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This was really interesting. Thanks for posting it. Does anyone know of a place to find similar content? (Analysis of web trends and practices from a data driven perspective.)
I'm missing 'authority' as way to improve conversion. Funny that they use it themselves in two ways: letting PWC check the results and, in a milder form, using a scientific way of communicating the results (LaTeX, article layout etc). The impact would have been less if it was just a blog post :-). I'm curious about results on authority, maybe someone from qubit can give us some insights on that?
At my company[0] we offer a solution to sites to implement these strategies through notifications/nudges. Having said that: we firmly believe in A/B testing but we believe even more in recognizing (we do that through machine learning) what technique works best on a personal level. This means that a site can have, for example, two strategies and that we apply none, either one or both on the visitor. That way you can reach higher uplifts.
tl;dr: The 3 items possibly statistically significant are: - Saying there are just a handful items left in stock (+2.9% revenue per client) - Saying other people are watching this product (+2.3%) - Time limited offer (+1.5%) I did not see mention of combining these factors. I doubt the gains are cumulative. My main takeaway is that most optimizations are not worthy if you have the opportunity to spend your time/money…
1. It's not just about items in stock. "Our SomeNonprofit membership program has just 10 places left at the platinum level, where you receive the following benefits..."
2. Social proof is more than just what people are watching. "Fans of SomeNonprofit donate an average of $121 to SomeNonprofit every year." Or, "When we asked SomeNonprofit donors what they liked most, they said it was the way SomeNonprofit does SomeThing. If you like SomeThing, too, then donate to support SomeNonprofit." It's really just about demonstrating that others have done a thing so it's okay for you to do it, too.
3. One nonprofit I'm involved with very successfully does a fundraising campaign for the last 24 hours of every year. It's an artificial time restraint in some ways, but it also capitalizes on being the very last day each year that tax-deductible donations count toward a year's taxes. It's a true time-constraint!
Want an easy win? Make mobile checkout better. It's generally the worst. I was on a fairly large, publicly traded, retailer's site over the weekend and had a goofy error that was extremely easy to make on their mobile checkout page. While I was alerted to the error, it also emptied my shopping cart and erased all the address and payment info I spent time typing in.
Likewise most GUI-related tweaks seem to have a negative effect (mobile friendliness, search, navigation). Assuming it gives a better mobile experience, why would anyone spend less - unless the goal is to get them off mobile and onto the desktop.
This is a really useful article. It's a shame that so much development time is wasted on large numbers of fruitless optimisations just because they are "easy" (eg. tweaking the colour of a CTA). That being said, I'm surprised many of the results are so negative. It would be great to also see the max uplift achieved for each category. A number of retailers I've worked with have been able to beat these uplifts by quite…
Two things - firstly, each of the scores you see in the key findings are just the average. We have also estimated the size of the standard deviation (see table in section 2, or appendix A). So for some treatments, large uplifts are not out of the question. Maybe more importantly - every A/B test ever run suffers from measurement error, and usually in e-commerce this error is on the scale of the effect you are trying…
I'm not an expert on plate notation, though, so I'm not sure which MLM you used. Is it basically `Revenue ~ (Covariate_1 + ... + Covariate_n | Treatment | Category)`?
If you want to see pretty much all the most effective measures in action, go to a ticket reseller like Viagogo and follow something through to the basket. It is both impressive and amazing the amount of psychological steers there are on the site.
Or flight/hotel/car rental booking websites. Google flights is a notable exception.
There's no hope of avoiding that with airlines for me - I don't fly enough to avoid the prole line. But literally any storefront where I can avoid that shit, I do, and it breeds not just dislike - it makes me want see them to fail.
This is a really useful article. It's a shame that so much development time is wasted on large numbers of fruitless optimisations just because they are "easy" (eg. tweaking the colour of a CTA). That being said, I'm surprised many of the results are so negative. It would be great to also see the max uplift achieved for each category. A number of retailers I've worked with have been able to beat these uplifts by quite…
It would be great to see the max uplift achieved for each category Indeed. What matters most with these kinds of experiments isn't really the average results, but what is possible and the distribution among beneficial results only . After all, the whole point of A/B testing is to try experiments and then either keep the changes if they improve results or stay with what you've already got if the changes didn't bring a…
No, the bad results also matter: you are still spending visitors and revenues in testing out bad variants, which is part of determining the costs and benefits. Even with a bandit approach, you incur logarithmic regret in the number of variants. And testing a bad variant is common: the best category, 'scarcity', has a 16% probability of the variant being harmful. A Value of Information calculation has to take into account the harm done while testing.
Well, running a rudimentary eBay store you realize these things help pretty quickly, but it's good to have data. However... Starting a new e-commerce property? Good luck finding traffic in anything profitable. Amazon and other Giants dominate search rankings so I'm not sure how you will find your traffic unless you create a new niche. Maybe you're a thought leader in a hobbyist space, that can work... But you're not…
Being a small category for a huge store means they don't care about that category too much but it doesn't mean there isn't a lot of cash to be made.
I've helped several companies to build an online store that did exactly that and they are all doing 5 digit revenue month after month.
It's easy to rank higher in search engine for something you are 100% focused on compared to a big stores where it's only a small thing that they don't highlight.
This was really interesting. Thanks for posting it. Does anyone know of a place to find similar content? (Analysis of web trends and practices from a data driven perspective.)
Still, it has proven a very valuable resource for me when trying to explain a decision I've made in a new website design. They have many free articles that offer some good insights, as well as some more in-depth reports about specific sectors that will cost a few hundred dollars each.