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.

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Pareto Principle Demystified: Applying The 80/20 Rule in Website Design

Are you spinning your wheels trying to boost traffic to your website? Are you constantly pouring resources into your site in an attempt to make sure that it’s everything your customers could want – adding new features, testing new strategies, redesigning in the name of staying current with the latest trend? What if I told you that the key to improving your website’s performance lies not in doing more but in doing less? If that prospect sounds too good to be true, I assure you that it’s not. Allow me to introduce you to the 80/20 Rule: focus on the 20 percent of things that will fetch you 80 percent of the results.

The 80/20 Rule defined

The 80/20 Rule is often interchangeably known as the Pareto Principle, Juran’s Principle and the Principle of Factor Sparcity. So what exactly is this multi-monikered principle? Let’s turn to Wikipedia for the answer: “The Pareto Principle...states that, for many events, roughly 80 percent of the effects comes from 20 percent of the causes.” The concept was the brainchild of business consultant Joseph M. Juran, and its namesake is Vilfredo Pareto, an Italian economist who observed in 1906 that 80 percent of the land in Italy was owned by 20 percent of the population. Since then, the principle has been applied widely to all aspects of business, whether it’s that 80 percent of a company's profits come from 20 percent of its customers, 80 percent of its sales come from 20 percent of its products or 80 percent of deals are closed by 20 percent of its sales staff. By following this principle, many businesses have realized great gains in profitability by focusing resources on the areas that net the greatest effect and eliminating, ignoring, automating, delegating or retraining the rest.

But how does the Pareto Principle apply to website design?

For the answer to that question, let’s head over to the blog of Tim Ferriss, a well-respected efficiency expert with a well-documented affinity for all things minimalist. Ferriss, a proponent of the 80/20 Rule, once performed a case study and noted that websites optimized using the Pareto Principle have a 20 percent higher conversion rate. Further more, Ferriss observed that in order to effectively implement the Pareto Principle in the design of any given website, only certain changes are required to be made, the majority of which involve the home page itself, since that is where most – if not all – of the site’s most mission-critical information lives. Most of these changes are relatively minor in nature, such as a cleaner call-to-action button, an uncluttered sidebar and so on.

Why should you use Pareto Principle in your web design?

The benefits of applying the Pareto Principle in the design of your website are two-fold for your visitors and for yourself. To begin with, the Pareto Principle means less work for you. Rather than fussing and fretting over how to max out every available square pixel of real estate on the screen with every conceivable feature and copy point, you only have to concentrate on that most important 20 percent that will take care of the remaining 80. Plus, keeping the focus on the most essential aspects of your site website ensures that your visitor’s attention is driven straight to your primary call-to-action elements (in fact, the Pareto Principle can be detrimental if not backed with a crystal-clear call-to-action mechanism). This in turn leads to higher conversion rates and winning over more new fans, subscribers and customers for your brand. From the perspective of visitors to your site, the Pareto Principle guarantees that they can look forward to a clean, streamlined browsing experience with fast page-load times that’s free of distractions and frustrations of any kind, thereby helping to turn turning random first-time visitors into regular users.

Putting Pareto into practice

Now that you’re on board with the Pareto Principle, how do you go about putting it into practice? To begin with, let’s take a literal interpretation of the rule: focus on the 20 percent of the elements that are responsible for the other 80. What is that magical 20 percent of the most vital things in your website? Call-to-action buttons, traffic funnels, images, whitespace, etc., right? In other words, USER EXPERIENCE. Yes, that’s right. The driving motive behind the 80/20 Rule is to provide the best possible user experience. Let’s examine the simple example of social sharing buttons – a nearly ubiquitous presence on every website or blog nowadays. Look at the sharing buttons that are present on your website. When was the last time the MySpace, Friendster or Digg buttons were used? These do not belong in that vital 20 percent. Similarly, let’s focus on another commonplace element of web design – the sidebar. Look at the sidebar elements on your own website or blog. What’s the purpose of having your 15 most recent posts listed there? If you are running a blog, your visitors can easily find your most recent posts on the main page of the blog itself. If you are designing for mobile, the Pareto Principle becomes all the more vital. In general, the elements that are prioritized for a mobile version constitute that 20 percent. If you are able to freely leave out certain sections of your website in its mobile version without negatively impacting its usefulness to your visitors, chances are that those sections do not belong in the most important 20 percent segment of your desktop version, either.

Five simple steps to implement Pareto

1. Identify the primary objective of your website. Is it to sell products, promote your brand or provide a service to the community? 2. Next, make a list of all items on your website that contribute directly to the fulfillment of this goal. For example, if you are selling products, the area where you promote your latest special offer or new arrivals belongs in the 20 percent. Also make a similar list of items that do not directly contribute to the main goal. 3. Eliminate any and all unnecessary elements. Easier said than done, isn’t it? 4. Refine, refine, refine. Make sure the focus of every page and every element on the page remains on that critical 20 percent of items that directly support your main objective. 5. Grab a coffee.

Analysis, prioritization, optimization and simplification

Before you launch into an all-out take-no-prisoners offensive to streamline your website, here are a few additional tips to consider: Analysis: Use tools such as Google Website Optimizer and Analytics to analyze your website’s most frequently used and important elements. Prioritization: Once identified, prioritize that 20 percent of important aspects that are responsible for 80 percent of the results. Optimization: Optimize that 20 percent elements and thereby see a boost in 80 percent of the performance. Simplification: Implement good design principles of minimalism and reductionism to simplify your site’s user experience without sacrificing quality. A final word of caution: Don’t overdo the 80/20 Rule. While you do want to focus on the 20 percent, this does not mean you should outright ignore the other 80 percent of lesser important things. When it comes to user experience, the details matter. Unarguably, the greatest benefit of implementing the Pareto Principle in the design of your website is that it allows you to keep your focus on the content that matters most. So go ahead, and experiment with putting it into practice. After all, what do you have to lose besides the clutter that is holding your site back from reaching its maximum performance potential?

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