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Brand Measurement: Analytics & Metrics for Branding Campaigns

Occam's Razor

One of the ultimate excuses for not measuring impact of Marketing campaigns is: "Oh, that's just a branding campaign." It is criminal not to measure your direct response campaigns online. I also believe that a massively under appreciated opportunity exists to truly measure impact of branding campaigns online.

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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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Excellent Analytics Tips #20: Measuring Digital "Brand Strength"

Occam's Razor

Bonus One: Read: Brand Measurement: Analytics & Metrics for Branding Campaigns ]. There are many different tools, both online and offline, that measure the elusive metric called brand strength. I love using this tool to measure " unaided brand recall." Amazon is an interesting example.

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Explaining black-box models using attribute importance, PDPs, and LIME

Domino Data Lab

Because of its architecture, intrinsically explainable ANNs can be optimised not just on its prediction performance, but also on its explainability metric. but it generally relies on measuring the entropy in the change of predictions given a perturbation of a feature. PDPs for the bicycle count prediction model (Molnar, 2009).

Modeling 139
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Emerging Trends: 4 IRM Market Insights to Aid COVID-19 Business Recovery

John Wheeler

Provide a full view of business operations by delivering forward-looking measures of related risk to help customers successfully navigate the COVID-19 recovery. Offer capabilities to analyze business impacts at all levels of the organization by linking both strategic and tactical risk metrics.

Marketing 110
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ML internals: Synthetic Minority Oversampling (SMOTE) Technique

Domino Data Lab

Working with highly imbalanced data can be problematic in several aspects: Distorted performance metrics — In a highly imbalanced dataset, say a binary dataset with a class ratio of 98:2, an algorithm that always predicts the majority class and completely ignores the minority class will still be 98% correct. return synthetic. link] Hall, L.,

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The Importance Of Financial Reporting And Analysis: Your Essential Guide

datapine

Utilizing financial data with the help of online data analysis tools allows you to not only share vital information both internally and externally but also leverage metrics or insights to make significant improvements to the very area that allows your business to flow. firm Kraft, in 2009, it reported IFRS-based profits of $690 million.

Reporting 248