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We’ve talked about how search advertising and display advertising can be used by marketers to communicate offerings and drive transactions, but there’s another way to do this by involving online influencers and bloggers: affiliate marketing.

Affiliate marketing is the process by which an online merchant provides commissions on purchases made by traffic originating from affiliated websites or social media accounts. Blogs, videos, social media posts and other content that are used to review, endorse, highlight or just plain talk about products are easy to monetized with affiliate marketing. 

Amazon pioneered this online business model in 1996. There were earlier affiliate programs, but Amazon created a system that made it easy for just about anyone to participate. In Amazon’s program, affiliates operate as a selling agent for Amazon’s products. As this is a form of advertising, Amazon categorizes its Associates program as a marketing expense in their investor reports.

How Do Affiliate Marketing Programs Work?

So how do affiliate programs work?

Every affiliate marketing program has three actors. The first is the consumer. This is the online shopper or, hopefully, buyer. The second is the publisher. This is the person who signs up to be the affiliate. They might run a blog, record videos, or post to social media. The third is the Advertiser or Merchant. They are trying to drive traffic to their site so they can sell their products or gather valuable leads. 

Let’s look at how this might play out. A Consumer is looking to buy a new laptop. One of the first places a consumer may visit in their search for a new laptop is Google for product information, or YouTube to watch product review videos, or even social media to hear thoughts from online influencers. In this scenario, the Publisher or Affiliate runs a blog and is looking to monetize the content on their website. The Publisher would likely join and affiliate program from the third actor, the Advertiser. The advertiser is an online merchant looking to sell laptops in their online store. 

So the Consumer visits the Publisher’s blog. The Advertisers runs advertising on the Publisher’s blog and after the Consumer clicks an affiliate link on the Publisher’s website leading to the Advertiser’s site and buys a new laptop, the Publisher then will collect a commission on the sale.

Now this is the exact sort of scenario you might see with a Publisher that belongs to the Amazon Associates program. Since Amazon operates their own affiliate program they can signup publishers directly. But creating and operating your own affiliate program can require a lot of resources, which is why many Advertisers decide not to create their own affiliate programs from scratch and instead work with a third party to manage the affiliate relationships and technical components. 

Affiliate Marketing Brokers

These third parties are called brokers. Advertisers sign up with Brokers to have them manage their affiliate programs and Publishers sign up with Brokers to help drive profitable traffic to the Advertisers through the Broker’s network.

CJ Affiliate is an example of an affiliate broker. They cater to both the publisher and the advertiser helping to promote a variety of products. 

At this point you might assume that all affiliate programs work basically the same. A Consumer has an interest in some product, encounters a Publisher’s site where the Consumer might click on a link that leads to the Advertiser’s website. While that may be true for a lot of affiliate programs, not all affiliate programs are based on a pay-per-sale model. In other words, not all programs benefit the advertiser through product sales.

Affiliate Marketing Pay Models

Let’s look at the different forms of Affiliate Pay Models.

First, is the Pay-per-Sale, which we’ve already discussed. If a consumer purchases something on the Advertiser’s site the Publisher will get a commission.

Next is Pay-per-Lead. Quite a few Affiliate programs are not based on getting someone to buy someone, but instead getting someone to try something, or ask for more information about something. In other words, affiliates are paid to generate leads. Often these are going to be leads for services that cannot be fulfilled through digital means.

Advertisers may also choose to run their programs using a pay-per-click model. If you recall, pay-per-click or cost-per-click is the model used in search advertising. So affiliate hyperlink that appears on the publisher’s website is tracked the same way as a search ad on a search engine results page.

Finally, pay-per-impression uses the same model as display advertising, but often without the graphical element. 

Pay-per-sale and pay-per-lead are very common forms of affiliate marketing, while pay-per-click and pay-per-impression are uncommon. Pay-per-impression is especially rare.

Let’s look at an example from the advertiser’s side and revisit the Amazon Associates program and look at what pay models Amazon uses. As you can see from their Program Fee Rates schedule, that they pay out at different rates based on the product category with Luxury Beauty product paying the highest commission rate at 10% and video games and video game consoles paying the lowest at 1%. If we scroll down the page and look at Amazon’s Special Program fees, you can see that Amazon will pay out dollar amounts for specific actions that a consumer might take, in other words pay-per-lead. For example, if you’re running a website and include a link to Amazon Business and your referral turns into a successful registration for an Amazon Business account, Amazon will pay you $15. Not too shabby.

But what do things look like from the Publisher’s side? 

Let’s visit one of the biggest Amazon Associates affiliates out there, Wirecutter. Wirecutter is a product review website that was purchased by the New York Times in 2016. The review a wide variety of products, but tend to focus on electronics and home items. As you can see, they review items and make their recommendations and—surprise, surprise—the links they embed take the user to Amazon. But how does Amazon know how to credit Wirecutter with a commission on a sale when the Consumer buys this product? 

Affiliate Marketing Tracking Mechanisms

Well, here’s a hint on the first method. There are actually two different affiliate tracking mechanisms used to accomplish this. The first is the Affiliate URL. When a hyperlink is embedded into a Publisher’s website, it contains a number of extra elements that tell the advertiser or merchant about the affiliate and other information. Let’s breakdown the elements of an affiliate URL. The first component is the Product ID. The is the most basic part of the URL and absolutely required for the URL to get the consumer to the product page. Next, is the affiliate ID. This is everything assigned the “tag” parameter, in this case “thewire6-20”. This is the minimum required for the advertiser to be able to assign a commission to an affiliate. The next two parameters are optional. The Campaign ID is useful for a Publisher to track commission income categorized into different campaigns. and finally, for established affiliates with a large number of repeat customers, like Wirecutter, the Customer ID allows the affiliate to break down their income based on specific customers.

The second mechanism used is a bit easier to implement and is typically used in places where a hyperlink might be impractical. Think of a sponsorship in a Youtube video. Affiliate code may often be referred to as coupon codes, but in addition to providing a discount to the consumer, they also provide referral income for the affiliate associated with the affiliate code.

Affiliate marketing has become a very attractive source of passive income for many online entrepreneurs and just going on the thousands of videos on the subject on Youtube, it shows no signs of letting up. Whether you’re an advertiser, publisher or just a consumer looking to buy something, affiliate marketing might be a great digital marketing solution for an additional revenue stream.

Retail research is something that all retailers should engage in, no matter how big or small. In this presentation, I’ll share why it’s important to do retail research, what the typical retail research subjects are, and we’ll look at some insights generated through research along the way.

Why do we do retail research? The insights provided by retail research  can help us anticipate shoppers’ needs and desires. You’d be amazed at how the small task of actually talking with customers can provide you big results. 

You can discover the points engagement and friction in the shopping process. If you sit and watch customers in your retail stores, you can quickly see where shopper become frustrated, the areas of the store they avoid, where they are most likely to congregate and other useful insights. 

You can also improve the retail experience for the customer and measure how shoppers respond. In essence, you retail stores can become a place of experimentation to help you improve your operations and increase customer engagement.

As retail researchers, the three big areas you are likely to study are shopper behavior (what your shoppers do while they’re in the store), atmospherics (how the physical environment impacts the shopper), and purchase patterns (what shoppers tend to buy together, what is purchased certain times of day, or the seasonality of products). 

Let’s take a break to look at a research insight from Why We Buy by Paco Underhill. Endcaps are a great merchandising tool for retailers to use and there are a number of benefits to their use. One is that shoppers must pass them as the enter an aisle. Chances are it’ll be the only merchandise that is perpendicular to their vision as they enter the aisle so it automatically stands out. This means that merchandise on an end-cap nearly always sees a sales boost. But the only problem is, there are only two per aisle, so use them wisely.

Shopper Behavior

Ok, let’s look in-depth at shopper behavior. What we do as shoppers is chock full of useful information for retailers. The shopping lists with carry (or don’t carry), how long we stay in the store and the type of shop we do, how many products we buy, or basket size, the decisions we make while in the store, how we move around the store, and so on. All of our behaviors and decisions say a lot about us, but also provide valuable data to retailers, who, if they’re smart, will try to turn that into actionable insights. 

Speaking of shopper behavior, let’s actually take a look at what American shoppers do in mass market retail stores. The following data are from the Point of Purchase Advertising International Mass Merchant Shopper Engagement Study. This organization periodically runs this study, the most recent one was 2014, and they have uncovered some interesting insights. Mass market retailers, by the way, are large retailers that sell a large variety of products. For this study, it was retailers that sold groceries as well as other products. Think Walmart, Super Target, Kroger Marketplace, etc.

First, is shoppers’ use of shopping lists and so-called pre-store media. As you can see by the data in red, mass merchant shoppers rely far less on written shopping lists and are much more likely to have no list at all compared to the data for grocery store shoppers in blue. We can also see that mass merchant retail customers are a lot less likely to use pre-store planning media, in other words, store circulars and newspaper inserts. Imagine how useful knowing this information would be if you were a store manager. You’d know that mass merchant shoppers were probably going to make more impulse buys and you could probably stop wasting money on in-store circulars.

The report also sheds some light on typical based basket for shopper trips. Interestingly, the break down the different types of trips that shoppers take, fill-in trips, quick trips, and stock-up trips.

Finally, and I think this is one of, if not the most, interesting insights from their report: in-store decisions. You can imagine that if shoppers don’t use shopping lists, then they are more likely to make their purchase decisions while they are in the store. And you’d be right. From this report, we can see that only 18% of purchases that shoppers made were specifically planned, meaning that 82% of purchases were made with an in-store decision. The in-store decision can vary from knowing you want to buy spaghetti sauce, but you’re not sure what brand to buying something purely on impulse that you had no idea you were going to buy when you entered the store.

Atmospherics

Atmospherics are another important area where we can uncover valuable insights in the retail environment. What lighting will keep your shoppers in the store longer?What colors coordinate with your products most effectively? What sounds and music put shoppers in a more comfortable and receptive mood? What smells can make your shoppers hungry? What fixture, carpeting, and furniture textures will make your shoppers feel more welcome? Heck, even taste! What tastes will make your shoppers want to come back? Think free mints at checkout or even food samples throughout the store. Atmospherics are hugely important to retailers, but the retail space is a blank canvas just ready for a retail design artist to make the right decisions that will lead to longer shops, largest basket sizes, and happier shoppers.

Here’s a video that shows how shopping malls think about attracting customers and keeping them in the shopping environment.

Purchase Patterns

Finally, purchase patterns are an important insight for retailers because they can tell us a lot about what products are bought together. This can help when merchandising products and creating purchase synergies through adjacencies. Retailers can also see how often products are purchased by individuals, when products are typically bought, and by whom. These are great insights to help a retailer provide targeted promotion for the individual shopper such as coupons.Product purchases can also help retailers predict the life stages on specific shoppers. 

There’s a famous article written in the New York Times titled, How Companies Learn Your Secrets, about how Target used product purchase patterns to predict a teenage girl’s pregnancy, much to the dismay of her father. It’s an interesting read.

One more shopping insight from Why We Buy. At grocery retailers, the use of shopping carts is common. But oftentimes, shoppers don’t want to travel all the way down an aisle for a product with their cart. They often leave the cart at one end, walk to the middle of the aisle, and the return to their cart. Paco Underhill noticed this common shopping practice and named it the “boomerang effect.” One of the ways that retailers can encourage shoppers to traverse the entire aisle is by putting the most popular items towards the center of the aisle. That way the see more products on the way to what they want, increasing the likelihood that they’ll make another unplanned purchase.

By the way, we shouldn’t forget about online retail. 51% of Americans prefer to shop online, but online purchases only make up 16% of retail purchases. That means there’s a lot of retail research left to be done to figure out what it will take to push those shoppers over the edge and get them to buy more online.

To recap, we do retail research to understand consumer needs and desires, discover points of engagement and friction, and improve the customer’s experience. The subjects of most research in the retail realm are shopper behavior, atmospherics, and purchase patterns. And finally, while 51% of Americans prefer online shopping, only 16% of retail purchases are made online, meaning there’s much more retail research to be done!

So what are infographics? You may have heard this term before as it’s something that comes up quite a lot within digital marketing. You may have even seen some examples before. They are the combination of data visualizations, illustrations, and text used to communicated a specific topic. The term infographics used to be used synonymously with data visualization, but its use in content marketing has given it a more specific meaning now. In this video we’re going to walk through the four things that successful infographics do.

Tell A Story

First is, Tell a story. Consumers get more emotionally invested in a subject when they can hear a story. And that story narrative can do an affective job of pulling a reader through the story.

As we look at the infographic on the right, notice how this story of an animal foster parent and her pet is told in narrative fashion. We can literally follow the red path through their story and we arrive at the most important detail of the story, the outcome of the fostering process and how the reader can get involved. Overall, the story should be simple and easy to follow.

This infographic fails on both the simple and the easy to follow. Your eye does not know where to begin reading and it’s a bit of a visual jumble.

Put Info First

We also want to Put Info First. The information or data of your infographic should be the most important element. Design should always take a back seat to the content. If you’re going to tell a story, and you should, then the narrative should be structured with your information. 

You shouldn’t create an arbitrary structure and try and fit the data to it. Notice at the bottom of this infographic how the source of the data is given and actual details about how the data was generated. It’s always a good idea to cite your sources.

This example is probably one of the worst offenders in terms of not putting the information first. Not only is the actual content minimized, is so visually confusing it’s difficult to interpret as well. It’s certainly clever from a design standpoint, but is this really serving the data or is the data serving the design?

Make It Visually Engaging

Your building an infographic. Of course you want the design to be done well. You want to ensure that you’re using design best practices. Thinking through the color theory. Ensuring the best usage of typography. Giving the readers eyes room to digest information be providing adequate white space. 

That’s what makes this example so bad. The colors don’t work well. A mustard yellow background? Really? Green titles? There’s no white space. The text is dense and line spacing too tight. This really is a mess to look at. And what do these design choices have to do with the story or content being discussed. Overall, the design is just incoherent.

Contrast that with this design. Everything is well-organized. The use of color and typology help with communication rather than hinder.

Facilitate Sharing

Finally, infographics are an important communication vehicle on the internet and their popularity has exploded with the proliferation of content marketing. If you’re trying to get your message out—and you should be—then you need to provide your readers and easy mechanism for sharing your infographic. Utilize the technology you have available to you to help the reader share your infographic using whatever social media or communications platform you can.

To recap, your infographics should tell a story. Stories make your message easier to remember. You need to Put Info First. Design should always take a back seat to your actual information and data. Make your infographic engaging. Your design should be visually coherent and follow design best practices. And you should facilitate sharing. Help your readers spread your message as far and wide.

Data visualization is the practice of placing data in a graphic format to help convey the data’s significance. We also use the term data visualization to refer to the graphic itself, so it’s both a practice and the outcome of that practice. Data visualization or DataViz as some call it, is important because some patterns that might go unnoticed in tabular, text, or statistical form are more easily communicated and understood visually. DataVix is a crucial skill for those working with large datasets who need the ability to communicate the importance of that data…and that’s pretty much everyone in business these days. Let’s look at a few important reasons why dataviz is so crucial.

90% of information transmitted through the brain is visual in nature. As mammals, we are designed to take in information through our eyes. If we can format that data in such a way that it makes it easier to communicate and easier for the recipient to understand, why wouldn’t we?

Our brains also process images in as little as 13 milliseconds and visuals are processed 60,000 times faster than text . This means that the time it takes to comprehend complex data can be significantly decreased if we put that data in a format optimized to communicate visually. That’s dataviz!

Now that’s interesting and all, but how does that help us as marketers?

Presentations using visual aids are 43% more persuasive than those using text alone. And persuasion is the business we marketers are in.

Blog posts and articles with visuals perform 91% better than those without. It’d be silly to use blogging and content marketing and not include a visual component to ensure that your content is memorable.

Data Visualization Types

Let’s briefly go over the different categories of data visualizations from our reading, A Tour Through the Visualization Zoo.

Statistical

First are statistical visualizations. These visualizations take large datasets and use a variety of techniques to help make sense of the data, hopefully exposing patterns that we can use in some way. Scatter, violin, frequency or histogram, and box plots are typical examples.

Time-series

We also have time-series visualizations. We typically think of these as timelines. These visualizations organized items or events temporarily. In Western cultures, this would typically mean reading left to right as we move from the past to present. The ubiquitous stock value returns graph is another example, but notice this is also a line-graph. If a line graph is showing time-based information, we would consider it a time-series data visualization and not a statistical data visualization.

Maps

If the data is geographic in nature, then you can plot the information using the map type data visualization. For example, here’s a map showing the most well-known brands from each state. And another showing Doctor’s pay in America. Or a map showing the origins of articles in Wikipedia.

Networks 

Network maps show the interconnectedness between data points such as this visualization showing the financial connections between CEOs at the top Silicon Valley tech firms.

And while you might think this famous London Underground visualization is a map, it’s better described as a network data visualization because the actual line and station information is divorced from actual geographic placement. Does having a perfectly accurate representation of the distances between stations really matter to the passenger? No. This map shows only the information that’s really needed for the passenger and eliminates everything else extraneous. But this visualization does show the interconnectedness between the lines and stations quite effectively. 

In fact, this is what the London Underground map would look like if it was actually mapped geographically. Doesn’t exactly enhance communication and understanding does it?

Hierarchies

Finally, hierarchical data visualizations are similar to network visualization in that they show the interconnectedness between the data, but these data visualizations also show how portions of the data fit within or emerge from each other such as this family tree diagram of the Kennedy family. Or how pints, quarts, gallons and other forms of measurement fit within each other. Oh, and it’s quite possible, and rather common, to combine data visualization types together such as this statistical line graph that shows a time series. Or this front page visualization from The New York Times

Lying with Data Visualizations

Now that you’re familiar with the different types of data visualizations, there’s one more bit of information that’s important for you to know: 

how easy it is to lie with data visualizations. Perhaps you’ve heard the saying, “There are three kinds of lies: lies, damn lies, and statistics”? Don’t think because data is in a form intended for easier communication and understanding that it can’t be manipulated. Data visualizations are actually very easy to manipulate. Here are a few examples and the methods used to mislead, so you can know what not to do and how to avoid falling victim to it.

First, is ignoring conventions. We all know what a pie chart is right? It’s supposed to add up to 100%. So what does a pie chart mean that totals up to more than that? It doesn’t make much sense. This example is obviously wrong because the percentages are far too large. But what it the numbers didn’t seem wrong because the percentages were only subtlety too large. That can be a big problem and very confusing.

You can also hide negative trends but obscuring them in cumulative totals. Notices how the graph on the right looks so good. Everything’s great. Our revenue is growing like gangbusters. The graph on the right tells the true story. Yes, revenues are still in the positive but they are declining. Cumulative charts like the one on the left can hide all sorts of bad news. Don’t get suckered into believe them at first glance.

Omitting data points is another way to hide what’s really going on. For example, the graph on the left makes it look like it look like steep uninterrupted growth followed by consistent results. The reality is more complex and not a rosy. When you see a graph missing crucial data points like this, especially if it’s yearly results, question why. It could be someone is trying to fool you.

A very common approach to manipulating the visual display of results is truncating the y-axis. Really it could be either axis, but the y-axis is more common. The graph on the left makes the revenue results look a lot more dramatic. But when scaled correctly and the entire y-axis displayed, the truth is less impressive. Often this sort of misleading data visualization is not done intentionally. Typically, someone wants to show how some data series has changed, but because the amounts of change are so small, they end up visually amplifying those changes by truncating the y-axis. 

Finally, this is the most egregious example of lying through data visualization that I’ve ever seen. There’s virtually zero chance that the person who put the graph together didn’t know exactly what they were doing. Have you figured it out yet? It looks like Gun deaths in Florida went down after the “Stand Your Ground” law was passed in 2005, right? It may seem that way until you realize that 

The y-axis was flipped vertically. Now zero is at the top and 1000 is at the bottom. This is another example of defying conventions, but so bad it deserves its own category. The lesson to be learned here is that graphs that accompany politically charged stories should probably receive more scrutiny.

To recap,

Data visualization is crucial for business managers as it can help you see patterns and relationships that the raw data may not easily show.

It is both a process and an outcome.

There are five types of data visualizations: statistical, time-series, maps, networks, hierarchies

Data visualization types can be used in combination

Data visualizations can be used to mislead. Make sure you give extra scrutiny to visualizations in politically-charged topics.