Four Fears That Sink a Website

Your website is one of the most important tools in your business growth arsenal. However, website development is a complex science, and there are any number of opportunities for the process to go awry. Following are four common decision points where uncertainty or indecision can compromise the execution of good design, content and functionality, resulting in a site that doesn’t perform.

Not catering to every possible customer and every imaginable need

You never want to waste the opportunity to gain a new customer. When you think about all the people sitting in front of a keyboard who could potentially land on your site, it’s difficult not to want to swing for the fences. However, the penalty for trying to appeal to everyone is that you’ll appeal to no one. You’ll end up with bland, unfocused content that speaks in broad generalities rather than razor-sharp sales copy that addresses key points. It’s critical to think about the type of person who falls within your core target audience, how they most likely arrived at your site, what their level of familiarity with your product or service is, and what is required to convince them to take the next step – whether that’s submitting a contact form, picking up the phone or making a purchase. When you’re honest and realistic about who you’re really speaking to, you can build your site around powerful sales messages that hit home and compel action rather than settling for an insipid and ineffectual approach that fails to motivate anyone to do anything.

Not addressing every question on the home page

This is the corollary to the fear of not serving every possible visitor. You’re afraid that if every potential question that someone could have is not addressed as soon as they land on your home page, you’ll lose them. The result is a cluttered mess, and the reality is that you’ll turn away more customers than you’ll win because no one will be able to find what they’re looking for. It’s important to divide your website visitors into audience segments based on their needs and motivations and provide funnels for each user type that point them to the tools and information contained below the surface of your site that are most relevant to them. For example, if you’re a non-profit, chances are that you have three primary audience segments: prospective clients, prospective donors and prospective volunteers. The only two jobs your home page must accomplish are conveying your mission, so that all of these groups understand who you are and what you do, and providing clear signposts that guide each segment to content within your site that is tailored to their specific needs. Website users are in no way averse to clicking and navigating; they just need your help in knowing where to go.

Not providing enough information to close the sale

Unlike when you’re face-to-face with a prospective customer, when someone is browsing your website, you don’t have the ability to adjust and tailor your sales pitch on the fly based on the flow of conversation. As a result, the tendency is to include any and every detail possible within the copy on your website in order to make sure you address all possible questions and sales objections. After all, if someone can’t find what they’re looking for on your site, they’ll give up and you’ll never hear from them again, right? Wrong. When you provide too much information, it makes it difficult for users to find anything of real use or value to them. In the culture of the Web where time and attention spans are severely limited, “less is more” is a universal truth – as long as that “less” is well-chosen and well-crafted. You simply can’t afford to put every detail about your product, service, company or brand on your site. Instead, you must make smart choices and be strategic in the way you present information on your website so that you capture visitors’ interest provide the best possible user experience. By stripping down your content to only that which is most relevant and most useful to your target audience, you’ll make the good stuff more prominent and make it easier for users to find exactly what they’re looking for. Brief, powerful, well-organized copy will win out every time over page after page of verbose, indirect, indecipherable content. Read more: Ten Secrets of Must-Read Copy

Not doing everything the competition is doing

It is the curse of anyone charged with the task of growing a business to obsess over the competition. The Web only intensifies this fixation because everything is highly visible. It’s tempting to make sure that your website does everything in exactly the same way as your competitor’s because it’s right there in front of you. Or is it? You don’t know the motivations – business growth driven or otherwise – that determined why they chose to go one route over another. You also aren’t likely to know if they have a great web architect directing them or if they’re just grasping at straws and trying to capitalize on every web design trend du jour. If their site features bells and whistles that yours doesn’t, that doesn’t necessarily put you at a disadvantage. For example, you might envy the colorful, eye-catching animation on your competitor’s website. But what you may not realize is that those effects were created in Flash and are therefore invisible to anyone who might be trying to access their site on an iPhone or iPad. Moreover, you may be competing for some of the same customers, but that doesn’t mean that your business models are the same. Their strengths are not your strengths, and your long-term growth plans may be leading your company in a different direction. You need to ensure that your site serves your business growth objectives – present and future – not theirs. Let them do what they want. If you stay true to your own goals and your own well-founded knowledge of your customers, you’ll win in the end.

Need a second opinion?

If your website isn’t bringing you new customers every day, something’s amiss. Find a business-growth-oriented web development firm that specializes in web design and user interface to partner with you and steer your site back on course to work for you.

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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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