Operational case analysis: How to formulate an operation strategy?

The formulation of operation strategy is a hurdle that every new operator must overcome to advance to a higher level. I believe that many new operators will often encounter such questions during campus recruitment interviews: "If you were asked to operate our product, what would you do?"

I still remember that when I was asked this question, I was completely confused and didn't know where to start. However, most articles on operational strategies on the Internet currently only touch upon the subject and talk in general terms, lacking cases and practical operations. Based on this, the author will tell you how to formulate operation strategies step by step, from ideas to specific operation methods, based on his own practical operation experience.

1. Definition and characteristics of operation strategy

According to the definition of Baidu Encyclopedia , strategy refers to the actions taken according to the development of the situation. This sentence contains two key words , "based on the development of the situation" and "action guideline". Many people tend to ignore the former when formulating strategies, and start by formulating a series of operational strategies, such as how to attract new customers and how to retain customers, while ignoring the fact that all operational strategies should be formulated on the basis of a full understanding of their own product functions, business logic, etc.

For example: When a cancer patient comes to the hospital for treatment, the doctor will develop a series of treatment plans based on the patient's condition. Is the cancer early or late? Is the patient young or old? These situations will affect the formulation of our treatment plan.

2. Case Background

A paid tool app whose target customers are real estate agents, and its main monetization model is port sales. Brokers can publish properties through the app purchase port, and the published properties will be displayed on their real estate website PC, WAP and app. After the home buyer sees the property information of interest on the three terminals, he or she can directly call the mobile phone number left by the agent to communicate.

The specific business logic is as follows:

Based on this, a closed loop of behavior is constructed:

Through the above behavioral loop, we can find that the more brokers there are, the more properties they publish. Rich properties will attract more buyers, and more buyers means more calls.

• For real estate agents, they hope that their listings will be more exposed and bring in more calls.
• For home buyers, they want to see abundant and high-quality properties.

Therefore, we can determine the goal of the operation strategy: use all operational means to obtain more customers, more and high-quality properties, form an ecological closed loop and promote monetization.

The main goal is further divided into two secondary goals based on the product life cycle. For the cold start stage, the goal is to build and improve the business closed loop; for the mature stage, the goal is to promote monetization.

For the cold start phase, the goal is to build and improve the business closed loop.

(1) More listings: Breaking down barriers that prevent real estate agents from posting listings

Through user surveys, we found that the factors that influence brokers to post properties are mainly fees and operating costs. In order to break the cost barrier, we first offered a free trial package to new users, which included three free property listing slots. In addition, we also launched a series of limited-time free promotions to stimulate brokers' desire to buy.

In terms of operational barriers, we mainly optimized the process of publishing listings on the app based on user feedback, and added publishing channels on the PC.

(2) High-quality listings: ensure authentic, standardized and accurate listing information

In terms of ensuring high-quality properties, the first thing is to educate users. The app mainly displays examples of subjective content, such as titles , property descriptions, and pictures, to standardize the published content. In addition, we have established a series of new home listing review and reporting mechanisms to ensure the authenticity and accuracy of the listings.

(3) More customers: Improve user conversion rate and get more buyers to call the broker’s mobile phone number

In terms of improving user conversion rates, we have established user conversion funnels on PC, WAP and app, and improved the conversion rates of each step through data analysis and monitoring.

Taking the conversion path of WAP-side users as an example, home buyers first enter the new home listings page through the new home listings entrance on the homepage, browse to the appropriate property information on the list page, and click to enter a property details page. Finally, they click the [Contact Agent] button on the details page to make a call.

After the user conversion path was established, we found that the conversion rate from the home page to the property list page was extremely low, only 1%-2%, and there is great room for improvement. The main reason was that the entrance was too deep. Unable to apply for a better entrance position, we took a different approach and applied to the distribution group for a text link promotion position. We screened high-quality new home listings for recommendations every day, opened a new entrance for the new home listings channel, and doubled the conversion rate of the first step.

For the mature stage, the goal is to improve core indicators, which in this case is to promote monetization.

Generally speaking, operational strategies involving specific indicators must be specific to numbers to be meaningful. Below, the author will use virtual numbers to explain how to achieve strategic goals.

Quoting Avinash Kaushik, one of the people who popularized Google Analytics:

“All data in aggregate is crap. Segment or die.”

[All the summed data is garbage, either group it or die]

When formulating an operational strategy, we need to set a specific goal, such as achieving 1 million daily DAU and 2 million daily GMV. However, these goals can only point us in the direction. The specific steps still need to be broken down by indicators to make the setting of goals more based on evidence.

Model:

Total daily transaction amount = daily transaction amount of new users + daily transaction amount of existing active users

Daily transaction amount = (daily download users, registration rate, purchase rate , average consumption amount) + (active users purchase rate * average consumption amount)

Current situation (involving business, the following figures have all been processed)):

The average daily transaction amount in August was 760,000 yuan, the average daily number of downloading users in August was 10,000, the activation rate was 80%, the first-time purchase rate was 20%, and the average consumption was 100 yuan; the number of daily active users in August was 30,000, the purchase rate was 20%, and the average consumption was 100 yuan.

• Average daily transaction volume of new users = 10,000*80%*20%*100=160,000
• Daily transaction volume of active users = 30,000*20%*100 = 600,000
• Total daily transaction amount = average daily transaction amount of new users + daily transaction amount of existing active users = 760,000

Goal Setting:

The total transaction volume in September reached 1.3 million. In order to achieve this goal, we need to start with specific sub-indicators and find a breakthrough.

After analysis, we decided to start with the number of daily download users, registration rate and average spending. The number of daily download users increased to 15,000, the average spending increased to 150 yuan, and the activation rate increased to 90%.

• New user daily transaction volume = 15,000*90%*20%*150 = 405,000
• Daily transaction volume of active users = 30,000*20%*150=900,000
• Total daily transaction volume = 1.305 million

After setting the goal, we can formulate targeted operation strategies. For example, in order to increase the number of daily download users, we further refined the specific operation indicators, such as old-to-new user promotion (2000), app store promotion (2000), and cooperation with other platforms (1000).

In order to increase the average consumption amount, we launch preferential bundling sales, full-discount activities, etc. Through the above goal setting, we can find entry points for targeted system optimization solutions, increase core business indicators, and control operations in all aspects, so we no longer have to grope in the dark. We can also reflect and summarize the areas that did not meet expectations in order to optimize subsequent operational actions.

Source: jonaski