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.

How to Scientifically Predict Revenue in Seasonal Industries

Whether you own a sports team, run a ski resort, or sell school supplies, you’ve likely come across some seasonality in your sales and revenue. Indeed, even seemingly noncyclical businesses, like fast food or clothing, experience some sort of seasonality.

Seasonal sales are risky because, in the most extreme cases, you have only a few days to make your sales numbers. Imagine you’re a retailer preparing for Christmas — success or failure in mid-December might mean success or failure for the entire year. With that in mind, an analytic tool that gives you an idea of what to expect can be a crucial resource during the seasonal sales cycle. Here, we present an example of how one can apply predictive analytics to forecast seasonal sales months in advance and take pre-emptive action.

What is a Universal Customer ID (UCID) and why does your business need one?

Most companies have multiple sources of data. These include transaction systems that track customer purchases, e-mail systems, CRM databases, and numerous other data sets that track individual customer interactions with the business. Oftentimes, these data sit in silos with little interaction or cross-pollination of information between databases. As companies become more inclined to run analytics projects, they often ask how to merge such data sets into a unified whole. The first step to doing so is through the use of a Universal Customer ID (UCID).

If your company tracks individuals, you already have some idea of what a customer ID is: a unique identifier meant to track customers within the software tools you use. In eCommerce settings, the most common type of ID is the e-mail address — every individual is considered unique, and individuals use e-mail addresses for receiving receipts, subscribing to newsletters, and other functions.

Analyze your customers and API data in R through the Canopy Labs Console

Canopy Labs strives to make it as simple as possible for any individual to understand their customers by browsing profiles and viewing dashboards. We also know that it’s not always possible to predict what customer analytics problems our clients will be looking to solve. With this in mind, we are introducing the R Console for Canopy Labs. The goal behind the R console is to make all your centralized customer data and model results in a scriptable, customizable form. We’re hoping that this will allow you to build even more advanced and interesting models. In this blog post, we’ll show you how to start using the R console yourself.

When should marketers send e-mails? And why?

Do you run an online business or market your products on the web? Then you’ve likely come across numerous tactics that are believed to help your reach your goals — launching on a Tuesday, sending e-mails when people are actually sitting at their computer, and responding to people’s inbound questions within 5 minutes of them contacting you.

Of course, not all tactics are created equal, and as more companies market online, tactics that once worked have now become moments when everyone tries to reach their audience.

Related to this, many of our customers ask, “When should I be sending my e-mails to customers?” When you send an e-mail, you want it to stand out from the crowd, and to arrive at a time when your customer is most likely to read it. This should be when they are attentive and at their inbox, but not overwhelmed with too much e-mail — work or personal.

Optimizing e-mail click rates — how to structure a call to action

We regularly help companies with their customer outreach through e-mail, and in the process have become very familiar with different types of e-mail templates and calls to action. Companies often ask us how they can optimize their click rates on e-mails, and today we wanted to share some findings from a recent case study based on e-mail templates and specific types of actions to recommend.

The challenge with designing e-mail templates is a seemingly contradictory set of goals. When sending an e-mail, you want to have a clear and obvious call to action (e.g. purchase a product, make a donation), but to also present it with context so that the reader understands why they are being presented the specific call. In other words, you want to provide context around the call to action to ensure a person has enough information to understand why they are being asked to click, and to actually click through.

The Canopy Labs Lead Generator: an introduction

A primary use of the Canopy Labs cloud platform is lead list optimization. When you have a large customer base and specific marketing campaigns in mind, it is crucial to generate lead lists that actually target the right customers for offers and marketing campaigns. Not doing so could lead to poor conversion rates and wasted effort.

Unfortunately, lead generation is not an easy process: you need to know who your customers are, what they are likely to want next, and make the list accordingly. However, there is light at the end of the tunnel: the Canopy Labs lead generator allows you to filter customers in such a way to boost performance of marketing campaigns. This tutorial aims to show you how, and includes three parts to the process:

  1. Creating a lead list based on future spend likelihood.
  2. Filtering based on past customer performance.
  3. Reaching out!

Five Articles for Boosting E-mail Campaign Conversions

E-mail newsletters are some of the most common outbound sales channels today. Nearly every online purchase now asks you to provide a valid e-mail, and for good reason — businesses covet these lists. MailChimp, arguably the most popular service for running e-mail newsletters, boasts over 2.5 million users and sends over 4 billion e-mails per month.

If you run an online business, chances are you are — or are considering — running an e-mail newsletter. As you jump into this process, it’s important to keep in mind the best practices around running e-mail newsletters.

What is “Customer Success”?

In recent months, the term Customer Success has been getting more interest from companies, particularly for those focused on online sales. “Customer success” however is still a largely ambiguous idea, one that few companies have actively explored and engaged with. In light of this week’s Pulse Customer Success conference, we thought it would be helpful to discuss the term in detail, explain what it actually means, and outline how your company can strategize around it.

Model Performance Differs by Analytics Tool — A Tale of Caution

Business analysts rarely give much thought to the analytics tools they use, and usually just use the software already available in their enterprise. Even more commonly seen is the use of default settings within such systems — strapped for time, analysts and reporting staff will use the default settings in their software packages to complete tasks on time. This is risky, as default settings are not always the best ones to use for specific business problems or modeling tasks.

New Features in the Canopy Labs Platform

We are excited to announce a new set of features to the Canopy Labs platform this week. These features have been under development for the past few months, and are now available to all users and customers. They are the result of your valuable feedback, support, and advice. If you ever want to learn more and see other new models, dashboards, or other tools, please let us know.