Wojciech Gryc

Wojciech Gryc is the CEO of Canopy Labs. Prior to Canopy Labs, Wojciech was a consultant with McKinsey & Co. and a researcher at IBM Research. Wojciech is a Rhodes Scholar and Loran Scholar.

Our Favorite Big Data Marketing Slogans

Like it or not, the term “Big Data” is here to stay and every day sees new businesses building on the trend. Many promise to boost sales, drive productivity, and help executives and junior staff make sense of all that is “Big” and all that is “Data”.

Very few companies veer away from this type of marketing message, but those who tactfully and effectively market in this space, do so by building a vision and idea around how data change the world. This year will likely see more data-oriented companies than any other time in human history, and we decided to choose the ones that paint a portrait of the future in a positive and exciting way.
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Happy Holidays! Five Holiday Gifts for Data Scientists

First and foremost, the team at Canopy Labs wishes all our readers, data scientists, and customers a happy holiday season! It’s been an amazing year for Big Data, analytics, and IT — and we’re excited with where 2014 will lead.

If your data science team is anything like the ones we’ve seen, they’ve likely seen a busy 12 months. Whether they’re implementing a new data warehouse, generating models to target cross-sell opportunities, or simply updating executive-level reports, data-oriented roles are becoming more important and significantly busier. If you’re getting holiday gifts for your data science team at the end of the year, here are five we recommend for any data scientist on your list.
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A Heat Map of Consumer Sentiment For The Past 13 Years

Visualization is crucial to understanding and learning from our data. As we continue to experiment with new forms of visualization, we wanted to share with you a heatmap of consumer sentiment over 13 years, from 2000 to the end of 2013. The visualization below shows a grim, yet informative, view of how consumers feel about their lives and prospects. Mouse over the grid elements to see the numbers themselves.
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Prescriptive analytics: three ways to maximize customer success through Big Data

“I’ve invested in analytics and have thousands of data points streaming into our databases, yet life doesn’t seem any easier.” Unfortunately, this is a very common complaint about Big Data investments. Teams get overwhelmed with too much data, and analysis often takes longer if you throw more data at a problem. A newly emerging trend in this space is the use of “prescriptive analytics” — rather than simply collecting data, your team can rely on automated analysis tools to generate recommendations (i.e. prescriptions). This means no more lengthy data reviews, but simply allowing the prescriptive tool to make business decisions on its own.

If this sounds too good to be true (or scary!), you might be surprised to know that many companies already use such approaches. Review the examples below to see how companies are using prescriptive analytics to automate and grow their businesses.
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Canopy Labs announces analysis of over $1 billion in commerce; releases new dashboard and analytics tools

Please note this is a copy of the press statement released earlier in the day today. Any media questions should be sent to wojciech@canopylabs.com.

Canopy Labs, a predictive customer analytics company, announced today that its predictive customer analytics platform has now analyzed over $1 billion in commerce activity. Since launching its platform in early 2013, the company has begun to work with professional sports teams, retailers, and ecommerce companies to predict customer activity for sales and marketing teams.
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Customer activity maps: predicting and preempting customer activity

Picture this: Julie, a website visitor, decides to send a customer service e-mail. Given her browsing history, tone in her e-mail, and mailing list subscriptions, you know she is 70% likely to make a big purchase before the holidays. Her e-mail is routed to your best support agent – to provide support, and ultimately make a sale.

It might sound too good to be true, but if your company is collecting data about your customers, it’s not far from reality. Every day, your customers are making decisions on which emails to read, products to buy, and pages to visit. If you’ve centralized this data, you can predict which of those actions matter, and just how likely they are to make other decisions.
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Buying self-serve analytics tools? Make sure they’re “end-to-end”, are scriptable, and provide support

The analytics space is getting more crowded by the day, with new startups, products, and tools being announced regularly. If you’re a business executive or manager and are hoping to implement an analytics strategy, the choices can be overwhelming. Many tools purport to be easy to use, to have no integration requirements, and to give you answers to every question you have about your customers and the segments they’re in. While this might be the case, consider the following five rarely-considered points when choosing a tool — not only will they save you grief, but ideally, they’ll help you implement a best-in-class strategy.
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Case Study: using images in emails to encourage clicks

A very common strategy in email marketing is using images in the body of the email, or even turning the entire email into an image. Doing so serves a few purposes: the email content becomes less likely to fail depending on the browser being used, and data collection becomes easier — tracking email opens requires enabling images. These facts, and others, have led many companies to adopt image-based email marketing campaigns. Below, we present a case study related to using images to encourage open rates — and whether or not it is a good idea.
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