In It to Pin It: 8 Ways to Win New Customers with Pinterest

A Pinterest-ing development in social media

The results are in and they’re rather stunning: Pinterest is now the third largest social network in the U.S., right behind Facebook and Twitter (Google+ who?). Moreover, a recent study by BlogHer showed that women trust recommendations from Pinterest more than any other platform. Not too shabby for a network that’s barely two years old and still in an invite-only open beta phase.

The basic mechanics of the site are simple. Members (known as “Pinners”) can establish a profile and “pin” all the cool, funny, trendy and inspirational things that they find in their online travels to digital bulletin boards, where images (and their associated links) are bookmarked. Pinners use these boards to visually document anything and everything pertaining to their interests, whether those interests entail fashion, home décor, food, parenting, wedding planning, tech gadgets or cars.

As you’d expect from any social network, pinners can follow each other. They can also “repin” other users’ images as well as like or comment on pins. Naturally, there’s also integration with the other Big Two, with the option to share links to pins on Facebook and Twitter.

More interesting is the question of why the site has caught fire so quickly. The primary reason lies in its anatomy. True to its name, Pinterest creates a highly streamlined experience for its users that is curated according to their interests. Unlike Facebook and Twitter, where users have to sift through every photo and status update from those they follow in a linear fashion, Pinterest users can focus solely on their hobbies without their feeds being cluttered with information that holds no value to them.

The most important question, of course, is how you can harness the power of this explosive new social network to grow your business. To answer that question, here are eight ways you can use Pinterest to win over new customers and fans:

1. Tap into what people love.

Before you dive in, take some time to study the ecosystem and how its members interact. One of the greatest advantages of Pinterest from a marketing perspective is that the community is very open, so it’s easy to see who’s influential in a certain area of interest and what types of content generate the most repins and comments.

By monitoring these trends, you can identify where the best opportunities lie for your brand to create the kind of content that your customers crave.

2. Focus on values, not products.

Think your brand isn’t a good match for an image-driven platform? Don’t be too quick to dismiss your Pinterest potential. Plenty of brands that don’t seem like the most obvious fit for Pinterest – from GE to Kotex – have found creative ways to leverage the platform to engage with customers.

The key is focusing not on your products or services but on the core values that define your brand. Organize your boards around these pillars of your brand and share things there that anyone who shares that common interest or passion would enjoy. Make sure to offer a healthy balance of content that includes your products where relevant but also great stuff from across the Web as well as repins from other users.

Whole Foods Market, for example, has quickly emerged as a Pinterest rock star using this approach. The company’s core values include caring about the community and the environment, promoting healthy eating habits and providing education about good nutrition. Drawing upon these values, they’ve created a diverse collection of boards –ranging from “Who Wants Dinner?” to “Winter Entertaining” to “Super HOT Kitchens” to “We’re Used to Reusing” – where they share content from a wide array of sources that collectively represents the Whole Foods lifestyle.

3. Tell a story in pictures.

Unlike Facebook or Twitter, Pinterest is image-based rather than message-based – which is one of the key reasons for its success. When users scroll through feeds or boards, they’re presented with a simple, uncluttered interface that includes a stream of pictures interrupted just slightly by a brief caption below. As a result, to be successful, it’s important to ensure that the images you pin to your boards tell the story of the content they represent in a visually compelling way.

For example, if you want to share a link to a post from your blog on Pinterest, you need to make sure it includes a powerful image that encapsulates its key theme or message and is also intriguing enough to prompt someone to click through to see the full story.

Keep in mind, too, that when followers re-pin your images, they can change the caption. As a result, it’s important that the images you pin can stand on their own outside the context of your brand’s boards so that they continue to convey your message and values as they are repinned from one board to another.

4. Be a participant, not just a contributor.

Creating boards that offer great curated content organized around your customers’ interests is a good first step. But as with any social network, to get the most out of your presence on Pinterest, you must also listen and engage, not just broadcast.

Repinning other users’ content to your brand’s boards demonstrates that you’re there to do more than push your own agenda by elevating those who have something interesting to offer on your topics of interest. Likewise, following other users’ boards and commenting on others’ pins is an effective relationship-building tactic that can draw new eyes (and potential new customers) to your own boards.

5. Let your customers create content for you.

Pinterest makes it easy to crowdsource content. All you have to do is create group pinboards and invite other users to pin content to those boards – a great way to spark engagement with your brand.

You can also use group pinboards as a springboard for contests where you ask customers to pin pictures of themselves using your products, with prizes for the most creative, innovative or inspiring images. It’s a win-win strategy for both your brand and your customers, as your customers can enjoy a turn in the spotlight while you can promote your products in a tasteful way that’s very palatable to the community.

6. Diversify your boards.

Another element that differentiates Pinterest from Facebook and Twitter is that users have the option to follow specific boards in addition to following users. This means that a user may elect to follow just one or two of your boards rather than everything you post.

While this may initially seem like a disadvantage to you, it’s actually a benefit. Why? Because it means you don’t have to worry about limiting your content to only that which offers the broadest appeal. Instead, you can tailor each board to fit a specialized interest.

Returning to our Whole Foods example, each of their boards is tailored to a fairly narrow area of interest, whether that’s recipes, seasonal entertaining, home décor, DIY projects, gadgets or books. While all of these boards may not appeal to every Whole Foods customer, by providing such a wide array of boards, the brand has greatly increased its chances that every customer can find something that resonates with their interests.

7. Make sure your great content can be found.

If you’re investing the resources required to create and curate interesting content, you want to make sure it can be found by the greatest possible number of customers and potential customers, right? The good news here is that there are tactics you can use to boost your odds.

First, just like Twitter, Pinterest supports hashtags. Tagging each image with the central idea or theme of your board will increase its chances of being found in search. Additionally, the sharing tools built into Pinterest automatically pick up these hashtags and include them when users share your content on Facebook and Twitter.

Also, make sure when possible to form the name of your boards around keywords. For example, West Elm offers home décor boards organized around specific color palettes (“Coral,” “Aquamarine”) and patterns (“Stripes,” “Chevrons”). By naming their boards according to these keywords, West Elm helps lead users who are looking for decorating ideas focused on that color to their boards.

8. Turn pins into traffic.

Don’t overlook the opportunity to use Pinterest to drive traffic to your website. If you pin cool imagery and interesting content from your site to your boards, you’re basically seeding Pinterest with a lot of links back to your site.

You can also add the “Pin It” button to your site right next to your other social sharing buttons in order to make it as easy as possible for visitors to add images from your site directly to their boards.

And if something either you or one of your customers pins happens to become incredibly popular? Think of all the potential clicks back to your site!

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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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