It’s always wrong.
Hello. Welcome to the University of Queue 18.
In the last session, we talked about the starting point for demand mining, which comes from product managers’ deep perception and insight into users, which can enhance the “reception” of users by listening, forgetting, modelling and customary law.
So, is it okay to make a product based on the user needs we understand? It is regrettable that the extraction of product demand is not a once-in-a-lifetime exercise, and it is often unexpected that we may be able to push well-developed products into the hands of users with anticipation and enthusiasm.
Murphy’s Law of Insight.
In 1949, a captain of the air force named Edward Murphy was a rocket.
The same is true of our thinking about product needs. No matter how powerful the product is, no matter how deep the thinking about product programmes, there are blind spots in the insight of the user mind. As long as there are blind spots, it is inevitable that the products produced may break the user ‘ s acceptance in some unexpected places.
The product managers who used to work with the QQC team may never forget that, over the weekend of May 2013, almost every colleague of the team was fighting all night, with tens of thousands of user feedback coming in, each requiring an explanation and apology from the team. Because in the recently released version of QQQ4.0, 90 per cent of the more than 30,000 user comments in the new version of AppStore showed that users who had used to see the online status on the PC end of QQ had expressed extreme discomfort by removing the distinction between QQQ on-line status.
This is probably the biggest user crisis that the QQC team experienced at the time, yet this version is the first official step from the QQC to move from the PC to move, and is the result of several months or more of the team’s reflection. The distinction between online status has been removed because it is actually a display of the state of users in the PC era, yet a mobile phone is a device around a regular user, and one of the features of the mobile Internet is “AlwaysOnline” , even though a user does not use a mobile phone QQQ at this point in time, he is still able to receive information easily through a system alert.
So the decision is not wrong, and even in the case of the subsequent update of the 4.0 version, the idea of weakening offline was upheld. On the one hand, after the product team actually saw the update, the phone QQ.
Why is it not acceptable to users to have the right ideas, to be trend-oriented and to be in line with the scene? The team reflected that we were prepared for this big update, but two key elements were missing:
First, the strong inertia of “user habits” is ignored.
Changing user habits means that the user needs input costs, which involve the user ‘ s cost of understanding, the cost of developing new habits, without a buffer, and significantly lower user acceptance.
Second, it ignores the old user base, which has a vast experience.
QQQ, a product that hundreds of millions of people are using, has been updated with a 4.0 version that actually includes more than a hundred functions and optimising points for QQQ mobile, and the removal of the online status is only one small feature, yet it is a small mistake to ignore user habits, like the “butterfly effect” that triggered a “tsunami” for all.
After that, the QQQ team quickly adjusted its products, developed, operated, and all of its classmates turned into guest clothes, pacified the mood of its users to the greatest extent possible, and tens of thousands of user feedbacks were “indigentized” over the weekend. In subsequent updates, while adhering to the product concept, contact list optimization and additional text identifiers, such as a sign that you can see a certain “phone online” to allow users to gradually accept changes in the way mobile Internet age online is presented. The same needs, the way to meet them evolves.
Interestingly, the story of “Online” is not over yet. In the new version of QQQ in 2020, we found that personalized online situations such as “hearing the song” and “TiMi” became popular among young people, and people went on to ask them where they were set up and even where there were personalized posts in forums.
When you listen to the “TiMi” and you don’t react at all, but remembering the sound of the familiar King’s Glory, you laugh at the moment, a simple and secret state of affairs, and your friends’ communication is transmitted in silence.
So with the development of the mobile Internet, the online status has long gone beyond a simple definition of whether it is online, and it has begun to extend to its own current individualized state of life, mood, etc., and to convey more social will.
Also, the QQQ team skilfully shares some of the information that users use their mobile phones and applications, with the permission of the user, in different online situations.
For example, when you switch to the “hearing in the song” state, the song that the user is listening to on QQQ or QQQ music is shown. Think if there’s a girl in love, and the QQ status shows that you’re listening to Zhou Dong’s new song Mojito, would it give you a chance to start talking to her? A product can bring to the world.
So we can’t ignore the user’s “no” habits, but we also need to keep an eye on our “customs” – because it’s common practice, it’s likely that they will be eliminated, and the stoppage of the product is likely to be a setback, which is one of the reasons why we need to keep the product ‘evolutionary’.
Users who do not follow the standard “show”
In addition to the constant exploration of the need for product optimization, an entirely new product’s “evolutionary power” is likely to be more important, as innovation often comes from the ideas of product managers, from simulations of user scenes and demand predictions, which are often highly biased: We will never know exactly how users will use our products, how user feedback may be unconscionable, how user research may be wrong, but the behavioral data generated by users using the products in real terms reflects market demand to a large extent.
You must have heard of the famous photo-sharing application of Instagram, but you don’t necessarily know that the earliest Instagram is different from the present. Kevin Ström, founder of Instagram, was originally inspired by a combination of two products, one from a geographical sharing application of Foursquare and the other from the mafia game MafiaWars. He expected users to share their travels through this application, to sign up for the location, to share where you planned to go, to send photos, comments, to meet friends to get points, etc. This discovery inspired Strømme, when his team re-engineered the application, focused on the sharing of photographs, cutting off irrelevant features, retaining only the publication of pictures, comments and praises, and changing the name of the application from Burbn to Instagram, making it easier for users to share images and more beautiful images.
On 20 September 2010, Instagram was officially launched, reaching 250,000 users on the first day; after three months, it reached 1 million; after one year, it exceeded 10 million; and two years later, Facebook acquired Instagram with $1 billion. The product, which was based on failure, had finally turned its back.
It is well known that the failure rate of innovation is extremely high and that the chances of success in innovation can only be increased if continuous evolutionary power is maintained in the innovation, lessons are accurately learned in the failure and products are kept on the right path.
The four recipes for improving the evolutionary power of the product.
With so many cases of product evolution, are you starting to wonder if we have any specific ways of maintaining this “evolutionary force”? Here we share four recipes:
First secret formula, lead to sound.
We need to listen to the user at the beginning of the project; after the product goes online, we
In addition to the products, the user community is organized to communicate freely.
It is recommended that a small group of 1 to 1 or 3 to 5 people be used to communicate with users, who are few, who can communicate more deeply, and who, because of a certain level of privacy, are more natural to express themselves. Friends and colleagues around us can also be the first tasters of our products. In telecommunication, even at the head of the department, they often appear in forums where internal products are exchanged, answering very carefully the questions raised by colleagues.
Within the product, a sound-routing route is designed to fit the user scene.
It should be common sense for all to plan a user feedback portal in the product. What is often overlooked, however, is that the design of suitable sound channels in a user-blocked scene, for example, when the user plays video Cardon, where there is an entry to broadcast unusual feedback, where the system can collect the user’s network environment, view the content, fail time, etc., and provide some reference to failure judgement; and that, for example, in out-of-sale orders, we can see the design of some “telephone” functions, which allow users to express their claims very easily when they have waited too long and have gone beyond patience.
This type of user feedback, integrated into detailed product design, can make it easier for us to locate problems and can help users to mitigate and vent frustrations in a blocked path.
Second secret formula, greyscale strategy.
At each stage, the game team optimizes the game details based on the player ‘ s feedback and behaviour data. The call will also give a six-star rating of the game based on data from each game at the grey stage, which will determine the extent of the promotion of the game.
The greyscale strategy generally has three ways of applying to different scenarios.
One is random greyscale. Usually used when publishing new features or features suitable for global users, i.e., random testing of a group of users among global users to observe effects;
Two is directed greyscale. It applies to some of the new functions published in products according to sub-groups. Like the example of the QQccm show that we talked about in our last session, it’s a clever ash scale for target user groups to promote innovative products.
Three is the invitation greyscale. It usually applies to the birth of a new product and has certain social or community attributes. On the one hand, it is possible to focus more on typical seed user groups at the beginning of a product ‘ s life, while, at the same time, it is possible to create a self-dissemination of the user by means of an invitation code, with a self-inflicted flow of the product and a symbolic effect.
Third secret, good use of the experiment.
In 2000, Google, in order to determine how many of the best results were on the search engine results page, conducted its first A/BTest experiment; by 2011, even when Obama was running for President of the United States, it had conducted an A/B test on its own website, using continuous attempts in pictures, news titles, donations buttons, etc., which cumulatively increased Obama’s contribution by $57 million!
So good use of experiments, through data-driven products, can help us reduce the cost of certification, quickly reach consensus and improve innovation efficiency.
The experimental system is also a very complex and specialized area, and we do not have the means to explain it to you through this course, which provides you with two core learning paths:
1. You need to learn systematically about experimental design. The presentation of assumptions, targeting, targeting, grouping of experiments, and estimation of samples has an impact on the reasonableness of the experiments. We all need to know something about, for example, the drums, the layers, the North Star indicators and the p-value values of statistical visibility.
2. You need to learn to use experimental tools. We usually build our own experimental platform in telecommunication, and business-type companies, we suggest using third-party tools like Google Optimize for experimental design and statistical analysis.
Fourth secret, attention to anomalies.
Unusual, means problems or opportunities. We must be sufficiently sensitive to abnormal performance and abnormal data in products, which can often be the starting point for helping us to tap new needs. It was then through observation and understanding of the user that it became clear that the original user was emptied through the exit function. As a result, a feature was then replaced by a “clean” button after the word had been converted. As a result, the re-entry of functional exits has been reduced, increasing the ease of use of products.
Summary
Today we have learned the second kind of ability that needs to be tapped — the need for proof-reading, the “evolutionary power” that keeps trying wrong.
The QQQ online story shows that there may be a blind spot to think more deeply and thoroughly about the product; the needs will be met in different ways in times;
And the story of Instagram shows that users may not be using our products along the lines of design that we imagine, but only real behavioral data can tell us the truth.
We can identify problems, verify demand and keep the product evolving in four ways, by directing sound, greyscale strategy, using experiments and focusing on anomalies.
After-school sharing
Suspended Prognosis
Both of these classes, “Estimation” and ” Evolution” help us to identify product demand in the current age or in the current product; how do we look to the future and develop “prejudice” of the need for innovation?
The continuation of the fifth message, Insight Trends, Prejudicing Needs, is welcome. Congratulate you for another lesson, and if you feel something, don’t forget to share it with more friends and grow up together.
In the hyperheavy test, there was a slight malfunction, and he said a word, and no one-to-one-to-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one-one- 4/11|
There is a greater need to obtain user-used feedback to validate past ideas or to discover that the 6/11 ashscale strategy is often applied to new products or attempts at new functionality. 7/11
