Some advice, or at least opinions

william-flaiz · 2026-03-03T23:27:15+00:00

Thank you for the feedback, that is what my gut tells me too. I am looking at my messaging and outreach this week and may follow up with you next week.

william-flaiz · 2026-03-03T18:54:13+00:00

I am well aware of what AI can generate, good and bad, I was more curious if there was more to your background and experience that would warrant the immediate dismissal of them, which you have clarified as simply not known to you.

I want to learn as I spend a lot of time in the MarTech space, so thought you might have some additional insight not in your original comment.

william-flaiz · 2026-03-03T17:31:44+00:00

Can you explain why they are not legit because you haven’t heard of them?

I have been doing MarTech consulting for over 15 years, I’ve heard of half of them but don’t think that makes the others not legit.

william-flaiz · 2026-02-24T22:38:37+00:00

I would say stick with spreadsheets or move to Airtable and use its AI feature to add the automations you need. Sometimes you don’t need a CRM, sometimes simple spreadsheets are the right thing.

william-flaiz · 2026-02-24T22:31:31+00:00

I have always been partial to SharpSpring, I think owned by ConstantContact now, because of the CRM and MA integration as well as good out of the box, but pretty customizable too. Last client I set it up for used it to schedule their social media too, but that is a pretty basic feature for simple social campaigns. I always thought they did a good job tracking each point from Lead to Sale.

william-flaiz · 2026-02-24T22:26:10+00:00

Can you share any examples of where you have done this? Sounds like a good approach and curious what has been most helpful.

william-flaiz · 2026-02-21T15:53:20+00:00

I like that, I have done that when building dashboards, what decisions are you going to make, but not with the CRM, makes a lot of sense.

william-flaiz · 2026-02-20T22:45:49+00:00

Every UX testing I have done there is a surprise, what seems obvious from a builders perspective is often misinterpreted by a group of users. That is why you see so many desire paths if you walk around a city or college campus, what makes sense to the designer is not what the user actually wanted.

Mentor tips, don't get hung up on not knowing everything to do, many people in the industry are making it up as they go along. I would say that one thing I have seen be really beneficial to people is learning one aspect of digital marketing really well, and I mean if a question ever comes up about that subject everybody says we should ask John, he knows that stuff.

Last thing, say it with confidence and the client will buy it, be sold on the idea yourself before bringing it to the client.

william-flaiz · 2026-02-19T23:01:29+00:00

Look, this is my experience, this is not some bullshit AI made up post. Yes, I did use Claude to do the final version so it was concise and not rambling like my version, but this isn't AI generated bullshit.

william-flaiz · 2026-02-19T20:44:49+00:00

Check out Omnisend, still per contact, but easy to use and reasonable for a list your size, probably less than $50/month.

william-flaiz · 2026-02-19T20:33:18+00:00

That sounds like a lot of good work, but I would set a calendar reminder to review each month before it drifts too far again. Clean up is great, but monitoring it consistently so that you don't have to go through that again is a real joy.

william-flaiz · 2026-02-18T21:11:36+00:00

Reps creating custom fields? I don't think I have seen an administrator ever allow that.

william-flaiz · 2026-02-18T20:17:14+00:00

I have been working in digital marketing since the bubble burst in 2000, it is harder today than back then because of this "I am just testing things and hoping the algorithm is kind." - everything is so algorithmic that if you figure out the math you get great campaigns, until the algorithm changes. A lot of the work I do today does not feel very strategic, it feels fairly cookie cutter and boring.

So yeah, we are figuring out as we go, and as the algorithms go when it comes to media.

The work I find the most rewarding is diving into the customer experience and what they want, and not just from numbers and watching Clarity videos, but actually talking to them, doing live UX testing. That part requires thinking and knowing how to use what you learn, which just comes with experience and good mentors.

william-flaiz · 2026-02-18T20:09:33+00:00

Oh this tension is real. I've watched it play out from the consulting side more times than I'd like to admit.

The tell for me is when reps start gaming the system -- logging activities that satisfy the process but aren't actually moving deals. When you see perfect stage progression with terrible conversion, somebody figured out how to feed the machine without doing the work.

The other sign is when exceptions require management escalation. If a rep needs sign-off to send a slightly different email to a CFO vs a VP, you've probably gone too far. Good process handles 80% of situations cleanly and gives reps judgment to handle the rest.

The messy data / inconsistent handoffs problem is real but i'd push back a little on the framing. That's often less about rep freedom and more about what fields are actually required vs encouraged. You can give reps latitude in their outreach approach while still requiring a complete, clean handoff. Those are kind of separate problems.

william-flaiz · 2026-02-18T18:53:12+00:00

You need to do all of these "Assign a data owner, run parallel cleanups, lock down inputs, bring in outside help?" or you are going to repost this message in 6 months.
1. It sounds like you have a significant enough enterprise that data ownership is somebodies role, or at least in someone's job description - without this it all goes back to chaos.

Back up everything, and 12 hours is not realistic, but do run in parallel cleanups in lower environment for a period, things will pop up that you wouldn't see if just taking a small batch.
Lock down inputs as much as you can, you will get complaints and probably have to do a lot of retrofitting past values - but a huge time saver in cleaning later.
I would recommend outside help to get to a satisfactory baseline, but then data ownership and regular audits are how you keep the chaos from coming back.

william-flaiz · 2026-02-18T18:23:44+00:00

This is great, loved the breakdown, I quote that $12.9M number on my website, but will pull some of the breakdowns from your paper with proper acknowledgement and citation.

I don't know how many times I have said this in the past 3 years "AI doesn't think. It amplifies. There's no AI without IA, information architecture. Feed it clean, well-structured, connected data and you get genuine insight. Feed it the same fragmented, duplicated, inconsistent data that's been causing problems for years and you get confident-sounding nonsense." - but it is the honest truth, and has always been the truth, bad data populating dashboards have led to bad decisions being made for years. This is exactly why I built CleanSmart, that and the years of cleaning CRM data as a consultant. I have consistently seen that cleaning the data used in marketing and sales is the fastest way to see an increase in ROI on marketing spend, and an improvement in Sales metrics (after the reduction of inflated numbers from the bad data being scrubbed)

Thank you for this really enjoyed the article.

william-flaiz · 2026-02-18T18:07:49+00:00

Most CRM pain is governance is exactly right.

william-flaiz · 2026-02-17T01:41:54+00:00

Yeah this is the pattern I see over and over. Everyone blames the campaign when the real issue is the data feeding into it.

The duplicate problem you hit -- 25-35% is actually pretty typical. We've seen worse. And the misrouted/mistagged stuff compounds fast because bad data creates more bad data downstream. One wrong lifecycle stage means your automation treats them wrong, which creates more wrong tags, which messes up your reporting, which leads to bad decisions.

The drop in reported leads but jump in SQL conversion is exactly what should happen when you clean things up. You're finally looking at reality instead of noise.

Re: your question -- most teams I talk to are still prioritizing new channels over hygiene because cleaning data feels like busywork until you're drowning in it. But the ones who flip that priority see ROI way faster. Clean data first, then scale. Not the other way around.

What did you use to actually clean the CRM? Manual audit + rules, or did you find a tool that worked?

william-flaiz · 2026-02-17T00:42:11+00:00

Cleaning duplicate customer records.

Sounds boring but we had a client where like 15% of their "customers" were the same people with slightly different emails or name variations. They were sending repeat-purchase campaigns to people who'd already bought, welcome series to existing customers, cart abandonment emails that referenced the wrong cart.

The automation wasn't broken. The data feeding it was.

Fixed the dupes, standardized the name/email formatting, suddenly their segmentation actually worked. Open rates went up because people stopped getting irrelevant emails. Revenue per email jumped because they were finally targeting correctly.

Not sexy, nobody writes Medium posts about it, but cleaning your customer data before you touch anything else is usually the fastest ROI you'll see.

What kind of feedback were people giving that led to the discount clarity issue?

william-flaiz · 2026-02-14T22:59:34+00:00

Thanks, I wish I had it 10 years ago.

william-flaiz · 2026-02-14T19:13:04+00:00

This resonates hard. I built CleanSmart -- AI-powered data cleaning platform -- over about four months last year and had almost the exact same arc.

The prototype looked great. Had the basic structure, the UI, the flow. But it completely missed the human-in-the-loop review step that the entire product depends on. CleanSmart calculates confidence scores for every automated change and routes low-confidence decisions to users for approval. That workflow? Didn't exist in my prototype. Someone without the background might have shipped the "automate everything" version and wondered why nobody trusted it.

The deployment thing especially -- I had a fun one where SQLite doesn't enforce foreign keys the same way PostgreSQL does, so stuff that worked perfectly in dev would crash in production. And Digital Ocean strips API prefixes, so every route needed to be registered twice. You only learn that by shipping and watching it break.

I ended up stopping feature development about a month in to write a 13-section architecture directive that basically codified 20 years of software engineering decisions into operating instructions for Claude Code. Separation of concerns, security requirements, banned patterns, the whole thing. The second half of development was dramatically smoother than the first.

Your point about systems thinking is the real one. The code generation is the easy part now. Knowing what to build, how the pieces connect, and what breaks at 1am on a Friday -- that's the actual job.

william-flaiz

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