whether it was his calendar, his CRM data, his enablement systems data, we saw he needed help with product knowledge, with consultative skills, with mindset. And as we began to serve him those pieces together with his manager's help, we saw Mike go from that world of 50K box seller to the world of a seven figure SAS seller. And in that pain, the world of people lens came to life. And our mission is really to make every rep a better performer and a manager a better coach. And again, grateful for all the folks that have guided this journey to bring it to life.

**[4:52]** - That's a great story. And I love like Palo Alto Networks, such a gem in the tech community and such a good story. So I'm sure there's so many good learnings there. And I think you're also dealing with a group of people, people who go into sales don't go into sales to lose. So they're highly competitive. They're highly interested in self-improvement and becoming the best salesperson they can be. And it also impacts their paycheck. So they have every incentive in the world to try to do better and same with their managers and coaches. So I think everybody is always really hungry for any bit of knowledge that can give them an edge

### 05:33 — What PeopleLens does: unify, model, lens, nudge

**[5:33]** in becoming a better salesperson and winning more revenue. So I think where you're at is a perfect place to be. And I would love to, I know you have a demo prepared for us. I'd love to dive in and just take a look at the approach that you have taken to get this type of Intel to a person to help them become better. - Absolutely, Anthony. And the more we do this, the more we recognize the struggles in a world today where data sets have really exploded, but insights continue to only trickle in. And so we do really four things. One is we unify the data sets that are sitting across the enterprise, pretty much every rep touch point going well beyond

**[6:25]** that go-to-market data set, we widen that aperture and augment that customer data set with org and people data sets, i.e. a rep's calendar, their enablement systems, their engagement systems, their conversation, and we bring those together. We unify those systems where that connective tissue. Number one, number two is we are able to then run our proprietary models, bring those structured and unstructured data sets. Number three, we really put this together in a lens for every persona. Of course, for the corner office and for the execs, we have their own lens, but we largely focus on the front lines where execution happens.

### 07:07 — The manager lens: Leila and Whitney

**[7:07]** So we have a manager lens and a rep lens, and we help the individuals with where they are at. It's really about helping reps grow as opposed to letting them go. And then four, we make it pointed, we make it personalized with our performance agents and our nudges that we bring to the front lines to help them understand where they need to execute. So let's jump in and see how that plays out. And we'll start with the manager lens. So let's bring that up here. Awesome. So this is the manager lens. Leila is a manager. She's got a bunch of folks on her team. She can pick an outcome she really cares about. Here, she'll jump into code entertainment,

**[8:01]** and she knows who sits where on her leaderboard. She knows who's a performer, who's not. So she'll go in and pick Whitney, Whitney's struggling. Leila obviously knows that. She can pick a best-in-class performer, or she can pick Annabelle, and Leila knows this. What she doesn't quite know is why is Whitney struggling? And as people lens, surface is the key driver for Whitney's performance, or lack thereof. They happen to be her med pick score, her time with customers, her time to respond to emails. And we now get really pointed. It's about identifying where in that med pick is Whitney really struggling.

### 08:50 — Nudges in Salesforce, calendar, and Slack + the rep lens

**[8:50]** And we see her economic buyers coming in later in the cycle. Our research indicates that when we bring them in earlier, deals close at 15% higher, giving Whitney the impact and the opportunity to lift a game to do another 100K in revenue as she goes into next quarter. All of this is obviously visible inside Salesforce, or it can get sent to a rep's calendar as a nudge, or in her Slack, really meet them where they live. So this is that manager lens. What we also have is the rep lens, where Whitney can jump into her own lens. She obviously has a bunch of dashboards today, but this is her lens. She can begin to see her outcomes. What's she making?

**[9:48]** How can she do a little more? Painting a few scenarios out there. Her meetings, her manager one-on-one, the agenda, the nudges that are active completed. Her pipe, the activities, where she allocated her time, last week, last quarter, her competencies, her learning, really that 360 view for her to help her zoom into where she needs to go. But where this again comes to life is in that execution flow. And she can begin to see what are the nudges that have come in her direction, the active nudges and the completed nudges. Full cycle, we can begin to see where did she need that help? Where did Leila, her manager, nudge her?

**[10:33]** And once she nudged her, once she completed that nudge, how did it full cycle, again, move the needle on an outcome, her code attainment, really making sure we can see and grow the top line with a focus on that frontline.

### 10:51 — Deal-level vs. rep 360; why reps take long to ramp

**[10:51]** - I love it, and I think a lot of this, like you said, this data is kind of in disparate areas. They have to log into a lot of different dashboards or tools to get some component of this. But I think the tailored nudges that are specific to improving their performance is really unique. On those nudges, are you looking at this at the deal level as well, how to perform specifically better for a particular deal? Are you looking at this just for the rep in general, or are you kind of looking at both, like high level zoomed out of the person, but then in the micro with a specific dealer opportunity? - Great, great question, Anthony.

**[11:36]** And so what we see is, for example, one of our customers, a sales enablement leader, she's got Gong open here, Salesforce open here, Tableau open here, and she's trying to triangulate between those three and really struggles to surface, where is that individual at, and where does the individual need the help? What People Lens is able to do is bring those pieces together for her, and then zero into what does the manager need to do to help that rep? And so for us, it's doing it at two levels. One is at the deal level aggregate, not just at the call, but bringing call, bringing emails, trying to piece those together and diagnose

**[12:28]** where does this individual drop off in a deal? And the second layer we do that at is really thinking about it with a rep lens, a true rep 360, zeroing into what's the muscle that a rep, really needs to lift to up their game. And that could be a competency, that could be a skillset. So we surface that across their journey, for example, why do reps take long to ramp? And we are able to understand like what are the three or four drivers that matter inside a company? For example, if it's a technical product, they could be spending more time with the product guy. So with their SEs, and that matters in how quickly you ramp,

### 13:21 — First principles: customer, product, and the forgotten rep

**[13:21]** that matters in how you surface your inhibitors and really address them quickly. And that is relevant both in the channel scenario and in the sales scenario. So really getting pointed, but always putting that rep at the center would be observed like really first principles is over the last few decades, a lot of the energy was around the customer. Rightfully, so they got us here, but there've been systems, there've been data sets like around what is the spouse's name? What is their pet's name? Like you can get a gazillion feels on the customer. What we think about is really true first principles, the customer on one side, the product at the center

**[14:10]** and the rep on the other. We're trying to do the same for every rep. We're trying to bring that rep into the equation, they were a forgotten part, and begin to serve them with their own lens. Really thinking about every attribute, every skill, every competency, where they allocate their time, their activities, and then run our models to determine where they're struggling, bring that back to them, really identifying that muscle they need to flex to lift their game. - No, that makes a ton of sense. I think getting the insights that a rep needs to be better is super important, and I think that's where it starts,

### 14:50 — The exec lens: the massive middle and grow-or-go

**[14:50]** like is the individual focused on self-improvement on an ongoing basis? Now for another persona, for execs within a company, they might have multiple sales managers. What type of insights and data are you surfacing that are helping them make decisions, helping them in the boardroom, and helping them make sure their leadership team is doing the job they need to be doing too? - Great question. What we found is that there are really, really solid consultants, experts serving the corner office, but they serve them at points in time, when they're in deep pain, or the RevOps team puts together QBR decks, dashboards, and that's looking at a stack rank of reps.

**[15:39]** They make really important people decisions in those conversations they're about grow or go, and they're largely driven by anecdotes. They're largely driven by what folks might have to say in that meeting, as opposed to hard facts. And so we have this exec lens. Let's see if I can pull it up here. What she begins to see is this overarching view, where as she looks at her team, she can zoom into the three key drivers that matter for her reps, her reps go to attainment, and they're met pick score, they're timed with customer, they're technical skills. And all of this is, again, visible at the aggregate level across the reps,

**[16:31]** so she can look at a stack rank of reps, and tying it back to the manager lens, tying it back to the rep lens, we see here Sherry Stuggling, rather she's one of the top performers, Met Pick is her driver for that performance, and we can also begin to see her top three drivers there. As we double click, we can begin to see that massive middle. And what we see is in most organizations, there is that B pool or that massive middle, and there's a massive opportunity to help these folks lift their game. As we zoom in there, we can look in to see where is each individual struggling again, and how can the manager, the respective manager,

### 17:29 — The most expensive math in sales + attrition

**[17:29]** begin to help the Joanne, the Cordels of the world at an aggregate level when the CRO sits down with their RevOps leader or their enablement leader, they can have a conversation on what are their strategic initiatives, their priorities, their programs, are they aligned to Met Pick, are they aligned to growing technical skills, because this is that opportunity to surface and make those bets really aligned with the insights coming through across the team. What we found is the most expensive math in sales is when you really rep, let reps go, and it's really expensive. It's almost 18 months of math if you think about revenue coming in.

**[18:21]** And there's an opportunity to change that narrative, to change that math, and to begin to think about coaching reps and not cutting reps, because that is quite a game changer, and that massive middle pool can really move that needle if it's addressed with personalized insights and helping that manager, that quarterback, guide those conversations, lead those reps, change their game. - Yeah, one of the biggest things we do at Lean Scale, so for all of our customers, we put together a growth model, we lead planning for the companies that we work with, and one of the biggest missing attributes that people overlook is sales team attrition

**[19:10]** and how that impacts your capacity. So typically, you have your current reps, you're thinking, okay, I'm gonna add five, 10, 20 more throughout the year, and this is what their capacity is gonna be. People are starting to understand ramp now, like, okay, it's gonna take a quarter or two for them to ramp, so I need to hire them earlier. They completely leave out of the equation, which one of those reps are gonna be good leavers or bad leavers, ones that you hire, you made a mistake, you need to make a quick decision, which one of your good reps is gonna find an even better job somewhere, and how are you backfilling that,

**[19:47]** and how can you lower the attrition rate as much as possible, 'cause it's very expensive. The recruiting fees, recruiting time, even if you're not paying for a recruiter, enablement and training and ramp, like, two quarters of them trying to build pipeline, it's immense how much you invest in that team. So for you to make all that investment and then they just leave and go somewhere else, or you think they're a lost cause and not worth keeping when maybe they just need better coaching, it's a huge impact to the growth of any company. - Yeah, very, very well said, Anthony. And so it really ties back to our mission. We believe reps are, as you said,

### 20:31 — Integrations: connective tissue across 30+ GTM tools

**[20:31]** really have that potential. It's about helping them surface that and empowering the manager with the AI agents with that performance nudge to grow that rep as opposed to letting them go. - Absolutely. Well, I was hoping we could transition a little bit. This is maybe for the RevOps-y folks that are listening right now. What does the integrations ecosystem look like for Peoplelens? How do we get all the rich data that we're capturing in a million different tools into Peoplelens so you can let your models do the magic on coaching the reps? - Yeah, super. As we go into customers, that's really at the heart of it.

**[21:19]** What we see is they've got a pretty, pretty solid stack. They have a fancy CRM, a fancy conversational intelligence play, a couple of enablement systems, LMS, CMS, and they obviously have the reps calendar, a few other productivity plays out there. What we find is that they wanna add more data sets. And when we begin to ask the question, how are you using the data that's sitting in your backyard today? The answer quickly leads to a siloed set of data. - Sure. - So for us, it's imperative as we really build out our platform to be that connective issue and to bring the data sets from across those systems. So we have APIs built out again,

**[22:25]** against a few dozen systems that just pretty much starts off bringing in data from your Salesforce, from your conversational intelligence systems, from your enablement systems, from your calendar, and let our models then surface these execs, these manager, these replans out of the gate, like in a day we can get this going. So companies don't have to really invest or care about expensive integrations or expensive implementations. Out of the gate, we can begin to really put this out. And we do 30 day pilots, where all of this is visible in the first day or so, and then we just tune. We let our models get better, let the insights get sharper

**[23:12]** and begin to build out that business case together for that long-term investment. So we believe there's a massive ecosystem out there. And as RevOps leaders or as systems leaders, the ecosystem has gotten rich, again, with more systems, with more data, but that insight is lacking and there's a need to personalize those insights for the managers and the reps, which is where our focus is. - Makes a ton of sense. And I don't think people realize, so the average size of the go-to-market tech stack, we primarily work with series A, B, C companies. When you're at that series B, series C stage, the average number of tools is over 30

**[23:59]** in your go-to-market tech stack alone. That's not talking about your core tools like email and Slack and everything like that. That's just tools dedicated to go-to-market. So yeah, pulling all those insights together in this context of coaching and getting your reps better, really, really tough to do and really siloed. So I think being able to do that is really powerful. So Yogi, I think anytime's probably a good time to be investing in coaching your sales team, coaching your go-to-market team. But from your perspective, when have you seen is the best time to bring on people lens? And for people to start getting really serious

### 24:39 — The best time to bring on PeopleLens

**[24:39]** about investing in this level of coaching for their team. - Yeah, great point. We see a few and what we see is when a leader comes in

**[24:52]** and they are bringing in a new methodology, could be medic, could be spiced, could be value selling.

**[25:03]** This becomes that vehicle to really understand adoption, not just at an aggregate level, but at an individual level, understand the elements and the competencies in the areas that the individual is struggling with. Because a bunch of our customers have the conversation intelligence platform, but they don't have the time. They're not able to really dig in and understand where is a rep struggling. What people lens does is it is able to jump into those calls, jump into the email, marry that against the framework. And then surface that like, where is this individual struggling and begin to help the manager decipher that so that their coaching conversations

**[25:51]** are really revolved on that area. So methodology helping accelerate the adoption of that methodology is a massive area. One of the big area is for the exact lens. You have a new leader come in, a new CRO. They have a pretty good hypothesis of what's happening or the blockers, but as they begin to use people lens, they can validate some of their hypothesis. Here are the areas where we need to make a big bet or here are the areas where we need to make those strategic investments. And so that's where we're finding good amount of momentum and some fun conversations happening. - I love it. Like I said, probably anytime's a good time,

**[26:30]** but if you find yourself kind of in that era of your company, where you are, it sounds like you can absolutely extract so much value out of bringing people lens in and starting to use the insights that you provide. Yogi, thank you so much. I think this has been super helpful. I love the way people lens has really thought about it from the lens to the name, which makes it easy to remember, but coming in from a sales rep view, how do I make myself better? What can I focus on to push this deal along, enhance my skills? I care about my career, I care about my performance and giving me the tools to do that is incredibly powerful for me.

### 27:11 — Wrap-up and how to reach Yogi

**[27:11]** Then the managers and coaches, I think of the sales managers as the coaches of the team, how can they lean in and help? How do they help the B players become A players? How do they help decide whether this is somebody who maybe it's not a right fit or they just need the right level of coaching? And then rolling it all the way up to that exact level lens where you can see what company-wide investments do I need to be making to make sure that my sales team is equipped to perform at their highest ability is something that I think is really lacking in the market right now. So this was awesome. Thanks for sharing the product. Thanks for giving all the insights

**[27:48]** from such a fruitful career, but also your experience with people lens as you built this out. Yogi, what's the best way for people to get in touch with you personally and potentially get started with leveraging People Lens today? Yeah, so peoplelens.ai, the demo is out there. That's the best way to get in touch. And of course, LinkedIn, Yogi Punjabi, that's the other really easy to get in touch and get some time. And we can do personalized demo, do a pilot, begin to really put this in the hands of reps. That's the way I'd recommend anybody out there. And you have a terrific audience, right? Anthony, as you have done this for a while,

**[28:36]** you guys are true experts in this space as you take the time and invest the energy to understand the lay of the land and bring that together, stitch it together for a bunch of your clients. So your comments and your perspective from that point of expertise really appreciated that. Absolutely, happy to share it. Thank you so much for being on the podcast. And as you grow and develop and the product continues to iterate and transform, we'd love to have you back. And Yogi, we can't wait to see what you all build next. Thank you for having us. Looking forward to following your journey too. Thank you.


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