previous articleHow Product Managers Can Dig Deep into the Motivations Behind RequirementsThe fourth question in section 4 talks about pseudo-demand, and this article will discuss this topic in depth.
Regarding pseudo-demand, the most famous is the case of Ford’s “users need a faster horse”, in addition to another classic case is the joke in the study room below.
This cartoon tells the story of a couple who went to a hotel to learn a foreign language, so the hotel owner really changed the hotel room into a study room, and then the hotel closed.
In requirements analysis and product design, identifying pseudo-requirements is one of the key competencies of product managers. Pseudo-requirements usually refer to needs proposed by users on the surface but do not have real value or feasibility in reality.
1. Typical characteristics of pseudo-demand
Although it is difficult to identify pseudo-needs, pseudo-needs still have some typical basic characteristics. For example:
Solution-based expression: The user directly says that I need XX function (e.g., the customer wants a faster horse in the opening case) rather than describing the problem (I want to get to the destination faster).
Lack of Role Scenario Process Description: Detailed descriptions of roles, scenarios, and processes are missing from the requirements description. For example, Alipay’s AA payment function on the PC side more than 10 years ago can be identified as a pseudo-demand more than 10 years ago through the role-scenario-process analysis method, but WeChat’s AA collection in the past few years may not be a pseudo-demand.
Emotional expression: The leader or boss directly benchmarks competing products or other products, bluntly saying “this function is cool”, “XX has this function” and other emotional expressions, without considering the positioning and stage of their own products, Alipay and Meituan can do farm chicken and fish farming, but the overall number of users is only about 200,000 B-end ordering platforms to do this.
Lack of data support: Requirements that cannot be verified with behavioral data or market data, such as the example of doing points function on the B-end ordering platform given in “How Product Managers Dig Deep into the Motivation Behind Demand”, neither products nor operations can support the authenticity of this demand through data.
If the demand for the above four characteristics is met, there is a probability of at least 60% or more that it can be regarded as a pseudo-demand.
The remaining 40% probability can be broken through the 9 questions in Chapter 4 of “How Product Managers Dig Deep into the Motivation Behind Requirements” to break the casserole and ask to the end, and explore the motivation behind the demand, so that the probability of pseudo-demand being identified can be increased.
In addition to the above methods, pseudo-requirements can also be verified by simple models.
This verification model can be summarized as: consistency, value, universality and feasibility, and these four keywords have a sequence.
2. Consistency of requirements
Whether it is the company or the product level, there will be a phased strategic planning goal, and when the product manager gets a new requirement, he needs to deeply analyze whether the demand is consistent with the company’s current stage of goals.
Taking the points in the article “How Product Managers Dig Deep into the Motivation Behind Demand” as an example, the strategic goal at this stage revolves around improving GMV, because only if GMV is high enough to get more financing, can quickly occupy the minds of consumers, so as to stand out in the fierce competition.
Taking the recent hot JD takeaway as an example, I personally think that at this stage (at least within half a year), the strategic goal of JD.com takeaway is to keep three rushes and two hopes, that is, to maintain the third place in the takeaway industry, hit the second place, and look forward to the first place.
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The specific KPI may be that the average daily takeaway order volume reaches 20 million in X month and 30 million in Y month, which helps to achieve the demand for this KPI, that is, the need to be consistent with the strategic goals of the takeaway business, which will have a very high priority
3. Demand value
Does this requirement create clear value for users (e.g., save time, reduce costs, improve experience)? Does it bring business value to the enterprise (e.g., increase revenue, improve user retention)?
Taking the above points as an example, the points of the B2B platform may be of some use to some buyers and customers, but for the seller and the platform, its value is minimal, neither significantly increasing revenue nor improving retention, so the value of points to the B2B platform is limited.
For B2C or other C-end products, the value of points is relatively unclear. Whether it is Tmall points or Alipay points, it always feels useless, and as a platform, it is impossible to quantify the value of points, that is, the platform cannot support whether the increase in the number of active users last month is the reason for points or other reasons.
For more information about points, interested readers can read section 3 of my previous article “20,000 Words of Dry Goods: How to Build a Membership System from 0 to 1” (Why do products need points, and what is the meaning of points?). )
Regarding the value of demand, it can be understood in a different way. If you are the boss of this company, your subordinate product manager will report to you with a bunch of unsatisfactory needs and ask you what you want to budget and cost
In addition to those with mines at home, normal rational professionals will evaluate whether this demand value is worth doing, whether there is value output after doing it, and what is the input-output ratio of ROI, in short: good steel should be spent on the blade.
For example, the above demand seems outrageous at first glance, and it feels like it has no value to users or companies.
However, if this demand development can be realized, the cost of implementation is relatively low (such as the development cost of 500,000 yuan), and the topicality and traffic exposure brought to the product after the implementation of this function, as well as the benefits of new users paying attention to order conversion are far more than 500,000, then this demand cannot be regarded as a pseudo-demand.
4. Universality of demand
Is the target user group large enough? This can be done through market research, user interviews, and statistical analysis of existing data. Are the users who made the request an “extreme case” or “non-targeted user”?
For example, the B2B platform mentioned in “How Product Managers Dig Deep into the Motivation Behind Demand” is the target user group of this demand large enough?
The order amount of the B2B platform is generally relatively large, and buyers will encounter the situation that there is not enough money in one card when paying, and multiple cards are needed, and buyers want to provide the function of paying multiple times for one order.
At that time, when we were doing this demand research, the customers we asked basically felt that this function was good and necessary, and the proportion of users who recognized or agreed with it was relatively high.
After several trade-offs, we decided to implement this feature to meet the needs of users. However, in the more than a year since the launch of this function, even if we have carried out all-round publicity and promotion, hundreds of thousands of users have only used it a few times, and the input and output are completely disproportionate.
Later, when we reviewed and reflected on this function, we summarized the following reasons:
- The operation is still troublesome: you still need to check the balance of each bank card before swiping the card, and the balance may not be available (bank cards still have daily and per-transaction limits).
- Capital security considerations: The security of POS machines and B2B platforms is still not fully trusted (even if Tencent Alibaba is changed, but the trust will be improved), and even if there is a risk of swiping a card, it will not affect other cards.
- Demand generation scenario: Most users will purchase goods according to the funds on hand and product sales, how much money to buy, rarely overorder, one card is not enough money to need to swipe multiple cards The probability is relatively small. Users can split the order, that is, the original plan is to purchase 20,000 yuan at one time, and they can be divided into two orders of 5,000 and 10,000 yuan according to the balance in the card, and the user can find a way to solve the problem.
In fact, the key to the universality of demand depends on two points: whether the user group is large enough and whether there is natural growth after the function is launched.
The user group is not large enough: Many application scenarios are “hard-made” or “imagined”, and users feel that they should/may/may need such services or functions, resulting in products that cannot fall into real public life and cannot take root.
There is no natural growth: The growth of data temporarily pulled by gimmicks and interests cannot be long-lasting, and once the drug is effective, countless problems will be exposed, such as the early door-to-door car wash service, and the demand forcibly pulled without listening to the user’s inner demands is not the real demand.
To borrow the point of view of a netizen: Any non-independent functional innovation is not enough to support a successful product innovation. Only product-level innovation has more value, and functional innovation value is limited.
5. Demand feasibility
If the above consistency, value type, and universality all come to a relatively positive conclusion, then the final step is to evaluate the feasibility of the requirement, that is, whether such technical capabilities are currently available to implement this function.
Specifically, it can be divided into three levels:
- Technical level: Does the existing team have the technical capabilities to develop this feature? For example, the team developing AR functions may exceed the technical boundaries.
- Cost level: Does the development/maintenance cost match the expected benefits? For example, if you develop an exclusive function for 100 users, the input-output ratio is too low, which is different from the above generality.
- Time level: Is it in line with the rhythm of product iteration? For example, in 2015, it is not feasible for Alipay to do AA collection on the PC side, and it is more appropriate for WeChat to do AA collection after 5 years (because there is an application scenario of WeChat group).
Through the above example of AA collection, it is not difficult to find that pseudo-demand is not a constant, it will change over time, environment, trends, and even derive into mainstream demand.
Regarding the detailed interpretation of Alipay’s AA collection, readers can go to Chapter 3, Section 4 of “Behind the Scenes Products” (WeChat Reading has this book), and Wang Shimu, the witness of this function and former vice president of NetEase Cloud Music Products, will interpret why the function “failed” through the role-scene-process requirements analysis methodology.
In fact, before the emergence of Internet taxi products such as Didi Taxi and Kuaidi Taxi, I and many netizens thought about taking a taxi through a mobile phone, but there were a few key points that were stuck at that time.
- How to accurately obtain the location of passengers.
- How to recruit enough drivers to ensure that passengers can call a car quickly.
- How to attract passengers to call a car through their mobile phones.
These two problems were not solved well before 2012, and many smart readers on Zhihu did not think of how to break the situation, until around 2012 the blowout development of smartphones and mobile Internet made problem 1 have an optimal solution.
Questions 2 and 3, readers who have experienced the taxi subsidy war should have thought of the answer and gave the subsidy directly. Passengers are subsidized, drivers are subsidized, or both are subsidized.
Above we briefly explained the 4 dimensions of the model, each dimension can be given a certain weight and score, and then the weighted score of each dimension is calculated, and the last four terms are summed.
Personally, I think that if a need is less than the passing line of 3 points through the above decision scoring matrix, it can be temporarily stopped, and if it is lower than 3.5, it needs to be cautious.
6. Minimum feasibility verification MVP
The above methods can improve the identification ability of pseudo-requirements to a certain extent, but they cannot be completely eliminated or avoided, and a safer approach is to do minimum feasibility verification, that is, MVP.
The concept and operation method of MVP will not be expanded in this article, but here is a brief explanation of how to verify the requirements with the lowest cost.
For example, B2B e-commerce platform operators have raised the need to add barrages to the carousel chart of the product detail page, which they believe will help product conversion. Regardless of whether this is a pseudo-demand or not, if not, we need to consider how to make an MVP at the lowest cost of this demand.
Perhaps we can try to pick out 10 of the top 20 best-selling products, and then directly add some barrages to the products at the code level, temporarily without doing the background management and maintenance of the barrage and the corresponding database table/field design, nor do we control the speed of the barrage, the height of color fonts, etc.
Then we compare other products without barrages, observe the number of clicks, views, dwell time, additional purchases and payment conversion rate, etc., if we find that the conversion data of the two has not changed much, we can preliminarily determine that it is a false demand.
Different needs will have different ideas and methods for implementing the lowest cost MVP.
Above, I hope this article will be helpful to you, welcome to collect and forward.
