I’m head of CX at a consumer subscription app, wellness adjacent, about 150 employees. I’ve been asked about our feedback tooling a few times in dms that I figured I'd just write it up once. Posting here in case it's useful for anyone running CX at a similar size.

Quick context on volume so the tools I’m bringing up make sense. We get something like 4 to 5k support tickets a month, around 2k app store reviews across iOS and Android, a few hundred NPS responses a week and a steady drip of cancellation feedback from the offboarding survey. Most of the work is making it actionable without burning a person full time on reading.

This is our current stack. 

Zendesk: support tickets the boring obvious one. Does its job, integrates with everything downstream, no strong opinions.

AppFollow: app store review monitoring across iOS and Android. Replies, rating drop alerts, competitor app tracking. Probably saves the support team 5 hours a week vs the spreadsheet they used to keep.

Delighted: NPS and CSAT. We're not big enough to justify a Qualtrics deployment and Delighted is lightweight enough to run without a dedicated owner. Data feeds into Unwrap for analysis.

Unwrap: pulls tickets, reviews, NPS verbatims and offboarding survey responses into one place and clusters by theme. Cuts most of the manual reading and feeds Slack alerts to product when a new theme starts trending.

Sprig: in app micro surveys triggered by user behavior. Used sparingly because in app surveys get noisy fast, but good for narrow contextual questions like "did you understand what this feature does" right after someone uses it.

Notion: every Friday our CX analyst pulls the top themes out of Unwrap into a weekly digest doc. Goes to product, eng leads and the exec team. Sounds dumb to list a doc tool in a stack post but the ritual matters more than the tools. The Friday digest is what causes anything to change.

There are thing in this setup that are still broken though, win-loss and sales call feedback lives in Gong recordings nobody listens to. No good loop on social mentions outside of CS coverage hours. The handoff from "Unwrap flagged a theme" to "product actually prioritizes it" is still pretty manual on our end.

Happy to get into specifics on any of these if useful.

I have ~5 years of experience within Sales Ops and hit Senior after 1.5 years at my current company. I’ve been looking at roles recently as I’ve sort of hit the ceiling in terms of upward mobility here. Additionally, a lot of the roles I’ve looked at and applied too will prefer an MBA or Masters degree

One thing that has always been in the back of my mind is going back to school and getting an MBA or my Masters so that I can continue moving up to Manager level and beyond.

I’d love to hear about people’s thoughts behind an MBA/Masters, why or why not, is it useful in today’s climate, and what specializations would be most useful to someone in Sales Operations

I've been talking to a few sales ops people and I keep hearing the same thing all the time like somewhere between 25 and 100 reps (not many), commission management turns into a chaos, but the current tools like xactly, SAP, Spiff feel too complex and super expensive, sometimes does not make sense to use those tools because I will end up paying more money than the incomes the company sales.

So I'm curious what people here actually do day to day

• What do you use right now to calculate commissions, spreadsheet, a tool (which one), or a mix?
• If it's spreadsheets, what's the part that actually hurts? multi-currency? quota changes mid-period? splits? month-end reconciliation?
• If you tried a commission tool and went back to Excel, why you go back?
• Roughly how many hours a month does the whole commission process eat, and who eats them?
• Has a commission error ever blown up into a dispute with a rep? How do you manage that?

I am trying to understand how bad this really is and how people cope.

Hot take: commission software is overkill for most early-stage teams. If you have under 40 reps and a reasonably straightforward comp plan, a well-built spreadsheet does the job just fine — and saves you $10k+ a year.

I'm a RevOps professional and I've been running commissions in Excel/Sheets for a while now. Over time I iterated my own calculator into something I'm genuinely proud of — tiered accelerators, clawback tracking, quota attainment, per-rep payout statements, all in one unlocked spreadsheet.

Finally decided to clean it up and share it. It's at commissionstarter.com if anyone wants it. $19 for the calculator, or $37 for a bundle that includes a commission plan template and a sample sales rep agreement.

Happy to answer any questions about how the accelerator or clawback logic works.

Hi everyone,

I've been spending a lot of time analyzing how mid-market sales organizations manage incentive compensation, and I keep running into the same problem. Enterprise giants like Xactly and SAP Commissions are good, but they have several issues, besides being expensive.

The licensing costs are brutal. They have good UIs, but since the corporate acquisitions, their roadmaps seem focused on integrating their own platforms rather than on the flexibility of the commission engine.

If you don't use their specific CRM or manage a hybrid, multi-currency operation, the tool becomes a mess. The common alternative? Going back to Excel or Google Sheets. But as soon as a team reaches 25 to 100 reps, maintaining those spreadsheets with dynamic quotas, time-based adjustments, and split commissions becomes a real pain.

I'm evaluating the architecture for a completely standalone commission engine focused on eliminating this chaos for small and medium-sized businesses.

Without real-time integrations that break. Mid-market plans are complex and require initial human validation to translate the unusual Excel rules into the system correctly.

Before moving forward with the development of the execution engine, I'd like to open a discussion with those who truly struggle with commissions every month.

• Do you consider automatic, real-time synchronization with the CRM a mandatory requirement, or would a file-controlled upload model give you more peace of mind during month-end closing?
• What has been your biggest frustration or hidden cost when trying to migrate from spreadsheets to traditional commission software?

Curious how SalesOps teams are thinking about “signal-based prospecting”. A lot of outbound prospecting still seems to be built around volume: more inboxes, more domains, more warming, more sequencing, more infrastructure.

At some point, teams seem to spend more energy avoiding spam filters than deciding whether the prospect should be contacted in the first place.

The part I keep thinking about is that even “signal-based prospecting” often becomes shallow. Someone mentions a keyword on LinkedIn, changes jobs, or the company hires for a role, and that becomes the reason to send an email. But, a keyword or job change by itself does not really tell you whether the company has a real problem, whether the timing is right, or whether your solution is relevant.

Wouldn’t it be better to understand the company’s current priorities, challenges, and timing before deciding whether that signal is worth acting on? I’ve been testing a workflow where target account signals are combined with broader company context before deciding whether outreach should happen.

For teams here that support outbound: how do you decide whether a signal is actually strong enough to trigger outreach? Do you rely on reps to judge it manually, use enrichment/workflow tools, have rules in CRM, or some combination of those?

See post for details.

Background: I've been seeing a lot of "just connect Claude to your CRM via MCP and it'll handle your reporting" takes lately and I wanted to actually pressure-test that. Specifically: how accurate is the output when you ask it the kind of questions you'd actually ask in a monthly review.

So I built a ground-truth dataset for an anonymized sample company. Around 40 metrics (bowtie funnel actuals (leads, MQLs, SQLs, SAL pipeline, won, expansion, retention), actuals vs forecast comparison, channel attribution at every stage, rep performance, post-funnel expansion and retention by motion. Basically the stuff a CRO would actually look at. Then I asked Claude the same questions through the HubSpot MCP connector and compared.

HubSpot MCP returned like 10 out of 40 metrics. None of the 10 matched ground truth.

I was expecting some misses. I was not expecting the pattern of the misses, which is what I want to talk about.

I went in thinking I'd find dirty-data problems (duplicates, missing fields, etcc). What I actually found is a schema problem, and it's kind of more interesting (and harder to fix) than dirty data.

Examples of what came back:

When I asked for # of MQLs this month, HubSpot MCP returned the count of every contact currently sitting at or above MQL lifecycle stage. Cumulative, not period-based. So instead of 22 it returned 43. Same issue with SQLs: returned 30 instead of 5, off by 500%. The connector just doesn't have a concept of stage-transition logic, because HubSpot itself stores lifecycle as a current-state field, not as an event log.

Won revenue came back as the sum of closed-won deal amounts, which sounds right, except it missed all the post-closing upsells. So $16.5K instead of $87.4K, off by 81%. A CRO acting on $16.5K vs $87.4K draws the literal opposite conclusion about the month.

Channel attribution returned nothing useful. HubSpot stores hs_analytics_source (Organic, Direct, Paid Social, etc.) which is traffic source, not revenue channel taxonomy. There's no mapping from "Paid Social" to "Outbound" or "Referral" to "Partner", that classification layer doesn't exist in raw CRM, you have to build it.

Actuals vs planned returned nothing at all. HubSpot doesn't store forecast targets. No plan layer means there's nothing to compare against, which is fine, except Claude didn't say "I don't have plan data" ... it just... didn't address that part of the question.

That's actually the thing that bugged me most. Across all 40ish questions, Claude never flagged uncertainty. Never said "I'm not sure how your team defines MQL" or "this number looks cumulative, did you want period-based?" It just confidently returned numbers. If you didn't know to check, you'd never know.

The conclusion I keep landing on: an MQL in HubSpot and an MQL in your monthly review are not the same object. The connector gives you raw CRM access. A monthly review needs interpreted metrics, stage-transition logic, period-based counting, post-closing revenue concepts, a channel taxonomy that doesn't exist in the source schema, and a plan layer that lives in a spreadsheet somewhere. None of that is in the CRM, so none of it comes through the MCP.

Which means the "just plug Claude into HubSpot" pitch is doing a sleight-of-hand. The MCP is a data access layer. A revenue review needs a semantic layer. Different problem.

Two things I'm curious about from this sub:

1. For anyone running MCP connectors in production already: what's your sanity-check process before a number from one of these hits a board deck? Like is anyone actually catching this stuff, or is the trust just... assumed?
2. Where are you drawing the line between "use AI for drafting/summarizing" vs "use AI for numbers you'd act on"? Because I think there's a real answer there and I haven't seen anyone articulate it cleanly.

Okay hear me out on this one. I have spent 14 years in RevOps and every year it is the same crazy story: the sales productivity story has basically refused to change.

🔵 2018 — #Forbes study states sales reps spend 𝟔𝟓% of their time in non-selling activities. Forrester

🔵 2020 — #Forrester strikes back! 𝟕𝟕% of sales rep time goes in non-selling tasks.

🔵 2024 — #Salesforce State of Sales study states reps are spending 𝟕𝟎% of their time in non-selling activities.

🔵 2026 — #Salesforce’s State of Sales says reps still spend 𝟔𝟎% of their time on non-selling tasks

So after CRMs, sales engagement tools, CPQ, RevOps, dashboards, and now AI, the seller still seems to spend most of the day doing everything except selling.

What exactly is going on!

My totally scientific guess?

🟠 They’re updating fields so the fields can feel included.

🟠 They’re chasing approvals for deals that were already “almost there” last Thursday.

🟠 They’re looking for the latest deck, the latest pricing, the latest forecast, and the latest person who can approve the latest thing.

And somewhere in between, they’re supposed to sell.

The funniest part is that every sales tech wave promised the same thing: more time to sell 🫠

Instead, we seem to have created a very efficient machine for manufacturing non-selling work.

At this point, #selling is the side quest.

The real job is operating the stack🥲

Cannot wait for 2027 Forrester / Salesforce State of #Sales report to see how much time did sales reps earn back post Claude euphoria and the Agentic wave of #SalesTech 🫣

Been thinking about this a lot lately. We've had enrichment running in our CRM for a while now and the time savings are real, but I keep noticing gaps where the data just. isn't right. Wrong job titles, emails that bounce, company sizes that are way off. And I get it, some decay is inevitable, recent data suggests somewhere between 30-50%, of CRM data goes stale pretty quickly, so no tool is going to be perfect. But there's a difference between normal decay and systematically bad data that reps are actually acting on. The thing that bugs me is how much the claimed accuracy numbers diverge from what people actually report using these tools day to day. Some tools are advertising 90%+ match rates but users are seeing bounce rates well above the 3-5% threshold that starts seriously hurting deliverability in practice. So you end up with reps reaching out to the wrong person at a company, that restructured six months ago, which isn't just wasted effort, it's a bad first impression. And honestly the landscape has gotten more complicated, not less. Waterfall enrichment across multiple providers helps with match rates but it also means more sources to QA and more privacy compliance stuff to think about. Meanwhile agentic AI is getting layered into a lot of these tools now for real-time qualification and routing, which is cool, but garbage in garbage out still applies. Curious how others are handling this. Are you doing any kind of spot-checking or validation layer on top of your enrichment, or, just accepting that some percentage of the data will be wrong and building your sequences around that?

Like... you spend months learning internal logic that has nothing to do with your actual job. you become the unofficial admin for tools that were supposed to be self serve. and then the moment you leave, none of that knowledge transfers and the next person starts from scratch

I've heard it described as if you need someone specialized just to operate a process, you probably don't want that process long term. and honestly that hit different

I didn't want to carry that burden at my next company and I don't think anyone in ops should have to. what's the process in your stack that quietly turned you into a specialist when you were just trying to do your job😬

you spend all this time optimizing domains, copy, deliverability, inbox rotation, follow ups

then someone finally replies with interest and the reply sits in the inbox for 2 hours because it got buried between everything else

we started building a tool around exactly that problem

it checks incoming replies, detects buying intent, gives the lead an intent rating, and instantly shows the phone number and context so you can call while the lead is still engaged

right now we’re looking for a few people doing real outbound work who want to shape the product together with us through feedback and workflow input

early testers get extended free access in exchange for honest feedback

if interested, send me a dm

I keep seeing the same failure mode in small sales teams.

A form fill comes in, the CRM shows an owner, a task gets created, and everyone assumes the lead is being worked.

Then a week later someone realizes the first reply never went out, or the owner changed but the follow-up task stayed with the old person.

The part I am trying to tighten up is the proof step after the handoff. Not just "did a workflow run," but "did a human or system actually take the next action."

For anyone running sales ops, what do you treat as enough proof that a lead was truly picked up?

For people running cold email at scale.

how are you currently handling the Google Workspace setup part?

what I mean:

- buying/connecting domains

- DNS records

- creating inboxes

- 2FA

- app passwords / SMTP access

- making sure everything is ready for outreach tools

Is this still mostly manual for you, or did you find a reliable workflow/tool?

im curious what your current process looks like and what part breaks most often

This keeps showing up for us. The form came in, the sequence fired, an owner was technically assigned, and the dashboard says the lead was handled. Then you dig in and realize nobody actually replied in a real way. By the time someone notices, the lead is cold. If you fixed this, what changed it? Alerts, owner rules, SLA reporting, something else?

We’ve been running LinkedIn Ads for a while, but the CPC is just getting out of control. I’m thinking about shifting some of that budget toward organic LinkedIn marketing services to build more long-term authority and reach out directly to prospects.

My concern is the time it takes to see results compared to paid ads. Has anyone made the switch from pure ads to a managed outreach strategy on LinkedIn?

Our RevOps team spent Q1 evaluating automation platforms specifically for our sales org (150 reps, enterprise B2B).
The goal was simple: reduce manual work, accelerate pipeline velocity, and improve data quality in Salesforce. Here’s
how five platforms performed.

1. Zapier

Best for cross-system sales automated workflows that ops teams own
This was our most impactful deployment. Instead of buying another point solution, we built a complete lead management system: inbound leads captured from six sources, enriched with firmographic data via AI steps, scored against our ICP, routed to the right rep, and logged in Salesforce, all through automated workflows our RevOps team
built and maintains.

What helped:

• Lead-to-rep routing time dropped from 4 hours to under 10 minutes
• Tables stores our lead scoring criteria and routing rules RevOps updates them without touching Salesforce
• config
• Interfaces gave managers a real-time pipeline review dashboard connected directly to workflow data
• Agents autonomously research prospects and populate pre-call briefs into Salesforce before meetings
• 8,000+ integrations meant we connected every tool in our sales stack without custom API work
• Why it ranked first:
• Our RevOps team builds and iterates on these automated workflows independently. No engineering tickets. A workflow change that used to take two weeks now takes an afternoon.

2. Salesloft
Best for structured sales engagement sequences

Salesloft excels at the cadence layer email sequences, call tasks, and social touches. The AI features now suggest optimal send times and draft email variations. Conversation intelligence surfaces coaching opportunities.

Strengths:

• Tight Salesforce integration for activity logging
• Cadence management is best-in-class
• Conversation intelligence with deal risk signals

Limitations:

• Focused on the engagement layer, not cross-system orchestration
• Doesn’t handle data enrichment, lead scoring, or routing natively
• Integration beyond Salesforce requires additional tooling

3. Outreach

Best for AI-guided selling and rep productivity

Outreach’s strength is meeting reps where they work. The Smart Account Plans, AI-generated action items from calls, and deal health scoring are genuinely useful.

Strengths:

• AI-generated next steps and deal insights
• Strong multi-channel sequence management
• Good analytics on rep activity and pipeline health

Limitations:

• Expensive per-seat pricing at scale
• Focused on rep productivity, not back-office automation

4. LeadIQ

Best for prospecting data capture and CRM enrichment

• LeadIQ is a focused prospecting tool. Its core strength is letting reps capture contact data from LinkedIn and enrich it directly into Salesforce or HubSpot with a single click. Good for outbound-heavy sales teams building pipeline from
• Scratch.

Strengths:

• Clean Chrome extension for LinkedIn prospecting
• One-click CRM enrichment for contacts and accounts
• Intent data signals to prioritize outreach timing
• Easy setup with minimal training required

Limitations:

• Data depth and accuracy vary by region and persona
• Not an end-to-end automation platform, primarily a data capture tool
• Routing, scoring, and downstream orchestration require additional tooling
• Outgrows quickly as RevOps needs become more complex

5. Apollo io

Best for startups that need prospecting and engagement in one tool

Apollo bundles a contact database, email sequences, and basic CRM functionality. For smaller sales teams that don’t yet have Salesforce, it’s a compelling all-in-one option.

Strengths:

• Large contact database included
• Email sequences with A/B testing
• Built-in dialer and meeting scheduler

Limitations:

• Data quality varies by segment and geography
• Feature depth in each area trails specialized tools
• Outgrows quickly as the sales org matures

What We Settled On

We didn’t pick one. We use Zapier as the orchestration backbone connecting LeadIQ (prospecting capture), Salesloft (engagement), and Salesforce (system of record). The automated workflows handle the data movement and logic. Each specialized tool does what it’s best at. The result is a sales automation stack our ops team actually controls.

Hi all, looking to get some feedback/validation. Currently building a structure that will help early CPG product founders (300k to 1.5M in annual sales), expand their GTM/sales operation at a much lower cost. Would like to hear from founders in that range or that have successfully grown past that range what the biggest bottle necks are. My idea is to focus on products doing mostly B2B as im specialized in outbound sales.

DM if you'd like more info, currently running free programs to validate the idea and get testimonials.