outsourcingdatasciencewhatyouneedtoknow

Outsourcing Data Science: What You Need to Know

More companies are creating data science capabilities to enable competitive advantages. Because data science talent is rare and the demand for such talent is high, organizations often work with outsourced partners to fill important skill gaps. Here are a few reasons to consider outsourcing. What can go right and wrong along the way? [Read More]

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tripadvisorgrowth

The Marketing Savvy Powering TripAdvisor’s Global Growth

TripAdvisor knows a thing or two about growth. In 2014, the world’s largest travel site saw 1.246 billion in revenue, an increase of 32% over 2013. The company’s product offering has expanded too. TripAdvisor’s Instant Booking Platform has growing steadily since its rollout in 2014; Priceline’s Booking.com was recently added to its roster of participants. […]

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intentionalserendipityanalytics

Intentional Serendipity: How Marketing Analytics Trigger Curiosity Algorithms and Surprise Discoveries

Microwave ovens. Velcro. Viagra. These and many other everyday scientific advances were discovered quite by accident. Serendipitous discovery plays a huge role not only in scientific advances, but also in major breakthroughs in marketing strategy. With more data open to marketers than ever before, marketing analytics can now play an even bigger role in revealing […]

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howairlinesbigdataprice

How Airlines Are Using Big Data to Price Your Ticket

Airlines are now able to collect more data than ever on their passengers, and they’re using this data to build profiles on individual passengers. By building individual profiles on passengers with information such as lifestyle purchase choices, flying habits, and even passenger financial position, they’re able to come up with clever ways to give you […]

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succesfulanalyticsteam

Roles and Responsibilities of a Succesful Analytics Team

After years of working with hundreds of companies, I’ve learned a thing or two about what makes analytics projects successful. I’ve also watched many projects fail. The most common reason for failure might surprise you. It’s not a lack of data expertise or an integration mistake. It’s simply that the organization forgot to make it […]

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wonderfulworldrecommender

The Wonderful World of Recommender Systems

I recently gave a talk about recommender systems at the Data Science Sydney meetup (the slides are available here). This post roughly follows the outline of the talk, expanding on some of the key points in non-slide form (i.e., complete sentences and paragraphs!). The first few sections give a broad overview of the field and […]

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