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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Guest Blogging 101 (Or How to Grow Your Audience by Giving Away Your Best Material)

Growing community and conversation around your brand is no easy feat; it requires dedication, focused effort and time. In addition to creating a platform that’s easy to navigate and top-notch content that drives engagement, you must constantly promote yourself to raise awareness and bring fresh eyes to your material. As counter-intuitive as it might sound, when you’re in the process of trying to grow a fledgling handful of followers into a thriving community of dedicated readers, one of the best ways to do so is by giving away your best posts. Why? Because in building relationships with bloggers who have already developed a community of followers whose interests overlap with your area of expertise, you can gain exposure to new readers who will then hopefully take an interest in hearing more of what you have to say. As a blogger myself, I've done this firsthand through Facebook, Twitter, Pinterest and strategic guest blogging opportunities. Though a bit intimidating at first, reaching out to bloggers I admire who cover similar topics has yielded valuable guest blogging opportunities that have helped me to steadily increase my reach and gain new readers for my own blog. Based on that experience, here are five secrets to success in scoring great guest blogging gigs that will help you grow your audience:

1. Know your niche.

What topics do you cover? How often do you post? What are your visitor stats? Who is your ideal reader? You need to have a strong grasp of these things so you can identify the right bloggers to connect with whose audience will most closely align with your own. It’s also important to make sure that somewhere on your site – whether it’s in the sidebar of your blog or on your about page – you have an introduction that’s crafted to quickly and succinctly orient new readers to your community. Focus on the reader’s interests by briefly explaining who you are, what topics you cover and what qualifies you as an authority in your niche. Point them to your most popular posts and invite them to subscribe to your content. And don’t forget to include a way for them to get in touch with you to pave the way for conversion from causal reader to paying customer.

2. Do your research.

You don't want to connect with just anybody out there with their own platform; you want to be strategic with the relationships you build. As a creator of content, you likely read quite a few blogs yourself. What are they? Do they cover similar topics? Is their demographic the same as yours in any way? It may be helpful to make a spreadsheet with these details, along with contact information to make your life a little easier when it comes time to reach out.

3. Become a prolific commenter.

By commenting, I mean both on your own blog in response to comments from your readers and also on blogs that you regularly read and follow. The blogging world is all about connection, community and driving conversation. If you stay silent, you’ll cut yourself off from opportunities to cultivate a more deeply engaged reader base. Although it may be impossible or impractical to reply to every single comment on every single blog post you write, you should make a habit of checking the comments section and replying to readers directly. Better yet, see if your platform has a tool that will alert you by email whenever you receive a new comment so that you can reply quickly and boost the chances of keeping the conversation going. When commenting on another author’s blog post, be sure to leave a thoughtful response. Avoid generic feedback like, “great post,” and opt instead for noting what what you found uniquely insightful or inspiring about the post, asking a question that provokes further debate and discussion or even answering a question the writer might have posed within the post itself. By doing so, you not only contribute in meaningful way to their community, but you also encourage them to check out your own blog as well.

4. Make a pitch.

Once you’ve acclimated to interacting with other bloggers and have a strong grasp of blogs that are aligned with your own blog’s niche, it’s time to reach out and make a pitch. By now, you should be very familiar with the content on the blogs you’ll be pitching to—what topics they cover, what they’ve written about recently, who runs the blog, etc. Not sure where to go from there? Here are some suggestions for crafting your message:

• Employ a tone that’s personal and friendly while keeping your request brief (no more than two paragraphs).
• Reference some of their recent posts so they can see that you are a real follower of theirs and you’re not just sending out the same pitch en masse to anybody with a blog.
• Provide links to your blog, portfolio and social media profiles to help them get a feel for your expertise, writing abilities and point of view.
• Be specific about what you’d like to write about, whether it’s a certain topic where you have expert advice to give or a series they’re doing where you can offer valuable insight.
• Follow up if you don’t hear back, allowing a week or so to make sure they’ve had time to review and process your request.

5. Become a contributor.

If you happen to have a little extra time on your hands, becoming a regular contributor on a high-traffic blog is a sure-fire way to connect with new readers who otherwise may not have found you. In addition to building your portfolio and legitimizing your expertise, being a contributor ensures major publicity for your content and exposure on a much broader level. Although developing an organic following will take some time, defining your blog’s niche, finding similar blogs to strategically connect with, engaging in the blog community through comments, pitching ideas to bloggers and contributing to high-traffic sites on a regular basis will help you develop valuable connections that will lure new readers to your blog. And when you feed these readers a steady diet of insightful, conversation-provoking content, you’ll find they’ll not only become a regular fixture in the burgeoning community that’s developing around your content and your brand, but that they’ll also become your allies in recruiting new members by sharing your great stuff within their own circles.

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