Intelligent Design: Transform Your Website into a Sales Engine with Machine Learning

Machine learning: The phrase evokes images of computers playing chess or IBM’s Watson destroying two legendary Jeopardy! champions in a three-day tournament. The truth is, though, machine learning is no longer a novelty; it’s now an integral part of our daily lives. Every time you receive a product recommendation from Amazon, your email server weeds out spam before it reaches your inbox or you enjoy a playlist on Pandora, you’re seeing machine learning in action. In a nutshell, machine learning is the science of training computers to recognize data patterns and make adjustments automatically when those patterns change. While on the surface this may not sound very exciting, nothing could be further from the truth. In fact, machine learning is the key to transforming your website into a lean, mean selling machine.

Understanding machine learning in 100 words or less

Machine learning uses algorithms to build models from data; as more data is collected, the algorithms are “trained” to adapt to changes. There are two ways in which machine learning can be implemented: supervised and unsupervised. Supervised learning algorithms are used to create models that establish relationships between types of data — the relationship between purchase data and user clickstream data, for example. Unsupervised learning uses algorithms to gain insights into customer behaviors and preferences by looking for patterns within the data. Both of these methodologies are designed to make marketing and e-commerce more exact, more personal and more profitable.

Putting machine learning to work

Netflix, Pandora and Amazon are all familiar examples of machine learning in action. All three use recommender systems powered by complex algorithms. These systems collect data about your browsing activities, past selections and any ratings or reviews you may have provided. Then they segment you into clusters with other customers who have demonstrated similar interests or behaviors and use this data to suggest items that might appeal to you based on the browsing and purchasing habits of these other customers. You see this on Netflix as the category titled “Because you watched...” and on Amazon as “Customers who viewed this also viewed...” To gain a deeper understanding of how these algorithms work, let’s take a closer look at Amazon. To Amazon, you are a very long row of numbers in a massive table of data. Your row represents everything you’ve looked at, clicked on, purchased (or, equally as important, not purchased) or reviewed on the site. The other rows in this gargantuan table encompass the same thing for the millions of other customers who shop on Amazon. With every click, visit and purchase, more data is added to your row, which allows Amazon to constantly mold and shape the products it recommends to you and the special offers you receive based on an ever-evolving stream of information about you that is being collected and stored. Another innovative example is True Fit, a retail software start-up that is on a mission to apply data analytics to increase customer confidence in online clothing purchases while decreasing the number of returns for e-railers. Well-known fashion retailers, including Nordstrom, Macy’s and Guess, have implemented True Fit’s algorithms on their e-commerce sites. When customers shop on these sites, they’re asked to create a profile that includes their height, weight and perhaps most importantly, the size and brand of their favorite piece of clothing. Using that data, True Fit is able to recommend the correct size for a specific brand and article of clothing. Even more importantly, as customers continue to use the True Fit system, it learns more about their personal style and preferences and steers them toward purchases they’ll be more likely to keep and enjoy rather than return.

How machine learning drives smarter marketing

You don’t need the resources of major e-commerce giants like Amazon or Netflix to take advantage of machine learning to to improve your e-commerce site and your online marketing efforts. By enhancing your existing site with systems that allow you to create a virtual marketing intelligence brain, you can create a more personalized – and therefore higher quality – shopping experience for your customers. By establishing this type of marketing intelligence ecosystem, you can mine the data provided by customers every time they visit your site to answer vital questions that will help you fine-tune your site and your online marketing strategy – questions like these:

• How likely is a given website visitor to convert?
• What behaviors characterize customers who are likely to buy?
• What behaviors characterize customers who are likely not to buy?
• How can new visitors be identified as high-potential long-term customers?
• Which type of web traffic has the most value?
• Which products or services appeal most to a given segment of customers?
• Given the contents of a particular customer’s shopping cart, which additional products are high-potential recommendations?
• How can website visits be optimized to provide the best possible experience for each individual customer?

Making it personal

The final question in the list above is one that deserves special notice because of the staggering potential for using machine learning to create a more personalized shopping experience – one of the key drivers for increasing online sales. Not only can the data collected via such marketing intelligence ecosystems be used to drive recommender systems, it can also be used to create personalized advertising based on market segments — or even individual profiles — that can be distributed across a variety of desktop, mobile and social platforms. This type of advertising can be tailored to any number of personal preferences and demographic information, including age, marital status, location, lifestyle choices, typical purchases, brand preferences and so on. Ads can be focused to such a granular level that they reflect specific colors a given customer prefers, and their individual purchase drivers, such as status or cost-effectiveness. Another exciting aspect of machine learning-based personalization is the development of individual customer profiles. You can even combine online and offline customer data to create a more complete picture of a given user. Types of data included in this profile might include online and in-store purchases, membership and activity in rewards programs, product ratings and clothing sizes. Just imagine how much more powerful your marketing efforts could be if you were armed with this level of information. One of the most important aspects of a successful marketing intelligence ecosystem is how data mined from customer activities is combined with sound business rules in order to make smart recommendations that are well received by customers and that do not compromise their trust in your brand. For example, most people who walk into a supermarket like bananas and will often buy some. So shouldn’t the recommender simply recommend bananas to every customer? No – because it wouldn’t help the customer, and it wouldn’t increase banana sales. So a smart supermarket recommender would always include a rule to exclude recommending bananas. At the other end of the spectrum, the recommender shouldn’t push high-margin items just because it’s beneficial to the seller’s bottom line. It’s like going to a restaurant where the server steers you toward a particular high-dollar entree. Is it really his favorite? Or did the chef urge the staff to push the dish because it comes with a side order of premium mark-up? To build trust, the best recommender systems strive for some degree of transparency by giving customers clues as to why a particular item was recommended and letting them adjust their profile if they don’t like the recommendations they’re receiving.

Science fact, not fiction

Machine learning can give your business a serious competitive edge by opening the door new opportunities in the marketplace. It can help you personalize and improve your customer experience dramatically and thereby drive sales and revenues. Creatives and developers alike are rapidly pioneering new and innovative ways for marketers to use machine learning — and the future of marketing built on these ideas has seemingly endless possibilities.

---

Go Mobile or Go Home

Once upon a time, not so very long ago, being available to your customers online 24/7 was enough. But then along came the smartphone – and its even more agile cousin the tablet – and the expansive mobile data networks needed to support them. Suddenly the Internet came unfettered from desktops anchored to offices and homes and became a ubiquitous presence in our lives. Today 24/7 just doesn’t cut it. You must be available to your customers not only anytime but anywhere. At the corner coffee shop. In line at the supermarket. At the airport. In the very aisles of your competitor’s store. You may not know for certain when or where your customers might be looking for you, but you can be absolutely sure that you must be there if you want to stay competitive in today’s market. Consider this statistic: smartphones and tablets currently drive nearly seven percent of digital traffic in the U.S. If that number doesn’t wow you, try this on for size: experts predict that by 2013 – that’s next year – more people will access the Internet via phone than computer. It all boils down to this: the proliferation of smartphones and tablets in the past few years has changed the game. If you’re in it to win it, you have to go mobile or go home. But where do you start?

Look before you leap.

Before you take the plunge into the world of mobile, it’s a good idea first to figure out where you currently stand so you know where you need to go and how best to get there. Peruse your website on as many different devices as you can get your hands on. Put yourself in the shoes of your customers, and evaluate the quality of your experience as you navigate through your site. How easy or difficult is it to select the specific link you want? If you have a lot of images on your site, how long does it take to render on a mobile device? Can you quickly and easily complete critical actions like locating contact information, filling out an inquiry form or even making a purchase? If you identify any obstacles, or if the overall experience is frustrating in any way, you need to take action to make sure you give your business the best chances of capturing and converting mobile browsers. There are a number of ways you can bring your site into the mobile era. To decide which approach is the right fit for your business, you must weigh your options based on your growth objectives and your customer’s browsing habits.

Option 1: Build a dedicated mobile site.

A good mobile website is not simply a shrunken version of your primary site. It’s designed specifically to deliver an experience that’s optimized for the needs and preferences of the mobile user. Keep in mind that these users aren’t typically casual browsers; they’re usually after a specific bit of information or seeking to accomplish a specific task. As a result, mobile websites don’t usually offer all the bells and whistles of their desktop equivalents. Rather, the content and functionality are pared down significantly to offer only those features that are most useful to those on the go. For example, while mobile users frequently comparison shop on their phones, they might not be as likely to actually go through the entire purchase process on their handheld device. As a result, you may not need to offer a full-fledged shopping cart on your mobile site. Instead, you might offer the capability for customers to log in to their account and save desired products to a wish list so they can quickly and easily complete their purchase later when they return to their desk. Great mobile websites have certain elements in common. They focus on critical needs, such as providing access to key services and products and contact information. They limit the use of images to minimize page load time. They offer easy, intuitive, finger-friendly navigation. If forms are included, they are streamlined and ask only for the most essential information. They don’t employ Flash, since Flash-based content is inaccessible to all iOS users.

Option 2: Employ responsive design.

Responsive design is the concept of building a website so that the layout of the site adapts and changes according to the resolution of the user’s browser, which means that it looks just as good and performs just as well on a 27-inch desktop display as a 3.5-inch iPhone and all screen sizes in between. The design is fluid and adapts to the the browser and the platform on the fly. However, the change is more than just a straightforward scaling effect; rather, certain key elements within the design – such as navigational menus, links and search fields – shift and transform according to the resolution of the browser. Employing responsive design allows you to deliver a robust experience to all users without the need to build and maintain a separate dedicated mobile version of your website.

Option 3: Get app-y.

A native app can be a fantastic mobile marketing tool, if done right. However, it’s not the right solution for everyone. Before you go down the app-building rabbit hole, there are a lot of questions to answer and obstacles to overcome. How big is your customer base? Apps require a certain scale to make sense. If you’re a mom-and-pop bakery, for example, you could theoretically develop an app that would let your customers design their own cupcakes and place their order right from their phone. While it would surely be a fun gimmick, it doesn’t fulfill a broad-based need, and the app’s ability to generate additional revenue would probably never offset the cost to create and maintain it. That brings us to another point: you must carefully consider your ROI. If you sink many thousands of dollars into development and get it approved, will people really use it? If you can’t develop an app that offers something people want and will use frequently – whether that’s in the form of utility, convenience, content or all of the above – chances are good that your investment will end up buried in the app marketplace collecting dust. Remember, too, that when you’re dealing with apps, you either have to develop a version for each operating system (Android, iOS, etc.), which can be a costly proposition, or choose just one and ignore the needs of a huge percentage of your potential customer base, which is never a smart business decision.

Be a contender.

When it comes to mobile, convenience and conversion are the name of the game. From a business growth perspective, it’s critical to ensure that your products or services are easily accessible to mobile users so you can boost your chances of capturing and converting an increasingly untethered customer base.

---