cleansmartlabs.com
Start a free trial of CleanSmart today → https://bit.ly/cs-free-trial
CleanSmart handles it in minutes. ✨
Beta's open, free trial: bit.ly/cs-free-trial
#DataOps #Spreadsheets #Productivity #SaaS
"Mike Johnson" and "Michael Johnson" at the same company = same person getting your email twice. Awkward. 😬
CleanSmart finds them. Free beta: bit.ly/cs-free-trial
#EmailMarketing #MarketingTips #DataCleaning #
"Mike Johnson" and "Michael Johnson" at the same company = same person getting your email twice. Awkward. 😬
CleanSmart finds them. Free beta: bit.ly/cs-free-trial
#EmailMarketing #MarketingTips #DataCleaning #
(555) 123-4567
555.123.4567
5551234567
+1-555-123-4567
555 123 4567
CleanSmart standardizes all of them automatically. One click. ☝️
Free beta: bit.ly/cs-free-trial
#DataStandardization #ContactData #DataQuality #Automation
(555) 123-4567
555.123.4567
5551234567
+1-555-123-4567
555 123 4567
CleanSmart standardizes all of them automatically. One click. ☝️
Free beta: bit.ly/cs-free-trial
#DataStandardization #ContactData #DataQuality #Automation
The rest? "Jon Smith at Acme Corp" and "Jonathan Smith at ACME Corporation" sitting in your CRM as two separate people.
Wrote a practical guide to unifying Shopify + Salesforce + HubSpot data: bit.ly/3LcTIhm
#RevOps #SalesOps #DataQuality
The rest? "Jon Smith at Acme Corp" and "Jonathan Smith at ACME Corporation" sitting in your CRM as two separate people.
Wrote a practical guide to unifying Shopify + Salesforce + HubSpot data: bit.ly/3LcTIhm
#RevOps #SalesOps #DataQuality
This is why I built CleanSmart. Upload messy data, get clean data back. No code, no formulas, no crying. 😌
Try the beta free: bit.ly/cs-free-trial
#CRM #SalesOps #DataIntegration #BuildInPublic
This is why I built CleanSmart. Upload messy data, get clean data back. No code, no formulas, no crying. 😌
Try the beta free: bit.ly/cs-free-trial
#CRM #SalesOps #DataIntegration #BuildInPublic
There's no universal standard for phone numbers because every country has different rules.
US: 10 digits, area code optional parentheses
UK: Variable length, starts with 0 domestically
Germany: Variable length, city codes vary
This is why automation matters.
There's no universal standard for phone numbers because every country has different rules.
US: 10 digits, area code optional parentheses
UK: Variable length, starts with 0 domestically
Germany: Variable length, city codes vary
This is why automation matters.
CleanSmart cleans it in minutes. Duplicates, bad formatting, missing data—all of it. ✅
Beta's free: bit.ly/cs-free-trial
#Marketing #DataCleaning #MarketingOps #StartupLife
CleanSmart cleans it in minutes. Duplicates, bad formatting, missing data—all of it. ✅
Beta's free: bit.ly/cs-free-trial
#Marketing #DataCleaning #MarketingOps #StartupLife
→ Emails bouncing
→ Same lead called twice
→ Reports that lie to you
CleanSmart catches what CTRL+F can't. Semantic AI that knows "Jon" and "John" might be the same person. 🧠
Free beta: bit.ly/cs-free-trial
#DataQuality #RevOps #EmailMarketing #AI
→ Emails bouncing
→ Same lead called twice
→ Reports that lie to you
CleanSmart catches what CTRL+F can't. Semantic AI that knows "Jon" and "John" might be the same person. 🧠
Free beta: bit.ly/cs-free-trial
#DataQuality #RevOps #EmailMarketing #AI
CleanSmart handles it in minutes. ✨
Beta's open, free trial: bit.ly/cs-free-trial
#DataOps #Spreadsheets #Productivity #SaaS
CleanSmart handles it in minutes. ✨
Beta's open, free trial: bit.ly/cs-free-trial
#DataOps #Spreadsheets #Productivity #SaaS
Built CleanSmart so nobody has to do this anymore. AI finds duplicates humans miss, fixes formatting, fills gaps.
Free beta: bit.ly/cs-free-trial
Built CleanSmart so nobody has to do this anymore. AI finds duplicates humans miss, fixes formatting, fills gaps.
Free beta: bit.ly/cs-free-trial
It's not finding the obvious duplicates. Most tools handle ""John Smith"" appearing twice.
It's finding ""John Smith"" and ""J. Smith"" at the same company, entered from different sources 6 months apart.
That requires understanding context, not just match
It's not finding the obvious duplicates. Most tools handle ""John Smith"" appearing twice.
It's finding ""John Smith"" and ""J. Smith"" at the same company, entered from different sources 6 months apart.
That requires understanding context, not just match
We're building AI-powered data cleaning tools—duplicate detection, format standardization, the stuff that usually eats hours of your week.
Currently in beta. Excited to share what we're learning here.
We're building AI-powered data cleaning tools—duplicate detection, format standardization, the stuff that usually eats hours of your week.
Currently in beta. Excited to share what we're learning here.