Your AI pilot worked. Your data didn't.
70% of enterprise AI initiatives stall before production, and bad data infrastructure is the first reason why.
bit.ly/4soawBg
#AIStrategy #DataQuality #EnterpriseAI
5 questions before approving any AI budget:
1. What data feeds this model — and when was it last audited?
2. What ONE metric defines success?
3. Who owns the outcome, by name?
4. What does failure look like at 90 days?
5. What changes if this works?
Most proposals can't answer all five. 🎯
#AI #En
Chrome extension discussions surged 2,300%. Linux-related AI conversations jumped 1,400%.
Enterprise users aren't waiting for platforms to solve integration. They're routing around the limitations themselves.
That shift changes vendor evaluation criteria entirely.
Report:
Google's AI sentiment score: –22.8%. The worst of any major platform.
OpenAI holds the most voice share (19.2%) but registers –9.98% sentiment. That's switching-cost inertia, not loyalty.
NVIDIA is the only major player in positive territory at +7.46%.
Full breakdown:
Most enterprise AI pilots nail the demo. Then they quietly die.
The failure isn't the model. It's the three structural gaps organizations skip before scaling.
Here's what they are. bit.ly/4soawBg
#AI #DigitalTransformation
Your MarTech measurement problem isn't the tools.
It's upstream. 🔍
Duplicate records. Inconsistent event tracking. Handoff gaps.
Fix the foundation. The reporting discrepancies usually fix themselves.
#MarTech #DataQuality
Pricing complaints outpace feature praise by 3.6:1 across AI subscription platforms right now.
If you're negotiating AI contracts in Q2, you have leverage. Vendors are showing flexibility they haven't offered before. The window is roughly 90 days.
Data: bit.ly/aiintelligen...
#AI #MarTech
New report: I analyzed 16,939 posts and 264,333 comments across 10 AI communities over 30 days.
The headline finding: engagement is at record levels while sentiment is deteriorating. That's not a market in retreat — it's a market in friction.
Full report (free): bit.ly/aiintelligen...
#AIStrategy
40,000-record B2B database. 18 months of accumulated contacts.
First pass:
❌ 34% duplicates
❌ 22% missing location data
❌ 600+ segmentation-breaking format errors
After CleanSmart: 26,400 clean records. Next campaign open rates up 31%.
Less is more when the less is accurate. 🧹
#DataQuality
Stages of analytics team effectiveness:
Beginner: "We have data"
Intermediate: "We're cleaning the data"
Advanced: "We trust the data"
Master: "We spend 80% on analysis, not prep"
Most teams live in stage two. Foundation is the difference.
#DataQuality #Analytics
The most expensive AI mistake in 2026?
Skipping the audit and going straight to the build. 🚩
29% duplicate rate in training data.
14-month roadmap.
Nobody had looked at the data.
The sequence matters as much as the strategy.
#AI #DataQuality
congrats on the new post at Antwerp btw! what's the catalogue looking like, mostly formatting issues or are there actual gaps in the records too?
The companies winning with AI in 2026?
Cleanest data.
Clearest strategy.
Courage to subtract before they add.
Clean your data. Simplify your stack. Build on a foundation that won't crack.
That's not a trend. That's a principle.
#AI #MarTech #DataQuality
Stages of data sabotage:
😬 Analysts clean more than analyze
📉 Campaigns feel like guesswork
🔀 Customer records don't match across systems
🤷 Nobody trusts the dashboards
⏳ Every new tool needs a "data project" first
3+ = foundation problem.
#DataQuality
An enterprise spent 8 months building an AI model.
Deployed it. Marketing shifted strategy.
Two weeks later: high-value customers misclassified. 😬
Root cause? 26% duplicate rate in training data.
Same algorithm + clean data = 3x better results.
#AI #DataQuality
The most successful enterprises aren't adding tools.
They're subtracting them. ✂️
We consolidated 1,200+ websites at Novartis into a unified platform.
52% cost reduction.
Sometimes innovation means simplifying.
#MarTech #Innovation
AI readiness assessment in 5 days:
📋 Day 1: Data inventory
🎯 Day 2: Use case stress test
🗣️ Day 3: Stakeholder interviews
🔍 Day 4: Gap analysis
🗺️ Day 5: 90-day action plan
Walked a healthcare client through this. They killed 3 projects. Fast-tracked 2.
#AI
CMOs spend ~25% of budget on MarTech.
Most can't answer: "Is it working?" 🤔
You don't need another dashboard.
You need 3 metrics, one source of truth, and the guts to kill the vanity numbers.
#MarTech #CMO
Don't build an AI strategy.
Build a data strategy. 🎯
Every AI conversation starts with "we have the data."
Every audit ends with "...not that data."
The gap is where pilots go to die.
#AI #DataQuality
Felt this deeply. Dirty data is a slow drain, not a one-time crisis, which is why it's so exhausting.
I work in this space (built a tool to help with exactly this), so happy to think through your specific situation if you want to share more about where the mess is coming from.
The best MarTech investment in 2026 costs $0.
It's a customer journey audit. 🗺️
Map what your customer experiences before you sign another SaaS contract.
Most enterprises can't. That's the problem.
#MarTech #CX
Stages of data maturity:
Beginner: "We have data"
Intermediate: "We have a lot of data"
Advanced: "We have clean data"
Master: "We have governed, unified, analysis-ready data"
Most companies are stuck between 1 and 2.
#DataQuality #DataStrategy
5 things that kill AI pilots:
❌ No data governance
❌ Vague use cases
❌ No change management plan
❌ Success defined after launch
❌ Committee ownership
Fix these BEFORE you touch the tech.
#AI #AIReadiness
Don't build a data lake.
Build a clean data lake. 🧹
Data teams spend 60-80% of their time cleaning instead of analyzing.
That's not a productivity issue. That's a structural failure.
#DataQuality #Analytics
Stages of AI readiness:
Beginner: "We need AI"
Intermediate: "We need clean data first"
Advanced: "We need one clear use case"
Master: "We need one owner, one metric, 90 days"
Most orgs never leave stage one.
#AI #DataStrategy
Not an auditing tool, this is the hard and tedious manual effort, because you are right relying on another tool could mean missing something.
Your MarTech stack isn't broken.
Your data is.
Stop buying new platforms and start auditing the 47 sources feeding garbage into every tool you own.
#MarTech #DataStrategy
February wrap: CleanSmart launched. First customers. Roadmap reshaped by feedback.
March: HubSpot integration. Team features. Saved templates.
Early adopters locked at current pricing before increases. 👇
#CleanSmart #BuildInPublic
Hardest part wasn't technical.
It was letting go of consulting income. Every coding hour wasn't a billing hour.
Watching pipeline dry up. Turning down easy money.
The "build in public" crowd doesn't show the spreadsheets.
#Founder #RealTalk
Month one lessons:
✅ Building in public drove signups
✅ Confidence scoring built trust
✅ Compliance teams = unexpected champions
❌ Should've talked to users earlier
❌ Over-built features nobody used
Learned more live than building.
#Startup