The latest perspectives on data, sales, and customer success
Canopy Labs is delighted to announce a public case-study detailing our work with leading travel company Kensington Tours. By using data to automatically respond to traveler intent, Canopy Labs helped Kensington earn a 49X return on their investment.
Many businesses across a number of industries are discovering that there is a plethora of data customers leave behind when interacting with their company, be it online, in-store or both. Even though harnessing this wealth of data can provide several organizational benefits, many companies still have not gone beyond collecting and storing their data. It isn’t easy to deal with unstructured data but the benefits are rewarding if you do.
Picture the last time you visited a museum, whether in your city or on a recent vacation. You probably went online to check opening hours, exhibitions, and ticket prices. You arrive at the museum, wait in line to purchase your tickets, spend a few hours viewing the collection, and stop by the museum store on your way out. You might find there’s so much left to see, you join as a member so you can come back again soon.
Every little interaction that day – from browsing the website, to purchasing a souvenir at the end of your visit – impacts whether or not you had a positive experience, and will consider visiting again.
Canopy Labs is excited to share our latest case study with Well.ca, Canada’s largest online destination for health, wellness, beauty and baby essentials. Canopy is proud to work with Well.ca, which has grown revenue per email by 129% through personalizing its emails with 1:1 product recommendations.
At Dermalogica New Zealand, reminding subscribers of individualized promotions increased campaign revenue by 61% and spurred 3 times more revenue per email. Specifically, Dermalogica New Zealand sent subscribers a reminder to use their promotional code from an earlier birthday email – a simple follow-up email based on engagement, which saw surprisingly powerful lift.
Product recommendations are quickly becoming a staple of online shopping experiences. Whether it’s Walmart.com or a new Shopify store, more and more companies are incorporating “Also Recommended” or “Customers Also Bought” offers to their site. However, too many recommendation engines today are still a bit clunky – if you look at one pair of blue jeans, suddenly all you get are offers for dozens of blue jeans.
Today we’re sharing how one fashion retailer used a different approach to product recommendations, leading to a 26% increase in Average Order Value.
Consumer-facing companies often face the struggle of not knowing enough about certain types of customers. While your most loyal customers will have lots of purchases, e-mail activity, and other data to inform your marketing team, this probably isn’t the case for a majority of your customers, particularly the ones that only have one or two transactions with you. These “middle ground” customers are usually missing just one or two data points to inform your segmentations or broader marketing strategy.
In our last blog post, we touted the benefits and popularity of one-click email surveys, particularly compared to traditional tools like Google Forms and SurveyMonkey. But how do these surveys perform in terms of engagement?
Online surveys typically suffer from low response rates (and even lower completion rates, especially if a survey takes more than a few minutes to complete). A University of Florida study found that online surveys are 11% less effective than mail/phone surveys, and response rates of 2% are not uncommon. The advantage, of course, is that online surveys cost very little to run, and give easy access to tens of thousands of respondents.
Given the benefits and ease of one-click surveys, they should theoretically see higher response rates than traditional surveys. Does this actually hold true?
Every company wants to be asking customers how they can improve their products and deliver a better customer experience. This feedback is often collected through telephone calls, focus groups, or conference workshops. From our experience, the most common approach is a digital survey, where a customer receives an email asking them to fill out a long website-based feedback form.
At Canopy Labs, we work with businesses of all sizes to power 1:1 product recommendations in emails and websites. The revenue and customer engagement benefits of personalization are clear – and the more you personalize, the greater the impact that personalization will have on your business.