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.

Every email marketer wants to be able to directly track sales generated by a specific campaign. Commonly used metrics such as open rates and click rates are only rough proxies for the measures that really matter – purchase conversion and total sales. In this blog post, we will explore how to use the Canopy Labs R Console to assess and compare email campaign performance.

Setting up the test

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.

One of the biggest opportunities we help our customers capture is converting infrequent purchasers into loyal customers. Today, we highlight the recent experience of one of our customers in the fashion industry (“Fashion Store”) and demonstrate how using email campaign segmentation helped them boost purchase conversion by 5.5x.

Creating a campaign strategy

So you’ve just installed the new Canopy Labs app for your Shopify store, and now want to reach out effectively to the leads you are generating through our system. While most companies do this with e-mail or phone calls, some of our customers opt for more creative solutions. Today, we’re featuring a set of apps that help bring your store’s outreach to a new level of sophistication.

Customer Pricing

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.

The Canopy Labs R Console versus R itself

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.

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.

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:

Email remains as ubiquitous as ever – to the tune of over 144 billion being sent per day in 2012. Furthermore, businesses are increasingly turning to inside sales as a primary method of prospecting. So how do you make sure that it is your email that stands out in the inbox of a potential client?

Today’s insight emerged out of a question one customer recently asked – is it worth the effort to personalize your emails to potential clients? While no one would disagree that personalizing your email is more effective than relying solely on a template , the obvious drawback is the amount of time it takes to write a personalized, genuine, thoughtful message. Today, we share some of our test results on the impact of personalizing your email outreach and provide you with a few insights to take away in your own outreach process.