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PIVOTAL CLOUD FOUNDRY
The Stoplights Metrics Dashboard for Cloud Foundry: Go or No Go

Pivotal’s Cloud Ops team provide production operation support for Pivotal Web Services, which offers Pivotal Cloud Foundry as a hosted solution. Our responsibilities include deploying releases and providing break-fix support. Monitoring the health of the system is a critical part of this process. We rely on our “stoplights” dashboard to give us a quick go/no-go look at the operational status of Pivotal Web Services (PWS).

LABS
How to use Analytics.js to fix your analytics code and achieve metrics nirvana

There are so many great analytics tools out there that it’s often hard to know what to use. What’s more, each one comes with its own flavor of JavaScript API that’s slightly different from all the rest, meaning each new one you choose to add, even if you’re not sure it’s right for you, is a ton of work to implement.

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LABS
Success Metrics for Lean Startups and New Products

So, you’ve launched your MVP… congratulations! That’s a huge achievement, but don’t kid yourself – your v1 product is almost certainly not ready to scale into a real business. MVPs are, by definition, the minimal feature set you need to start learning with real users, and the speed at which you’re able to learn and act on those learnings will mean all the difference between success and failure.

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LABS
No Driving on the Shoulder

(it seemed appropriate to have a cheesy marketing image here)

Keeping your Boss[es]’ Ideas in the Right Lane

I’ve been talking with a lot of Product Managers making the transition to adopting agile methodologies.  An interesting theme has emerged that I wanted to address.  

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LABS
A user metric is a terrible thing to waste

When it comes to user metrics, what should you log when you don’t know what to log?

Everything.

When you’re first getting an MVP site off the ground, you don’t know quite what you might want to track.  And might not have time to think about it.

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LABS
[Metrics] A/B Testing, Feature Flipping and going too far

A/B testing is probably not worth your time.  When you start hooking metrics up to your product, the feedback is addictive.  All of a sudden you’ve got lots of actionable data and you’re tacking validation goals onto feature stories.  This is great, but I implore you to not take it too far.

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LABS
[Metrics] Do you need that feature?

The hardest part of product management is deciding which features NOT to build, especially when they seem like great ideas.  When you have a product in the market (or are getting it out there), you want to spend your engineering team’s time delivering value to your customers.  

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LABS
Always be validating

Big companies with well established products and business practices often differ from smaller, younger, start-up companies with the cash flow available to prove business ideas. The startup companies will often have a “runway” or “burn-rate”, meaning they have a limited amount of cash to keep the lights on.

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LABS
[Metrics] It's so hard to say goodbye

When you release early and often, you’re bound to churn through new customers. I showed you in my last post how to measure the funnel of trial to activation to engagement, but what should you do with all the people that didn’t make it?  

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LABS
[Metrics] Plug your Funnel

Once you’ve launched a product, “metrics” can be a powerful tool in measuring engagement and product issues.  From the engineering side, devs have a hard time believing if a metric is valid or misleading.  From the biz dev/marketing side, it’s hard to understand the technology enough to know what kinds of questions can be asked.  

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