Wen/nir Eyal (TechCrunch)
In the past 25 years, the truly great consumer technology companies have a common feature that they create consumption habits. This is the key to the difference between a business enterprise and other businesses that will change the world. Apple, Facebook, Amazon, Google, Microsoft and Twitter are all products with high user usage rates, and the companies ' products are attractive enough to make it hard for many of us to imagine what life would be like without them.
But creating habits is a difficult thing to do. Although there are already many articles with behavioral engineering and the future importance of behavior to the network, the tools needed to design and measure user behavior are still inadequate. It's not that these technologies don't exist--in fact, these technologies are very familiar to those working in the enterprise. But for new entrepreneurs, the tools are mysterious.
The so-called "habit test" is some of the industry's best companies to adopt the method, and by some consumer network companies to create users love products.
Habit Test
Custom testing is perfect for creating, measuring, learning methodologies, and is supported by the Lean Entrepreneurship Movement, and it provides a new way to make data available for adoption. Habit tests can identify three questions: 1 who are you serving? 2 What part of your product can become a habit if possible? 3 Why do these parts turn into habits?
A prerequisite for a custom test is that a product appears and operates. Of course, a good way to do this is to try out your business model and find out how your product will create the user's expectations.
If you have a website or application online, you can start collecting data. Habit testing does not require the collection of data for everything-as long as it is appropriate, so the key is to set the appropriate analytical approach. In order for a custom test to achieve its purpose, you need to mark the time point of the user's path when the user uses your site.
Step one: Identify the user
The first question you need to answer when you have the necessary Web sites and statistical methods is: "Which users have habitual actions?" "First of all, be clear about what this means for the users you want to serve. Ask yourself how long a user will be using the site. That is to say, suppose that one day all bugs are cleaned up and the product is perfectly "ready", how often do you want habitual users to visit the site?
Be realistic and loyal to yourself. If your company has developed a mobile social networking application, such as Foursquare or Instagram, you want to habitually use the yen several times a day to log in. However, if you are developing a movie recommendation site, such as La Flixster, you will not want users to visit more than one to two times a week. Don't get overly optimistic predictions by calculating overly dependent sex; you just have to find a realistic idea and figure out how many users will interact with your site.
A simple and effective way may be to find out how long you and your co-workers will use your product on average. Of course, the more the better. The Twitter site is an in-house product of Odeo, the latter Biz Stone and Jack Dorsey initially created, because engineers have been using the site.
One thing to note: the higher the frequency of your product usage, the more likely it is that user habits will be formed. However, this is not to say that almost no use of Internet products is not a good business, they just do not form a habit, so special also vary. To be feasible, even a company that is not accustomed to formation may tend to be more transactional, requiring regular communication with the customer, so that the user is always in the mind.
For example, the brutal struggle of the travel industry has allowed us to constantly visit different websites. Expedia, Travelocity, etc. are frequently accessed by ordinary users, forming a habit, so they often compete for the attention of users. These are viable, even profitable businesses, but they are always facing more competitive threats as they are not used to form products. Everyday products naturally create barriers to market entry.
Who will form the habit?
Now that you know how often users "must" visit the site, analyze the data to see how many users really do it. Using a statistical tool can then show that the data is very helpful. Instead of letting engineers drop their core product development work, or even get business people to do it, consider recruiting a graduate who specializes in data statistics to figure out how many users like your site. The best way to do this is to create a batch of analytics data and set a baseline to measure future product iterations.
Step Two: Normalize
You'll have at least a few users who will often interact with your site and become "lovers" in Your eyes. But how many amateurs are enough? My rule is 5%. Even if active user rates need to be higher to sustain your business, 5% will be the right base to start a habit test.
However, if even 5% of users do not find that the product has the use value you have assumed, that is your problem. At this point, it's important to start designing and reshaping your vision. However, if you have more users than the bottom line, then you find the habit of using it, and the next step is to sort out the steps they use to your product so that you can understand what makes them obsessed with your site.
Each user interacts with your product in a slightly different way. Even with a standard user process, the level of user involvement in your site creates a unique data trajectory that can be used to analyze and discover models. From data to deciding whether similar behavior will occur. You may want to find a "custom path", a series of similar behaviors shared by most loyal users.
In the early days of Twitter, for example, it was found that once new users focused on enough other users, these new uses would not reach an outbreak point, and their chances of using the site increased dramatically. For each company, the behavior of a loyal user varies, and the goal of finding a "custom path" is to determine where steps are key to creating a loyal user.
Understand the user's ideas
After understanding the "custom path", the next step is to assume how to make a "passing" user into a loyal user through this path. Still, this step looks a bit like finding a reason for relevance, but it's something we can do on the eve of a new product launch.
At this stage, it is appropriate to communicate with the user personally to understand the reasons for their use of the product and the way. Custom testing can be used to prove the special point of these "hearsay people" and to discover what can be summed up by other users.
Step Three: Adjust
Take these new assumptions to heart, and return to the development, measurement and understanding of the various links, the new users to the same "custom path" used by loyal users. For example, Twitter's current process leverages the user's "Custom path" and directs new users to focus on other users immediately at the outset.
Custom testing is the way that a continuous process enterprise uses for each new feature and product iterative development. Tracking batch users and comparing their behavior with habitual users can lead to product evolution, improvement, and cultivation of habits.
Technical entrepreneurs often find their ideas not recognized because they are unaware of the importance of creating user habits. Unfortunately, if a product is not accustomed to a habit, it may not survive. By using "Custom tests" to define the maximum value and habits of the product, entrepreneurs are better able to serve the yen and increase the chances of creating changes to world-class companies.
Source: http://media.cocoachina.com/hooking-users-in-3-steps/