This morning, the Financial Times published an article on the dismal state of retail — Staples, Dick’s Sporting Goods, JC Penney, and others are all struggling. In large part, these challenges have been driven by a growing number of consumers moving their purchases online. With the move to the web, traditional retail is forced to compete with wholesalers, web-only discounters, and of course, Amazon. In fact, offline retailers now have the added challenge of serving consumers who enter their stores to browse, but make their purchases online from home. Not only are these consumers not spending money in-store, but they are buying the same products at competitive sites.

The hits to share prices and profitability are likely to continue as more individuals move their purchases online, particularly for products that don’t require browsing. Books, office supplies, and personal technology can all be bought online without having to be reviewed in-store. As virtual fitting rooms, bespoke “e-tailoring”, and subscription services grow in popularity, more verticals will be affected — we’re already seeing the growth of web-based food delivery and clothing purchases, for example.

If you run an online store, then you already know that triggered email campaigns should be a key component of your sales, customer service, and brand awareness strategies. Personalized trigger emails are opportunities to cross-sell your products, engage your customers with your brand, and reward your most loyal fans with special rewards and recognition. Best of all, they require minimal configuration on your end and run on their own after you set your business rules!

Here at Canopy Labs, we’ve seen that sending timely and relevant email messages boost purchase conversation rates and drive sales. But what kind of auto emails should your business set up? Below, we’ve compiled 6 ideas for triggered email campaigns that will help you manage your customer life cycle and boost your sales:

Regular readers of our blog might have noticed a lack of updates over the past few months… Worry not, fellow Canopy Labs fans, we’ve just been busy growing the business! And now we’re excited to share some of the good news with you.

Doubling Our Team to 15

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.

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.

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.

“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.

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.

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.

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.

1. Ensure that customer support is available daily. Your business doesn’t have time to stall while waiting on a customer service request. Ensure that the company you are buying from is available constantly or has a “maximum response time” guarantee. When you do not understand a chart or recommendation, it is crucial you get your conundrums addressed.
2. Clarify integration responsibilities. Companies often require you to pay additional fees for custom integrations, or refuse to integrate your data unless you use their supported platforms. Before making any decisions about a platform, ensure it supports your existing databases or commerce tools. Some companies (like ours!) will do the integration at no additional cost.
3. Make sure it’s end-to-end. Most companies are looking to buy an analytics tool to solve a specific need — be it discovering cross-sell opportunities, clarifying costs, or improving e-mail conversions. Whatever your goal, strive to find a tool that actually helps you achieve the goal rather than simply providing the analysis.
4. Check for a scripting language. As you become well-versed in analytics, your questions will become significantly more complex and oftentimes will be beyond the purview of the out-of-the-box dashboards most tools provide. Ensure there is a scripting language powering the tool you buy, and ideally, a customer support team that can write queries for you.
5. Be comfortable! Some sales teams will specifically try to confuse you or intimidate you with complex and fancy statistics. While such tools can be powerful, any tool that seems complex or intimidating is likely to remain unused once you actually purchase it. If anything, take the time to learn it before you buy; the sales team should understand and support you in this.

Have other tips for those buying tools? Let us know!