Build a SaaS product operation system from 0 to 1!

If 2015 is the first year of SaaS, then 2016 is the explosion year of SaaS! After more than a year of explosive growth, where will the popular SaaS companies go? The price of traffic acquisition is getting more and more expensive. How should SaaS companies move towards lean operations ?

Talking about the characteristics of SaaS industry from the perspective of cash flow

The SaaS (Software as a Service) industry is different from traditional industries in that its capital investment and revenue process have distinct characteristics. The figure below is a cash flow model for a SaaS enterprise customer’s life cycle. The yellow column on the lower left represents the huge initial investment in acquiring users, including the costs of marketing department promotion, sales department negotiations, and technical support. The blue column above represents the revenue from customers. The SaaS industry generally charges on a regular basis.

SaaS industry user cash flow model

If a SaaS company has an annual revenue of 10 million yuan and a user churn rate of 30%, it will lose 3 million yuan in revenue in the next year; when the company's annual revenue reaches 100 million yuan, it will lose 30 million yuan in revenue in the next year. When the company's user growth rate reaches a bottleneck, if the user churn rate is still as high as 30%, it is likely to cause user or revenue growth to stagnate or even decline.

From the above data analysis , it is not difficult to see that the SaaS industry has a series of significant characteristics and has a profound impact on business operations:

1. The cost of acquiring customers is high. Acquiring a B-side customer requires follow-up from multiple departments such as marketing, sales, and technical support, which consumes a lot of manpower and energy;

2. AR PA (average order value) is very high. Compared with To C products, the average order value of enterprise-level services is very high;

3. Product iteration requires data support. Every improvement of a SaaS product needs to be based on the user's perspective and the effect should be measured with data;

4. User renewal and retention are the cornerstones of the business. In the SaaS industry, LTV (lifetime value of a user) should be greater than three times CAC (customer acquisition cost) to improve efficiency.

In view of these characteristics, the SaaS industry needs to conduct in-depth research in the following four aspects: how to efficiently acquire users, how to activate and convert users, how to iterate and optimize products, and how to use data to drive customer success.

Exploration 1: How to efficiently acquire users

To improve the efficiency of acquiring users, the first step is to establish a refined channel tracking system; then measure the effectiveness of each content and each activity; finally, pay attention to every step of the conversion and optimize the conversion process.

1.1 Establish a refined channel tracking system

Unlike the past when people made subjective judgments about channel quality, UTM parameter configuration is now commonly used to track the source of users. As shown in the figure below, UTM provides five freely configurable parameters to facilitate tracking of users’ advertising sources, media, names, content and keywords.

UTM parameter configuration analysis

Through the UTM channel tracking system, we can accurately measure the effectiveness of marketing activities such as content marketing , social marketing , SEM , DSP, etc.

1.2 Measure the conversion effect of different channels

After establishing the UTM channel tracking system, start daily delivery and maintenance, and then conduct regular analysis of the tracked data. To measure the quality of a channel, we can conduct detailed data analysis on multiple aspects such as the number of visiting users, bounce rate, visit duration, and visit depth.

Monitor the conversion effects of different channels

In the process of channel evaluation, we need to select reasonable indicators based on actual business needs and application scenarios, and continuously evaluate the quality and drainage effect of the channel.

1.3 Conversion funnel analysis of different channels

Finally, we need to conduct an in-depth analysis of the conversion rates of different channels; we need to know not only the overall conversion rate, but also the conversion rate of each step in the conversion path in order to optimize the conversion path.

Analyze conversion effects through funnel function

At the same time, we can also split the conversion rate according to different dimensions, such as advertising source, browser , operating system, user region, etc. As shown in the figure above, the conversion rates of new users from two different advertising sources have different overall differences in each step of the conversion, which is worthy of attention and consideration by operators.

Research 2: How to achieve user onboarding and activation

SaaS products have complex functions and have a certain learning cost; SaaS companies need to help users get started as quickly as possible at the product level. On this basis, we also need to analyze the conversion of users' key behavior paths and activate users.

2.1 How users use the product

A SaaS product will have different functional modules, and different users will have different usage frequencies and depths of different modules. SaaS companies need to continuously monitor user performance on your products and observe the proportion of time users spend on different functions through percentage stacking charts and other forms.

The percentage stacking chart shows the time proportion of different functions

Taking July 11 in the above figure as an example, the proportion of time users spend on different product functions has begun to change significantly; the proportion of time spent on two new functions has increased significantly. During the operation of SaaS products , it is necessary to conduct lean analysis of user usage behavior and gain insight into users' product function preferences and changing trends.

2.2 Critical Path Conversion Analysis

When users use SaaS products, there are some key paths, such as registration path, SDK loading path, payment path, etc. Through machine learning methods, we can quickly identify the user's conversion path and calculate the proportion of people passing through different paths.

Analyze conversion effects through the smart funnel function

The success of the critical path directly affects whether users can be successfully activated or converted; therefore, every step of the critical path of SaaS products requires detailed data analysis. Generally, we use the "funnel model" to analyze the conversion of key paths. The figure below shows a SaaS product registration path. It is not difficult to find that there is obvious loss between the second and third steps of registration, which requires us to conduct in-depth analysis.

Registration conversion rate monitored by the conversion funnel

At the data analysis level, we can group these lost users, and then use user data to carefully examine their operating behaviors and analyze the reasons. At the product level, the best way is to register and experience it yourself. If this step is to verify the mobile phone number, then does it mean that the user will not receive the verification code? Or is the submission verification too slow? These details may affect the final conversion effect!

3. How to iterate and optimize products

Retention, as the name suggests, means that users stay on your website/APP and continue to use it. Through product retention analysis, we can understand the user stickiness and activity of different product functions, so as to iterate and optimize the product.

3.1 Three Stages of Retention

The retention curve is divided into three stages: oscillation period, selection period and stability period. The vast majority of new users are lost during the initial shock period, while some users discover the value of the product during the selection period and then gradually stabilize.

Three stages of retention

When designing SaaS products, it is necessary to consider the retention of new users, present the core value functions to new users as directly as possible, and improve the retention curves of the first two stages.

3.2 Find the key features for retaining new users

By comparing the retention rates of different product functions (functional modules), SaaS products can easily discover the core or high-value points of the product. Product functions with high retention rates also have higher value. Through product design optimization, we guide new users to discover and use these core functional modules, create business value for users as early as possible, and thus improve the retention rate of new users.

A SaaS company found that the retention rate of users who created single pictures or dashboards was significantly higher than that of other users, so it added a [New] button in a prominent position in the upper left corner of the interface to encourage new users to create their own single pictures or dashboards.

3.3 Find the Magic Number for Product Growth

In the growth hacking practice in Silicon Valley, there is a set of Magic Numbers that people talk about a lot. So what kind of existence is this set of numbers?

LinkedIn found that if new users add five social friends within a week, their retention rate will be very high;

Facebook found that if new users add ten friends within a week, their retention rate will be very high;

Drobox found that the retention rate of users who logged in on both operating systems was very high.

In fact, Magic Number is a combination of user behaviors, which reveals the status of users performing N operations on a certain product function within a specified time. So how do you find the Magic Number for a SaaS product?

Through machine learning methods, the correlation coefficient between user retention and user behavior (combination) is calculated. If the coefficient is between 0.4-0.6, it means that the two are positively correlated; if the coefficient is greater than 0.6, it means that the two are strongly correlated. Find a set of positively correlated user behaviors (combinations) that are meaningful and actionable and serve as the Magic Number that drives your product growth.

4. Data-Driven Customer Success

In order to improve user retention and activity and encourage user renewal, we need to establish a complete customer success system and drive it with data analysis.

4.1 The Logic of Customer Success

The essence of customer success is refined customer management, which enables user segmentation through the customer’s “temperature-health model”. The horizontal axis "Health Index" in the figure below represents the user's activity; the vertical axis "Temperature Index" represents the possibility of user conversion.

The Health-Temperature Model

We need to adopt differentiated operation strategies for different groups of users. The users in the upper left corner are not very active, but the possibility of paid conversion is very high; we need to strengthen training for users and increase their frequency of use. The users in the lower right corner are very active, but the possibility of paying is very low, which is worth our in-depth consideration of the reasons behind.

4.2 Levels of Customer Success

After clarifying the ideas of customer success, you need to build a customer success analysis system from scratch and analyze it in layers. According to business management needs, it can be divided into three levels: customer overall, company level and user level.

Customer Success System

The company's senior management (CXO, VP level) needs to focus on the overall customer situation, including user activity trends, login account status, visit duration, key consumption index and overall health ranking. Customer success managers need to focus on company-level health, including the usage of key product modules by corresponding customers, customer churn prediction, etc. Grassroots business staff need to connect with specific individuals, especially core users, to learn about their usage. If the sales director doesn’t use a CRM system, then the front-line sales or business staff will have no motivation to use the CRM; if the HRD doesn’t use a recruitment software, then the HR below is unlikely to use it much.

4.3 Build a customer success dashboard

After clarifying the levels of customer success, we need to build a complete data dashboard to support our previous logic and hierarchical analysis.

Customer Success Dashboard

The customer success dashboard should include: overall customer activity analysis, usage activity analysis of each company module, and activity monitoring of core users. Through data monitoring on the customer success dashboard, we can promptly identify customers who may churn, intervene and improve user retention.