Tag Archives: data analytics

3 Weird Analytic Practices at Mode | Tayler Mehit


For many of Mode’s employees, this is their first job at an analytics company. Those team members often assume that Mode’s internal analytics processes mirror the way analysis is commonly conducted within other organizations. In some ways, that assumption holds true. As CEO Derek Steer puts it, “I wish I had a more mind-blowing story for how we do internal reporting… But mostly, it’s funnel analysis.” That said, we approach analysis from some uncommon angles.

Frequently, we begin an analysis with a one-off report, rather than setting out to build a big dashboard. Many of our most technically proficient internal users, who produce some of our best analysis, are on the Customer Success team. And reports that are built with one purpose often find extended lifespans as reusable tools. In this post, we’ll take a look at some of the uncommon analytics practices internally at Mode.

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The Data You Ignore Is More Valuable Than You Thought | Forbes.com

Business leaders understand the importance of data, but just because you’re checking analytics doesn’t mean you haven’t also overlooked some important metrics.The new world of data isn’t just about gathering new information; all kinds of data that your business collects effortlessly can provide enormous value if you can look at it the right way.Finding the needle in of your haystack of data sources can be a lot more difficult than it might seem. To explore the untapped wells of information that companies should be paying attention to, I recently sat down with Catherine Havasi, co-founder and CEO of Luminoso, one of the most advanced data analytics companies out there today

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Big Data, Small Bets | Forbes.com

Big data and small experiments—what could appear more seemingly incongruous?  Yet the truth is: these two trends, one from the world of analytics, the other from the world of innovation and change, can be powerfully combined to drive sustainable success in a highly uncertain world.

Big data is a product of the technology revolution that is now well into its third decade. Thirty years ago, sophisticated analytical techniques promising extraordinary insights were lacking but one thing: the data to inform them.  The promise was clear: if you simply start measuring and tracking everything, from minutely segmented sales and resource usage metrics to every conceivable macroeconomic variable of remote interest, we will be able to identify all manner of relationships, correlations and insights, the net result of which will be the capacity to much more effectively and efficiently allocate resources to take advantage of opportunity and drive results.

The message was received, loud and clear.  In fact, perhaps too loudly and clearly.

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