What kind of content should you have on your site? How should you structure the menu? What should be the first-level menu items? One or two menus? What should the menu links be called? This post gives you answers.Keep reading »
Customer journey mapping is a widely used and impactful technique that can help you make a better product, marketing, UX, and merchandising decisions.
However, like other UX research techniques (including user personas), there’s some vagueness and obscurity around how to actually create customer journey maps.
A 1,983% boost in annual revenue and 1,000% user-base growth within six months, all with no upfront costs. Can this be true? These are actual results that startup Ringadoc got from their partner program.
In today’s environment, if B2B organizations are going to make it, they need to grow sales. Partnerships can be a big help.Keep reading »
I remember the first time that a client told me how much analytics had helped their business.
They were able to increase their sign up rate for their product by 22% while reducing their marketing costs. It wasn’t magic or fancy tactics. They simply used their analytics data to make informed decisions.
They didn’t have to guess or take huge bets. They knew exactly what was working and what they needed to do more of.
This is power of analytics and more specifically, product analytics.
Agile marketing may not be a phrase you hear often, but it’s becoming increasingly popular and important.
Traditionally associated with development and product management, agile is a lightweight and, well, agile framework for software development and bringing features and products to market.
It stands in opposition to “waterfall” production methods that treat analysis, design, coding, and testing as discrete phases – where in agile they are treated as continuous.
As marketing becomes more data-driven, quantitative, and iterative, we can use many of these same management practices to hone our marketing campaigns, mitigate risk, and ultimately ship more effective marketing campaigns.
Did you know that Netflix has only 90 seconds to find a show that suits a user before she gets frustrated and quits? According to a recent academic study, “a typical Netflix member loses interest after perhaps 60 to 90 seconds of choosing, having reviewed 10 to 20 titles (perhaps 3 in detail) on one or two screens.”
How does Netflix manage to find the right show for the right user so quickly?
According to the same study, 80% of its customers’ video plays comes from its personalized recommendation engine. Netflix estimates the value brought by this personalized recommendation system at a billion dollars per year.
That’s a serious win achieved through personalization.
From the outside, it seems like data is impartial. It’s cold, objective, accurate.
In reality though it’s more complicated. In the hands of someone with an agenda, data can be weaponized to back up that viewpoint. Even in the hands of someone benevolent, data can be misinterpreted in dangerous ways.
I’m sure you consider yourself data-driven.
You make decisions based on data. Problem is, most companies aren’t using their data to the capacity they could be. It’s almost a universal problem, and it means you’re leaving money on the table.