We are the digital agency
crafting brand experiences
for the modern audience.
We are Fame Foundry.

See our work. Read the Fame Foundry magazine.

We love our clients.

Fame Foundry seeks out bold brands that wish to engage their public in sincere, evocative ways.

WorkWeb DesignSportsEvents

Platforms for racing in the 21st century.

Fame Foundry puts the racing experience in front of millions of fans, steering motorsports to the modern age.

“Fame Foundry created something never seen before, allowing members to interact in new ways and providing them a central location to call their own. It also provides more value to our sponsors than we have ever had before.”

—Ryan Newman

Technology on the track.

Providing more than just web software, our management systems enhance and reinforce a variety of services by different racing organizations which work to evolve the speed, efficiency, and safety measures, aiding their process from lab to checkered flag.

WorkWeb DesignRetail

Setting the pace across 44 states.

With over 1100 locations, thousands of products, and millions of transactions, Shoe Show creates a substantial retail footprint in shoe sales.

The sole of superior choice.

With over 1100 locations, thousands of products, and millions of transactions, Shoe Show creates a substantial retail footprint in shoe sales.

WorkWeb DesignRetail

The contemporary online pharmacy.

Medichest sets a new standard, bringing the boutique experience to the drug store.

Integrated & Automated Marketing System

All the extensive opportunities for public engagement are made easily definable and effortlessly automated.

Scheduled promotions, sales, and campaigns, all precisely targeted for specific demographics within the whole of the Medichest audience.

WorkWeb DesignSocial

Home Design & Decor Magazine offers readers superior content on designer home trends on any device.

  • By selectively curating the very best from their individual markets, each localized catalog comes to exhibit the trending, pertinent visual flavors specific to each region.

  • Beside the swaths of inspirational home photography spreads, Home Design & Decor provides exhaustive articles and advice by proven professionals in home design.

  • The art of home ingenuity always dances between the timeless and the experimental. The very best in these intersecting principles offer consistent sources of modern innovation.

WorkWeb DesignSocial

  • Post a need on behalf of yourself, a family member or your community group, whether you need volunteers or funds to support your cause.

  • Search by location, expertise and date, and connect with people in your very own community who need your time and talents.

  • Start your own Neighborhood or Group Page and create a virtual hub where you can connect and converse about the things that matter most to you.

775 Boost email open rates by 152 percent

Use your customers’ behavior to your advantage.

772 Claim a bigger piece of the mobile e-commerce pie

Boosting your mobile e-commerce conversion rates is easier than you might think.

December 2016
By Kimberly Barnes

Going the Distance: Four Ways to Build a Better Customer Loyalty Program for Your Brand

Loyalty programs are no longer a novelty. That means that yesterday’s strategies won’t work moving forward, so look for ways to rise above the noise, setting yourself apart from the cloying drone of countless other cookie-cutter programs.
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Going the Distance: Four Ways to Build a Better Customer Loyalty Program for Your Brand

article-thedistance-lg It’s easy enough for a customer to join your loyalty program, especially when you’re offering an incentive such as discounts. All your customer has to do is give out some basic information, and voila! They’re in the fold, a brand new loyalty member with your company. From there, it’s happily ever after. You offer the perks; they stand solidly by you, bringing you their continued business. Simple. Or is it? In reality, just how many of those customers are act ively participating in your loyalty program? Do you know? Sure, loyalty program memberships are on the rise according to market research company eMarketer, having jumped 25 percent in the space of just two years. However, that figure may be a bit misleading. The truth is that, while loyalty program sign-ups may be more numerous, active participation in such programs is actually in decline. At the time of the study, the average US household had memberships in 29 loyalty programs; yet consumers were only active in 12 of those. That’s just 41 percent. And even that meager figure represents a drop of 2 percentage points per year over each of the preceding four years, according to a study by loyalty-marketing research company COLLOQUY.

When discounts just aren’t enough

So what’s a brand to do? How can you make your loyalty program worth your customer’s while—as well as your own? After all, gaining a new loyalty member doesn’t mean much if your customer isn’t actively participating in your program. Consider this: Does your customer loyalty program offer members anything different from what your competitors are offering? Chances are your program includes discounts. That’s a given. And what customer doesn’t appreciate a good discount? But when every other company out there is providing this staple benefit in comparable amounts, it becomes less and less likely that customers will remain loyal to any one particular brand. Frankly, it’s all too easy for customers to get lost in a sea of loyalty member discounts. They’re everywhere. In fact, just under half of internet users perceive that all rewards programs are alike, according to a 2015 eMarketer survey. The key to success, then, is to differentiate your business from the crowd. If you can offer your customers something unique and valuable beyond the usual discount, chances are they’ll be more likely to stick with your brand. Here’s some inspiration from companies who get it.

Virgin: Reward more purchases with more benefits.

That’s not to say you need to get rid of discounts entirely. In fact, nothing could be further from the truth. Customers still love a good discount. The goal is to be creative in terms of the loyalty perks you offer. Take the Virgin Atlantic Flying Club, for example. As part of its loyalty program, the airline allows members to earn miles and tier points. Members are inducted at the Club Red tier, from which they can move up to Club Silver and then Club Gold. Here, it’s not just a discount. It’s status. And people respond to feeling important, elite. Still, even where the rewards themselves are concerned, Virgin is motivating loyalty customers with some pretty attractive offers. At the Club Red tier, members earn flight miles and receive discounts on rental cars, airport parking, hotels and holiday flights. But as members rise in tiers, they get even more. At the Club Silver tier, members earn 50 percent more points on flights, access to expedited check-in, and priority standby seating. And once they reach the top, Club Gold members receive double miles, priority boarding and access to exclusive clubhouses where they can get a drink or a massage before their flight. Now that’s some serious incentive to keep coming back for more. Discounts are still part of the equation – but they are designed with innovation and personal value in mind, elevating them to more than just savings.

Amazon Prime: Pay upfront and become a VIP.

What if your customers only had to pay a one-time upfront fee to get a year’s worth of substantial benefits? It may not sound like the smartest business idea at first glance. But take a closer look. Amazon Prime users pay a nominal $99 a year to gain free, two-day shipping on millions of products with no minimum purchase. And that’s just one benefit of going Prime. It’s true that Amazon loses $1-2 billion a year on Prime. This comes as no surprise given the incredible value the program offers. But get this: Amazon makes up for its losses in markedly higher transaction frequency. Specifically, Prime members spend an average of $1,500 a year on Amazon.com, compared with $625 spent by non-Prime users, a ccording to a 2015 report from Consumer Intelligence Research Partners.

Patagonia: Cater to customer values.

Sometimes, the draw for consumers isn’t saving money or getting a great deal. The eco-friendly outdoor clothing company Patagonia figured this out back in 2011, when it partnered with eBay to launch its Common Threads Initiative: a program that allows customers to resell their used Patagonia clothing via the company’s website. Why is this program important to customers? And how does it benefit Patagonia? The company’s brand embraces environmental and social responsibility, so it was only fitting that they create a platform for essentially recycling old clothing rather than merely throwing it away. The Common Threads Initiative helps Patagonia build a memorable brand and fierce loyalty by offering its customers a cause that aligns with deep personal values. OK, so their customers get to make a little money, too. Everybody wins.

American Airlines: Gamify your loyalty program.

If you’re going to offer your customers a loyalty program, why not make it f un? After all, engagement is key to building a strong relationship with your customer. And what better way to achieve that goal than making a game of it. American Airlines had this very thing in mind when it created its AAdvantage Passport Challenge following its merger with USAirways. The goal: find a new way to engage customers as big changes were underway. Using a custom Facebook application, American Airlines created a virtual passport to increase brand awareness while offering members a chance to earn bonus points. Customers earned these rewards through a variety of game-like activities, from answering trivia questions to tracking travel through a personalized dashboard. In the end, participants earned more than 70 percent more stamps than expected – and the airline saw a ROI of more than 500 percent. The takeaway: people like games.

Stand out from the crowd.

Your approach to your customer loyalty program should align with your overall marketing approach. Effective branding is about standing out, not blending it. Being memorable is key. To this end, keep in mind that loyalty programs are no longer a novelty. That means that yesterday’s strategies won’t work moving forward, so look for ways to rise above the noise, setting yourself apart from the cloying drone of countless other cookie-cutter programs.

774 Feelings are viral

Feelings are the key to fueling likes, comments and shares.

June 2012
By Sufyan bin Uzayr

From Panda to Penguin: How to Practice Safe SEO Today

Make sure your site's performance in organic search results doesn't fall victim to the latest updates to Google's algorithms.
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From Panda to Penguin: How to Practice Safe SEO Today


Anyone who has had some exposure to the internet knows the importance of Google. After all, as the world's single most important search engine in terms of user base and popularity, Google wields considerable power to make (or break) any website.

Time and again, Google makes changes to its SEO algorithm, in order to improve its search functionality and usability. Thus, while earlier it was an attack on paid links, last year Google came up with the Panda update that effectively tackled websites which were mere content scrapers or low-level affiliates.

While the impact and implications of Google Panda have been discussed all across the internet multiple times, certain newer changes in SEO algorithm are still relatively lesser known. In this article, we focus on the newest change – the Over Optimization Penalty, and how to tackle it.

What is it about?

To quote Google's Matt Cutts, certain websites are often built keeping search engines in mind, and thus many SEO folks have sites that are “over optimized”, or in other words, “overly SEO-ed”. In short, the axis mundi of Over Optimization Penalty is to target and punish websites that focus more on SEO and less on content quality.

Yes, that's right. With search engines controlling a good deal of incoming traffic for almost any website, many site owners publish content keeping Google and Bing in mind, not their website visitors. In other words, SEO becomes the King, while content takes back-seat. It is this very practice that Google's recent Over Optimization Penalty patch aims to hit at. The motive is to “level the playing field” and crawl websites that offer quality content, not quality SEO.


How does it affect me?

Before going any further, let me present you with (my version of) a handy guide to Search Engine Optimization.

At the most basic level, SEO deals with analysis of data related to your website, so that you can assess what interests your website's visitors the most, what makes them visit your site, which topics are popular (and which aren't), and so on. Once you have such data, you can optimize or tweak your website to provide your visitors with information that they prefer, and avoid information that they don't like.

For instance, say, you are running a website about coffee. Now, you notice that most visitors to your website come by searching for terms such as “how to make awesome coffee”, and not “utensils for coffee”. Thus, you can focus more on preparation guides for coffee, rather than offering advice about purchasing coffee mugs. Similarly, you realize that your visitors are keen on knowing about the production of coffee all across the globe, and you can further provide such informational articles.

This is where over optimization comes into play. In your bid to get more and more visitors, instead of simply providing awesome coffee-related articles, you may also resort to repeatedly offer technically similar or 'SEO-friendly' articles about the history of caffeine, which may or may not be totally useful.

Good SEO is about content, proper coding standards and information hierarchy, and definitely not just about extra keywords.

So what should I do?

Avoid excessive usage of keywords.

The crux of the Over Optimization Penalty is to promote websites that do not play a handicap match by relying on keywords more than the actual content itself. Of course, keywords still matter – but you should not stuff them or fall prey to the 'keyword density' gimmick.

Avoid unnecessary "networked" links.

Let's say you have 10 websites, and you've created a 'network' out of them. Now, if only you can cross link within this network of websites, your traffic will increase – after all, users visiting the first site will be like, “Hey there's more to this network. I gotta visit 'em all!” Right? Sadly, not anymore. Google has been going tough on websites that are abusing interlinking.

Avoid backlinks from uncanny locations.

In other words, avoid link spam, period.

Avoid spending days and nights to 'comprehend the algorithm'.

Do not create content that satisfies Google's search algorithm – instead, spend time creating content which meets the expectations of your users. Google will automatically follow suit and take notice of your hard work. Surely, many SEO experts can claim to give you instant traffic boost and content promotion – but rarely do such tricks work in the long run.

Update your old posts and articles.

If your website has older articles and posts which have a good rank in terms of SEO, it is worth updating them – not necessarily a re-write, but check for broken links, outdated information, etc.

Build links the proper way.

Yes, properly employed link-building techniques can be effective in promoting your website. Certain measures such as writing guest posts and posting relevant comments on websites that are similar in genre to yours can be fruitful.

Implement a healthy on-site strategy.

It goes without saying that simple and clean code, along with validated HTML and CSS promotes better crawling of your web pages. Also, it makes sense to employ plugins and methods to make your pages load faster. Good load times almost invariably lead to better traffic. Similarly, HTML5 and responsive web design are the way to go, like it or not!

Employ social networking.

Websites such as Twitter and Facebook are ideal for viral campaigns – this is a well known fact. Further more, just in case you haven't noticed, Google is now keeping social networks in mind when assessing the importance of a website – in any search page, you can see the +1 buttons under each result, thereby allowing users to like or dislike a website in one go. Naturally, you'd not want to miss out on the social networking front.


Keep track.

Google itself offers a plethora of tools to aid you in your quest to promote your website – for instance, you can consider using Google Analytics and Google Webmaster Tools to your advantage.


Follow the golden rule of good SEO

So, what's the final word? Well, it's pretty simple, actually – Google is trying to offer search results that are clean of subpar content. Your best bet is to create content for humans, not search engines, so make sure you always write for people, not crawlers.

September 2014
By Kimberly Barnes

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

Machine learning may sound like science fiction, but in fact, it’s the new reality that’s redefining marketing and e-commerce.
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Intelligent Design: Transform Your Website into a Sales Engine with Machine Learning

computer-brain 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...” Amazon2 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. TrueFit 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.