r/CRM

Every time I got a new lead it turned into chaos.

First I’m scrambling to add them to my CRM before I forget their info.

Then I’m rushing to Microsoft Word to build a proposal while the lead is still hot.

Export PDF.

Attach to email.

Write the message with ChatGPT,

then finally send it.

Then a few days later I realize I completely forgot to follow up.

I got tired of bouncing between 5 different tools just to close one client.

So I built Tympi.

Now I can add a contact, create a branded proposal, send it professionally, save everything, and set follow ups all in one place in under 60 seconds.

Oh and it’s free 😊

It started as a tool for myself because freelancing shouldn’t feel like administrative survival mode.

How many tools are you using for just these steps?

I'm developing a tool for CRM marketers and trying to understand where the real gaps are before creating something inappropriate.

What data do you most often search for in your industry that irritates you?

Are you willing to pay for a service that automates this search?

Or maybe just searching isn't enough and you'd like something else? I'd appreciate any feedback

I signed up for AnyMailFinder about 6 months ago and the accuracy has been pretty inconsistent. Some weeks I'll get maybe 70% valid emails, other weeks it drops to like 40-50%. The bounce rates are killing my sender rep.

The good: pricing is reasonable, UI is clean, and their chrome extension works well. CSV upload is uncomplicated.

The bad: no mobile numbers, limited filtering options, and the data seems stale. Found a bunch of people who left their companies months ago. Also no intent data or technographics which I really need for better targeting.

Hunter has been more reliable for me accuracy-wise but it's pricier. I've also been looking at UpLead and Prospeo since I keep seeing them mentioned for b2b email verification and better data quality. Prospeo in particular seems interesting because people say the bounce rates are way lower and they have mobile numbers too.

Curious if anyone else has compared these email finder tools or found something better for b2b contact data?

I've been in infrastructure design/support for decades, most in a hands-on manager role. Recently my wife needed personal time so I started managing her small business full time, we own a massage therapy clinic with 25 employees. Reception is paid $20+ and therapists paid commission. For me it is keeping the schedule busy and costs down. Mailchimp, Social Media - recently setup voip ms , and now i get transcribed conversations that feed an automated follow up text funnel for people who call and say they are going to call back but don't. It also sends miss you texts to our therapist's regular clients that haven't booked in 6 months. Using AI to build all the API calls and the database (and reception tools like a confirmation webpage) has been so much fun. I'm now setting up a smart booking system for people who don't want to talk to reception to book but don't want to go through the website either. I set something similar up for my sister who is a real estate agent - first a way to screen her calls and call back hot leads and sending the rest to the same smart booking to schedule a meeting with her. Also sends her a call sheet.

Before I go any further, I assume paying for a developer is coming down in price for small businesses like this but I assume they are still not a target audience. Is anyone doing? Is this crazy to even try unless I'm still just testing if I really want to do more than a few setups for friends and family? Could this be a business and is anyone else doing it? Thanks in advance.

Background context: We are a printing business mainly my father dealt business since last 40 years. we mainly do wedding invitations and other custom printing for individual customers.

We are dealing in shop visiting customers and we also run ads on instagram facebook whatsapp and tiktok. the customer lands in our chat and we deal them manually through chat and they place order where maybe some advance amount is paid and we fulfill order and take remaining balance.

Now the issues i am facing are related to check which ad is working better and where i am lacking to close the deals and since mostly deals are closed on chats which CRM is better for my process.

Thanks for the guidance.

hey all - been a reader of r/CRM for a while, but wanted to get more active so thought it would be cool to do a series where we roast the crap out of a CRM.

goal is to create a mega thread for anyone deciding whether or not to use a certain CRM. it can highlight the positive aspects of the CRM, but primarily looking to poke as many holes as possible so folks know what they're getting into.

since Attio is a big newer player, figured we could start with them. so here it is.

ATTIO ROAST

• What is it the worst at
• What is frustrating
• What do you wish could be better
• What do most other CRMs have that they don't
• What is the main reason you didn't choose it?
• What is the main reason you regret choosing it?
• What is the main reason you stopped using it?

lets goooooo

Hey r/CRM, I'm a founder who's spent the past two years deep in the relationship intelligence space. I've talked to 100+ VCs, BD directors, accelerator operators, angel investors, and ecosystem builders about how they manage professional relationships.

I came into this respecting CRMs. I still do, for what they were designed to do. But I've come to believe the CRM model has a foundational problem that no amount of AI features, integrations, or workflow automations will fix. And I want to make the case for why, and hear where this community thinks I'm wrong.

The 1990s assumption

Every CRM, HubSpot, Salesforce, Pipedrive, Close, all of them, is built on the same underlying model: a relationship is a record you create, a row you maintain, a contact you update. The architecture assumes that managing relationships means writing things down and organising them into pipelines.

That made sense in the 1990s when the alternative was a Rolodex and a notebook.

But here's what I keep seeing: records decay. You enter a contact, tag them, maybe log a note. Six months later, the record is stale and hard to maintain. The context from your last three conversations lives in your email, your calendar, your meeting notes, and your head, not in the CRM. The record tells you someone exists. It doesn't tell you who they are now, what you last discussed, who introduced you, what changed in their world, or whether there's a reason to reach out today.

Every professional I interviewed had tried using a CRM for personal relationship management. Every single one stopped within weeks. Not because the CRM was bad software, but because the model doesn't fit the problem.

Records decay. Memory compounds.

The difference matters. A record is static. It captures a snapshot and immediately starts going stale. Memory is dynamic; it accumulates context across every interaction, across every channel, and becomes more useful over time.

When a VC partner told us, "the bane of my existence is having to do things the computer should do for me," he wasn't asking for a better CRM. He was describing the absence of memory. He wanted a system that remembered what he discussed with someone six months ago, who introduced them, what they're working on now, and whether the timing is right to reconnect, without him manually logging any of it.

An angel investor spends 15–20 hours a week on relationship admin across 200+ active relationships. He's tried three CRMs. None reduced that number because the work isn't data entry, it's context maintenance. And CRMs don't maintain context. They store records and wait for you to update them.

An open innovation lead described having hundreds of conversations a month, with "a lot of learnings which somehow get a bit lost." He had a CRM. The CRM didn't help because the context lived across LinkedIn, email, calendar, meeting transcripts, WhatsApp, and his own head. The CRM captured maybe 10% of it, and only what he manually entered.

Where I think the model breaks

CRMs were designed for sales funnels. The core data model is: contact → opportunity → pipeline stage → close. That's a transaction engine. It works brilliantly for tracking deals.

But professional relationships aren't transactions. They don't have stages. They don't close. They compound, go dormant, resurface in unexpected ways, and evolve over years. The person who wasn't relevant to your work last year might be the perfect warm introduction this quarter. The context from a coffee chat in 2023 might be the reason a deal closes in 2026.

No CRM captures that. Not because they're badly built, because they're built for a different problem.

The case for NRM: Network Relationship Memory

I've started thinking about this as a fundamentally different category from CRM. Not an add-on, not an AI layer on top of a CRM, but a different architecture entirely, one built for human networks instead of sales funnels.

What I mean by Network Relationship Memory:

• Memory, not records. Context accumulates automatically across every touchpoint — email, calendar, LinkedIn, meeting transcripts, notes — without manual input. The system remembers so you don't have to.
• Networks, not pipelines. Relationships exist in webs, not funnels. Your network has structure — clusters, warm paths, mutual connections, shared context — and the system should reason about that structure, not flatten it into rows.
• Signals, not updates. Instead of you updating records, the system monitors what's changing in your network — job moves, company news, engagement patterns — and surfaces what's relevant to you right now.
• Compounding, not decaying. Every interaction makes the system smarter. The more you use it, the deeper the memory, the better the recommendations, the warmer the paths. The opposite of a CRM where records go stale the moment you stop manually updating them.
• Network sharing. Every new person that joins your team brings with them a network and set of professional relationships your business doesn't know how to mobilise. Providing mechanisms to share this securely across trusted partners allows for a company or business to see where the trust lies, who can open doors to new markets and what their collective business network looks like.

Where I might be wrong

I want to be honest about this: I'm building in this space, so I have an obvious bias. It's possible that the CRM model isn't the problem; maybe it's just a configuration and discipline problem. Maybe the right CRM with the right integrations and the right workflow automations does everything I'm describing.

But after 100+ conversations with people whose careers depend on relationships, I haven't found a single person who's made that work. Not one.

What I want to hear from this community:

• Am I wrong about the model? Has anyone here successfully used a CRM for ongoing relationship management (not deal tracking)? What did the setup look like?
• Does the NRM framing resonate? Or does it sound like a CRM with extra steps?
• For people managing large professional networks — what's your actual system? And does any part of it feel like "memory" vs. "records"?
• Do you think AI will fix the CRM model or is the underlying architecture the constraint?

I'm not here to sell anything. I'm here because this community understands relationship management tools better than anyone, and I want to stress-test this thinking. Genuinely curious where the pushback is.

Everyone says building a CRM is a massive technical challenge. I’ve never really understood why.

Strip it down. It’s essentially a UI on top of a relational database. You have contacts, companies, deals, and custom schemas. That is standard CRUD.

I get that email and calendar sync is a nightmare. Microsoft and Google APIs are a mess. But what else is there?

I’m asking transparently because I'm building RootCX (github.com/RootCX/RootCX). It’s an open-source platform for creating ambitious internal tools with built-in enterprise governance.

I'm trying to figure out if factoring this "CRM complexity" into our core engine, so teams can build custom CRMs effortlessly, is actually a viable bet. Or am I completely underestimating the problem?

What are the hidden dragons? I'd love a comprehensive list.

Hey everyone,

I’m a young adult currently trying to build an online business, and I decided to go into freelancing in the CRM implementation / AI integration space. Right now, I’m mainly interested in working with small to medium-sized B2B companies in the DACH region.

I recently completed 4 different HubSpot certifications, and now I’m trying to figure out how you actually start and grow a freelancing business in this field. I’d really like to learn more about things like:

- what skills and topics I should continue learning
- how to acquire clients
- what services people actually sell to companies
- how projects are structured and delivered
- pricing, positioning, outreach, and everything around building a client base

If anyone here is doing something similar, works in CRM consulting, automation, RevOps, AI integrations, or freelancing in general, I’d honestly love to connect and DM. I have a lot of questions and would really appreciate talking to someone with experience in the space.

Thanks a lot!

I’m evaluating crm platforms with built-in AI capabilities and have researched attio, salesforce, hubspot, and sparrowcrm. Right now, I’ve narrowed it down to attio because its AI features will fit our need. I’m planning to start with the Plus plan for a 27-member team, and my main concern is as the team grows, will attio remain budget-friendly, or could it become expensive over time like hubspot?

With my team we've been doing outreach manually for months. It worked until it didn't. So decided it was time to actually invest in proper tooling.

Booked demos with the names that keep coming up in every "best sales tools" list. Cleared my calendar. Took notes.

The pattern was the same every time. Beautiful product, clearly built for a 50-person sales org with dedicated ops support. One of them spent 20 minutes explaining their AI forecasting module before asking what our current CRM was. When I said we were mostly using spreadsheets they visibly recalibrated.

Nobody listed pricing on their website. When the numbers finally came out (always on the second or third call, never the first) they ranged from uncomfortable to genuinely absurd for a small team. One of them quoted us an onboarding fee that was more than our monthly revenue at the time.

The thing is, what we actually needed wasn't complicated. A clean way to build targeted lists, a sending setup that doesn't burn our domain, some basic tracking to know what's working. That's it.

Apollo handles the prospecting and verification. Instantly manages the sending and warmup. Clay for the enrichment when we need something more specific. HubSpot free tier to keep track of conversations without losing context. Four tools, one afternoon to set up, fraction of the cost.

Six weeks in, reply rates are decent, pipeline is moving, and nobody had to sit through a 90-minute onboarding call to get started.

Why is the gap between what small teams need and what the market sells them so consistently enormous?

I was reviewing our CRM recently and realized we had hundreds of old leads that never really got followed up with properly. Some were assigned and forgotten, others got one generic email months ago and that was it. I’m curious how teams are handling this at scale. Are people automating re-engagement somehow, or is this still mostly manual cleanup work?

We’re currently on Bullhron and looking at moving CRM/ATS. At the moment we’re between Loxo and Atlas.

Demos always look great, but we’ve been burned before and would love honest feedback from anyone actually using either day to day.

Main things for us are reporting, workflows/processes, recruiter adoption and support.

Any regrets or things you only discovered after implementation?

I’m the head of partnerships at a mid-market B2B SaaS. Right now I’m managing 30+ referral agencies and losing my mind over how to track these relationships in a CRM. Partnership pipelines fundamentally don’t fit into sales CRMs. Surely I’m not the only person who sees this?!

Each partner relationship has a revenue share structure (these are not uniform), contract dates, referral volume tracking, relationship health signals, and payout history. Our CRM is built around deals. Deals have stages, a close date, and an amount. That’s it. This makes zero sense for an ongoing partnership that has variable monthly revenue.

I’m basically managing my partner ecosystem in a spreadsheet with conditional formatting. It’s ridiculous. What I need is a CRM with flexible data modeling. I want to define my own objects and fields and create custom relationship types. I want it to create a payout schedule that auto-calculates amounts based on the rev share terms I define.

It’s possible I can get closer to what I need with Airtable but then I’m rebuilding reporting from scratch. And it still doesn’t integrate cleanly with where my deal data is housed.

Please tell me there is an easier way to do this. Do I just have to manually build something?

I’ve seen companies choose one purely because it’s "popular" and then struggle later with scaling, security requirements, customization limits, or maintenance costs.

From what I’ve observed:

Cloud CRM works well when:

• Teams are remote/hybrid
• Fast deployment matters
• You want lower upfront infrastructure costs
• Frequent updates/integrations are important
• Scalability is a priority

But at the same time…

On-premise CRM still makes sense for some businesses, especially when:

• Data control/compliance is critical
• Internal IT teams are strong
• Deep customization is required
• Companies operate in highly regulated industries

What’s interesting is that many businesses don’t actually fail because of the CRM itself — they fail because the deployment model doesn’t match their operational needs.

Curious how others here see it:

If you had to choose today for a growing business, would you still go cloud-first, or do you think on-prem CRM still has strong advantages in 2026?

Hello,

I am new to this field and as the title suggest, I am looking for some pointers for the latest AI tools that can be integrated with Salesforce CRM Analytics to provide better user experience.

Please provide any recommendations or suggestions including high level implementation or pointers for that including the licensing cost etc.

Thank you and appreciate your help and support!

I need a CRM for my hvac company and was recommended ServiceJan from a friend that uses it for his furniture repair company and wanted to see what others think of it and if it would work for my business and potentially be an upside.

Lately I’ve been thinking about how much ChatGPT changed user expectations around software.

You type what you want.
It understands context.
It reasons.
It takes action.

But then you open most CRM/FSM/operations software and it’s still:

• dashboards
• filters
• forms
• tabs
• manual workflows
• endless clicking

So I’m curious:

Has anyone here found software that actually feels conversational and agent-driven instead of just “AI-powered” as a feature?

Something where you can genuinely say:

• “reschedule tomorrow’s jobs”
• “follow up with overdue estimates”
• “assign the nearest available tech”
• “handle after-hours calls”

…and the system actually understands and executes it.

Feels like business software UX hasn’t caught up to where AI is heading yet.

sales forecasting has been such a pain lately. weve got all this data, but manually calculating forecasts is taking forever and its never 100% accurate. theres gotta be a way to automate this and save time.

i need something that pulls all the data together and gives us real time insights based on buyer activity and past sales. basically, i want a tool that does the heavy lifting and gives us reliable forecasts without the stress.

anyone got any recommendations for a tool that can automate sales forecasts without making it feel like extra work?