WHY IT MATTERS: Digital Transformation
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WHY IT MATTERS: Digital Transformation
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Curated by Farid Mheir
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What is good retention metric numbers? A panel of experts provides their value from Lenny's Newsletter @lennysan via @sebprovencher

What is good retention metric numbers? A panel of experts provides their value from Lenny's Newsletter @lennysan via @sebprovencher | WHY IT MATTERS: Digital Transformation | Scoop.it

If you take nothing else away from this post, it should be that retention matters. A lot. No other metric is as singularly telling of whether your business will thrive or die. And so, the better you understand what good retention looks like for your business, the better shot you have at the former. We hope this research proves useful to you whether you’re building, investing, or just curious.

Farid Mheir's insight:

WHY IT MATTERS: with every product moving to a SaaS, pay as you go, model, retention has become a key metric to consider. This post delivers insights into retention metrics for GOOD and GREAT retention numbers. I'd love to see similar posts on email open rates, ecommerce conversion, app usage, etc.

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Analysis 15,000 #startups funding shows 1 in 6 Gets Acquired - all other die via @Crunchbase

Analysis 15,000 #startups funding shows 1 in 6 Gets Acquired - all other die via @Crunchbase | WHY IT MATTERS: Digital Transformation | Scoop.it
Let’s say you randomly selected 1000 seed-stage startups based in the United States. How many of those would go on to raise a Series A? Of companies that go on to raise a Series A, how many would go on to raise a Series B? You could keep this process going until only
Farid Mheir's insight:

WHY THIS IS IMPORTANT

We say one company in a thousand makes it. This study provides hard facts that the numbers are more like 16%.

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How Does CB Insights Get Its Private Company Financing & Exit Data? Unveiling The Cruncher

How Does CB Insights Get Its Private Company Financing & Exit Data? Unveiling The Cruncher | WHY IT MATTERS: Digital Transformation | Scoop.it

The post is structured as follows:
How we collect our data
Why this data collection process versus others
What are our data sources?

 

Walking through the technology and process
Step 1 – The Life Event Classifier
Step 2 – Entity Recognition Engine
Step 3 – Relationship Extractor
Step 4 – The Clustering Engine
Step 5 – The Cruncher Admin

Farid Mheir's insight:

A very interesting explanation of the process that CBinsight uses to search, compile and structure the information on startups that it tracks. The paper is already 3 years old so I expect that reliance on manual work is less and AI automation is leveraged more today. Nonetheless a good read.

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