Remove 2011 Remove Experimentation Remove Metrics Remove Optimization
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The Lean Analytics Cycle: Metrics > Hypothesis > Experiment > Act

Occam's Razor

To win in business you need to follow this process: Metrics > Hypothesis > Experiment > Act. We are far too enamored with data collection and reporting the standard metrics we love because others love them because someone else said they were nice so many years ago. That metric is tied to a KPI.

Metrics 156
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When models are everywhere

O'Reilly on Data

It predates recommendation engines, social media, engagement metrics, and the recent explosion of AI, but not by much. The Entertainment” is not the result of algorithms, business incentives and product managers optimizing for engagement metrics. YOUTUBE, CONSPIRACY, AND OPTIMIZATION. In a long-term sense, definitely not.

Modeling 190
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Search: Not Provided: What Remains, Keyword Data Options, the Future

Occam's Razor

In late 2011, Google announced an effort to make search behavior more secure. As an analyst, I was upset that this change would hurt my ability to analyze the effectiveness of my beloved search engine optimization (SEO) efforts – which are really all about finding the right users using optimal content strategies.

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Experiment design and modeling for long-term studies in ads

The Unofficial Google Data Science Blog

Nevertheless, A/B testing has challenges and blind spots, such as: the difficulty of identifying suitable metrics that give "works well" a measurable meaning. This is essentially the same as finding a truly useful objective to optimize. accounting for effects "orthogonal" to the randomization used in experimentation.

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Unintentional data

The Unofficial Google Data Science Blog

With more features come more potential post hoc hypotheses about what is driving metrics of interest, and more opportunity for exploratory analysis. We data scientists now have access to tools that allow us to run a large numbers of experiments, and then to slice experimental populations by any combination of dimensions collected.

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How To Suck At Social Media: An Indispensable Guide For Businesses

Occam's Razor

Success Metrics. In my Oct 2011 post, Best Social Media Metrics , I'd created four metrics to quantify this value. I believe the best way to measure success is to measure the above four metrics (actual interaction/action/outcome). It can be a brand metric, say Likelihood to Recommend. Business Leaders.

B2B 167
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Deep Learning Illustrated: Building Natural Language Processing Models

Domino Data Lab

You can home in on an optimal value by specifying, say, 32 dimensions and varying this value by powers of 2. If we were using CBOW, then a window size of 5 (for a total of 10 context words) could be near the optimal value. Note: Maas, A., Learning word vectors for sentiment analysis. As summarized in Table 11.1, 0.85 = 0.15.