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.

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.

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.

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.

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.

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.

Building customer profiles through purchases, emails, and web activity (a fashion store case study)

If you run an online store, you likely know about the importance of analytics and tracking your web visitors. Unfortunately, most tools today provide a high level, aggregated view of your visitors. These tools tell you how many individuals visited each page, but it is often impossible to tell what each individual did and how this relates to their purchases. Today, we show you how you can view your customers’ purchases and email activities alongside website visits in the Canopy Labs customer profiles.

Building dashboards on Canopy Labs: a video tutorial

One of the best parts of the Canopy Labs platform is the ease in which you can build custom reports and dashboards. To make this even easier, we have created a short tutorial video to walk you through the process! Click below to watch the video tutorial.

We’ll be adding numerous dashboards to the dashboard and charting library over the coming weeks. Let us know if there are dashboards you are looking for and we’ll add them to the list!

Building customer segments using Principal Component Analysis (PCA)

A very common approach to building and understanding customer segments is through the use of clustering techniques such as Principal Component Analysis (PCA). These clustering techniques will analyze your customer data and see if customers tend to cluster by certain features, or combinations of features. Through such an approach, a marketer can use clusters to define specific segments. For example, running a cluster analysis could end up showing two clusters: one with customers who have high values for variables related to “engagement” (e.g., emails, comments, etc.) while another could be a cluster with lower values for engagement variables, but mid-sized value for purchase-related variables (e.g., number of purchases, number of products, etc.). In this case, the marketer can conclude that two segments, “Engaged Leads”, and “Slightly Engaged Purchasers”, exist within the customer base.

Segmenting your web visitors based on site traffic — a primer

Most companies that Canopy Labs work with sell their wares online. More generally, most major retailers do so as well, especially as they invest in digital content and sales processes. If you’re such a retailer, than you already know that tracking your online traffic is crucial to understanding the effectiveness and eventual success of your website. Indeed, every online business we meet obsessively tracks their Google Analytics dashboard, and they’re in good company: over 12 million websites use Google Analytics.