Every industry is plagued by myths, misunderstanding, and half truths. This is especially true in digital marketing, and conversion optimization is no exception.
Keep reading »All Things Data-Driven Marketing
When it comes to Google BigQuery, there are plenty of articles and online courses out there. Most are “tech to tech” explanations—which are great. But they can be intimidating for those beginning their marketing-to-tech journey.
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Five years ago, I was trying to build links—and failing. In fact, I was failing so hard that I had to work without getting paid while building only a couple of links a month.
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If you’ve ever tried to build an attribution model that wasn’t position-based (i.e. last click, first click, linear, etc.), you might have felt overwhelmed. But customer paths are non-linear and pretty complicated—sooo many things influence conversions.
Most businesses have a lot of data about customer behavior: the devices they use to purchase, ads, competitors’ pricing, keywords, etc. But they can’t make sense of it all.
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That it costs five to seven times more to acquire a customer than it does to retain one isn’t entirely true.
The origins of this myth can be traced back to the 1980s when the Technical Assistance Research Project published research that stated the cost of customer acquisition was significantly higher when compared to the cost of customer retention.
Soon after the research was published, other institutions like the Customer Service Institute, Consumer Connections Corp., and ITEM Group all “found” similar data.
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“Statistics are like bikinis. What they reveal is suggestive, but what they conceal is vital,” said Aaron Levenstein, a former professor of business administration at Baruch College. [Tweet it!]
The same is true of your data in Google Analytics. Most of what you spend your time looking at (and re-looking at) is merely suggestive.
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Video marketing is booming. It’s no longer news. Cisco predicts that, globally, video traffic will be more than 80% of all web traffic by 2022 (up from a prediction of 75% made in 2017).
Other recent reports claim a 17% leap in video content usage in 2018, with the average person watching more than 90 minutes of online video every day. In the same report, 85% of surveyed consumers said they would like to see more videos from brands.
However, simply creating videos isn’t enough. Content marketing in general—and video marketing in particular—needs strategic planning to work.
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A few years ago, our developers rolled out Angular on a few key web pages—without consulting the web analytics team. The pageviews on some of the pages suddenly dropped to almost nothing.
I bought two books on Angular to try to find a solution. Meanwhile, my manager stumbled on an alternative syntax for tracking pageviews in Adobe Analytics. As we found out, a similar alternative syntax also exists to track clicks (and anything else).
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When should you use bandit tests, and when is A/B/n testing best?
Though there are some strong proponents (and opponents) of bandit testing, there are certain use cases where bandit testing may be optimal. Question is, when?
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One of my favorite UX quotes comes from Chikezie Ejiasi, UX lead at Nest.
He wrote: “Life is conversational. Web design should be the same way. On the web, you’re talking to someone you’ve probably never met—so it’s important to be clear and precise. Thus, well-structured navigation and content organization goes hand in hand with having a good conversation.”
Can tabbed navigation be clear and precise? Of course it can, which makes it a valid form of navigation and content organization. What matters, as with most things related to UX, is how you implement it and how you optimize it.
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