Douyin e-commerce live broadcast review manual

A few days ago, I posted a message on WeChat Moments: "On the importance of reviewing live broadcasts: live broadcast without review is equivalent to no live broadcast."

Does it sound like correct nonsense? I thought, who doesn’t know that reviewing is important when doing live broadcasts?

Yes, there are, and quite a few! After coming into contact with a large number of live broadcast practitioners, I found that most people do not have a systematic review thinking when doing live broadcasts. Especially for newbies, they start broadcasting every day based on their feelings, hoping that good luck will come and the data in the live broadcast room will improve.

They seem to be working very hard, and in fact, it is indeed very hard. The fatigue revealed on their faces after each live broadcast shows that live streaming itself is not an easy task, and it consumes a lot of physical and mental energy.

But in fact, all their efforts are in vain, because they simply do not have the mindset of reviewing and summarizing. Even if they make many new attempts, if they do not review and summarize their experiences, and then use their experiences to do better next time, they will just be standing still.

I am so busy every day that I am exhausted. I am moved by my own efforts, but there is no substantial progress.

On the contrary, those who do well seem to be able to produce good data easily and continue to do better. In fact, that is only what can be seen on the surface. In order to obtain good data, there must be hard and repetitive meticulous execution work behind it.

They will review. They can find reasons why they did some things right, and they can also find reasons why they did some things wrong. So in every next action, you will do better.

1. Record basic data and information

First of all, the first step is to record a lot of basic data and information in a table. Note that we should use a table instead of a document, because the table is more conducive to our subsequent data sorting, and the digital recording method will be more intuitive.

Before we start recording, we need to understand these basic calculation formulas first, because a lot of data in the live broadcast room needs to be calculated. They have been organized into the figure below. Remember to read them several times.

There are two main tables used in the review. One table is the basic data record of the live broadcast, and the other table is the single live broadcast review table. In this step, we will focus on the first table.

The purpose of recording in this table is to facilitate our global overview of the data. Although some data can be seen in the Baiying background, the data is relatively scattered and not centralized enough. We need to record it centrally in the form of a table to monitor changes in the data to guide our subsequent actions.

1. Live data

2. E-commerce data

Includes number of transactions, sales, conversion rate, proportion of fans’ orders, UV value, and average order value.

3. Delivery data

Generally, the data of the delivery is recorded by the pitcher separately, and more detailed data needs to be recorded. The summary data here mainly records several key data, including consumption, number of orders, GMV, traffic, 1-minute stay, and ROI.

If you still don't know how to find this data, you can follow the steps below to get the live data:

(Mobile)

(Computer version - huge amount of responses)

(Computer version - Doudian Compass)

2. Organize and analyze the data

When we have completed the first step of data recording, we need to use another table.

At this time, the data we recorded in the previous step comes into play. We need to fill in some of the data recorded in the first table into this table to facilitate further analysis.

The main purpose of this table is to review a single live broadcast. We need to analyze the large amount of data and information recorded in the first step.

First of all, we need to record some data from the first table here so that we can have an overview of the data for this live broadcast.

1. Analysis of the attractiveness of live broadcast content

The attractiveness of the live broadcast content is mainly reflected in: the maximum number of online users, average stay time, number of new fans, conversion rate, number of comments, and interaction rate . These data directly reflect the attractiveness of the content of our live broadcast room. We need to fill in all the data in the form.

The problem record column in the table is very important. Our field control or operation needs to record in real time during the live broadcast and record all existing problems in the table.

Of course, in addition to recording some bad points here, we can also record the good points.

What are the possible problems that may arise from the lack of attractiveness of content in general live broadcast rooms? We have listed the following points, which you can also check when you are reviewing:

The lack of verticality between short video content and live broadcast content leads to high bounce rates, blocking the reverse heating mechanism;

The short video has a poor effect in promoting the product, and the product display scene, selling points, and performance are not outstanding;

The scene layout of the live broadcast room is not good, and the visual effect is very poor;

The host was not in good shape, and his performance was sluggish, unattractive, and uninspiring;

There are problems with product selection and assembly, and the goods cannot retain customers;

There are problems with activity design and interactive execution;

2. Live streaming sales force analysis

The sales power of the live broadcast room is mainly reflected in: conversion rate, order conversion rate, average order value, average order quantity, and UV value . These data directly reflect the sales efficiency of our live broadcast room. We need to fill in all the data in the form.

Factors associated with data indicators include: accurate traffic, powerful products, related sales, live broadcast display, and anchor guidance.

Low conversion rate caused by inaccurate traffic due to non-vertical content (need to check content quality and verticality)

The visual tonality of the content is poor and cannot support high-order products

Problems with product combination sales and matching plans lead to low average order value

The anchor’s ability to explain and guide transactions is poor

The display and product presentation in the live broadcast room are poor, resulting in low conversion rate and low customer unit price

3. Live streaming traffic optimization analysis

However, we can record more finely. The traffic entrance classification of Doudian Compass will be more detailed. For example, live broadcast recommendations are divided into squares and natural recommendations. We can record them separately, which will be more conducive to our analysis.

For example, from the data of this show, we may find that the proportion of short video traffic is too high, resulting in the anchor always selling products to people who come in through short videos, while failing to retain people who come in through live broadcast recommendations. We can allow people who come in through short videos to interact and sign up first, so that the original rhythm of the sales will not be affected.

4. Short video content optimization analysis

We need to record and analyze short videos separately, and the basic data needs to record the video's playback volume, likes, comments, and shares .

There is a video click-through rate in the table here. How to calculate this indicator?

Similarly, conduct a comprehensive analysis of the short video data indicators and existing problems, and record the analysis results in the review conclusion column.

5. Single product sales data analysis

The last section is the analysis of single product sales data. This is very important. We need to record the product data sold in this live broadcast room into a table, including product name, shopping cart serial number, live broadcast room views, live broadcast room clicks, single product click-through rate, number of paid orders, single product conversion rate, payment GMV, and single product UV value.

The last section is the analysis of single product sales data. This is very important. We need to record all the product sales data in this live broadcast room. By recording the data, we can get a lot of feedback;

For example, the automatic opening and closing oil bottle in our live broadcast room has never been explained by the host once, but the natural transaction data is very good, which shows that this product has the potential to become a hot product. We can explain it more often in the next live broadcast.

3. Summarize the data and form an action list

We have recorded a large amount of basic data and information above, and also conducted analysis. We have drawn some conclusions for each corresponding section. I believe that you now have a basic idea in your mind and know how to adjust and optimize.

But live streaming is not a one-man show, but a group of people fighting side by side. As a trader, you need to keep the team on the same page as you, so the last step is for us to review the situation together.

We need to further formulate specific execution tasks based on the above data analysis conclusions, and assign them to specific persons in charge to ensure that they are implemented in place.

All that remains is to make a clear division of labor and complete all these tasks during the next live broadcast.

I hope the above review ideas and methods will be helpful to you.

Finally, let me say a few more things:

1. At what point should the review be conducted?

It is best to review every live broadcast, but the key review time may be when you have made some special event planning or some special adjustments in your live broadcast room;

Then, for the review of the delivery, if you are a merchant broadcasting yourself, it is recommended to review it on a weekly basis, because the delivery data will have a long-term ROI, and the data of a single game cannot be used to evaluate the effectiveness of the delivery.

2. Ask yourself, “Why did I produce good data?”

I think this is extremely important. For example, our market today was very successful and we sold 2 million shares. Then everyone got excited and the whole thing passed without any sequel. But as a trader, remember to always ask yourself: how did we achieve such results?

You know, nothing good or bad happens by chance, they are all probabilistic. How can we increase the probability of sustained and stable growth in our live broadcast room?

The key is to "work backwards". Think about it. If there is some factor missing, the results you get today cannot be achieved. Keep working backwards and you will be able to find the root cause. What you need to do is to do better what you have done right.

3. How to avoid making the same mistake again?

If you have tried a path before and know there are pitfalls, but you still keep trying it over and over again, making mistakes over and over again, and never summarize the problems, the rules, or the types of mistakes, then there is no way you can make any real progress in doing things.

For example, we already know that saying a certain phrase or doing a certain action is against the rules, so we must avoid it. If we don’t take it seriously, the live broadcast room will soon be ruined.

4. Learn to review others’ experiences

Reviewing is not just about reviewing yourself. Reviewing others is actually more valuable than reviewing yourself because others have already walked the path that should be walked and stepped into the pits that should be stepped into. Since someone has already done it for us, why should we go through it again ourselves?

It is true that you have tried it all and gained experience, but the time cost is huge. There is a big difference between trial and error and making mistakes, so review your benchmarks and peers more often!

– END –

Author: A Tao and Chu Xin

Source: A Tao and Chu Xin