If your Analytics disappeared tomorrow, would your product still deliver the same value?
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https://t.co/hWRx3gEsHS
A shift every product leader should be paying attention to. https://t.co/BqPeH9sNoT
#EmbeddedAnalytics#SaaSProducts#BIForISVs
One Thing Analytics Teaches Over Time:
Curious how other ISVs think about this as analytics adoption grows across customers and teams. https://t.co/mjlcGJBoum
Know more 👇
https://t.co/PuYExQSbeF
#EmbeddedBI#Analytics#ISV#BusinessIntelligence
The fastest way to expose a bad BI setup?
Put 4 different teams in the same dashboard.
Read more
https://t.co/RshT6s5rSP
#BusinessIntelligence#Analytics#ISV#SelfServeBI
https://t.co/HuwCZrBrTf
We’re curious about this because most customer dissatisfaction doesn’t show up dramatically.
It usually starts with small signals teams don’t take seriously early enough.
Vote below 👇
https://t.co/leVviH1j6Q
#SentimentAnalysis#CustomerInsights#ISV#Analytics#Poll
How do business users actually access predictions?
Through a dashboard?
A report?
A web service?
Inside an existing application?
Read more
https://t.co/k8S6CtytiI
#BusinessIntelligence#PMML#Analytics#ISV#EmbeddedBI#BIForISVs
https://t.co/J3bv792gkh
We tend to treat churn like an event.
But it’s really a slow drift.
Read more
https://t.co/jkX6mFfeCD
#CustomerSuccess#ISV#SaaSProduct#Analytics
If you’re rethinking how early your product can spot churn signals, this is a good place to start: https://t.co/wJhu5HL7dl
The problem with demand planning isn’t bad predictions. It’s that even good predictions don’t stay good for long.
Read more
https://t.co/8D0ofrWSE8
#DemandForecasting#ISVProducts#SupplyChain#Analytics
This gets into that idea in a practical way:
https://t.co/Y4deGzGYGQ