As a retailer, how can you use science to ensure you keep an unfair advantage in the world of Sponsored Product Ads (SPA)?
At Conversion Sciences, our job is to redesign websites using data. This allows us to guarantee that our redesigns will improve results: regardless of the optimization goal (lead generation, purchases, long-term value etc).
Let’s dive into an example. Back in November 2012, retailer Finish Line chose to relaunch its website. As you can see in the before and after pictures, it delivered a visual treat. Very stylized graphics, high-quality images, and dedicated blog content. In short, it looked super slick.
But within a few weeks, the retailer had lost around $3 million in sales. How can this happen? After all, it had an impressive agency, a huge budget, and an executive team that knew its customers and products inside out.
We like to call this the “law of unintended consequences.” And this law helps us to understand whether what we’re doing causes things to go north…or south.
Whenever we decide to buy something, a specific impulse kicks in. It urges us to find a way to delay – just a little bit – in order to relieve anxiety. Broadly speaking, there are two types of buyers in the world:
Transactional buyers’ greatest fear is to buy something for that dollar more than they might otherwise save. They see shopping around as part of the experience. For this group, they accept finding and buying products online as a full contact sport. They want to be the experts.
For relational buyers, their greatest fear is buying the wrong thing. The longer it takes to find the product they want, the more it costs them (or at least, the bigger the perception of how much it costs). They look for experts to help guide them.
Placing a sponsored ad on a site triggers danger for transactional buyers. We run the risk of them wondering if they should hunt for a product elsewhere. After all, for this group, visiting five websites to get the best deal comes as part of the fun.
Sponsored ads can provoke relational buyers, too. Being taken to another site may have them second-guessing as to the right place to buy the product.
Retailers can often worry when someone else has control over their website. Sponsored Ads rest on external control over our product and category pages. Things may not go as well as expected. In this instance all my team had to do was turn on an ad blocker.
CC: Conversion Sciences™
CC: Conversion Sciences™
Slow loading times cause extra headaches for mobile users; as a retailer, it’s worth considering when you bulk out your product and category pages. Think of how fast your thumb is when it comes to scrolling. Check out any scroll report on a mobile device and you’ll see how quickly shoppers get all the way down the page. Sluggish load times that fail to keep up with thumb-speed can frighten shoppers away.
And Sponsored Ads can push relevant content further down the page, leaving it stacked. If a publisher’s vendors do a good job with ad relevancy, no problem. But they must be completely confident of this.
Case Study: Accelerating the customer journey
Conversion Sciences tested the efficacy of a website that sold magazine ads. Using a simple A/B test, we removed a very stylistic banner area. With its products now further up the screen, shoppers could accelerate their journey along the page.
This resulted in an 18 percent increase in subscriptions.
Takeaway: Let shoppers see what they’re looking for! If your ad networks aren’t making the right judgement calls – i.e. relevant content gets forced down the page - it could hurt your revenues.
The more opportunities retailers have to monetize their traffic, the bigger the cognitive pressure for shoppers. Psychologist Daniel Khaneman articulates two decision-making systems in the brain:
Each of us has a lizard-like limbic brain: our instinctive, fight-or-flight system. We also have an alternate (which kicks into gear when buying products). This version makes decisions logically as opposed to based on emotion – but takes more energy to run.
To avoid triggering limbic-based decisions, retailers need to avoid overloading shoppers with information. Think of all the different items potentially in the way, from “Customers also considered,” to “Customers also bought these products,” to “recently viewed products.” Is there cognitive room in our visitors’ heads to accommodate Sponsored Ads there, too?
When we add sponsored ads, are we causing a reduction in transactions? When we add additional items for shoppers to process, do we lose out on transactions? Actually, we can find out:I’d like to introduce a couple of tools that, hopefully, won’t seem strange to you. First of all: heat maps. These run under a site allowing marketers to see where people are moving on a page. We can see where they’re clicking, and how far they’re scrolling. This counts for groups of people as well as individuals. As a result, we can get a large quantifiable sample-size.
I’d like to introduce a couple of tools that, hopefully, won’t seem strange to you. First of all: heatmaps. These run under a site allowing marketers to see where people are moving on a page. We can see where they’re clicking, and how far they’re scrolling. This counts for groups of people as well as individuals. As a result, we can get a large quantifiable sample-size.
We can also use heat maps to see if people are even reaching that part of the page. Check out the product page for desktop and mobile (above). It has a scroll problem. At the bottom we see related products, represented by red-hot areas – most people are seeing this section. But the dark blue and black area represent only, say, 5 or 10 percent of potential audiences. Armed with this knowledge, we can begin to diagnose what happens as we start adding things to our product pages.
A/B testing controls for almost every variable you might imagine. It ensures you get statistically significant results. It helps publishers understand how everything done to a site impacts the bottom line.
And it’s a great way to measure expectations. If I make a dollar on ads, am I getting an increase on order value? Or if I’m making a dollar on sponsored ads, will there be a decrease in the long-term value of the customers who see those ads?
The bulk of our more successful clients no longer optimize for revenue-per-visit. Rather, they know that, if they can secure just one customer, it doesn’t matter how big that order is, just that they can cultivate it into longer-term value.
Discovering how optimal a sponsored ad is remains simple. We A/B test them (first person sees them, the second doesn’t) we’ve generated a statistically significant representation. At this point, we can see which scenario sold the most products.
If all is well, it becomes a case of finding the optimal place for customers to find sponsored ads. Here we can try a number of things. Size, placement and title can all help to boost the amount of attention a sponsored ad receives.
Only by reading between the lines can publishers get the most from Sponsored Ads. Be warned that they can increase loads times, introduce irrelevant content, and add to cognitive load. Each of these factors can cost more in lost transactions than they make in sponsored ads revenue. However, A/B testing and heatmap tools can make the difference. These allow us to test ad quality – and give us an insurance policy against any action your audience wouldn’t be happy with.