Double 11 Marketing Activity Analysis Manual

Double Eleven is approaching, and it is the day when major companies launch intensive discounts and promotions online. Girls often prepare an activity guide or shopping list.

Data analysts certainly also need to prepare a preparation manual, but it does not contain product names, but a collection of analysis methods. Otherwise, once the activity is over, various analysis requirements will come down like an avalanche. Not only do I have to work hard and overtime, but I am also often accused of things like “Your analysis is too superficial! Why don’t you have deep insights!”

Today, let’s take stock of what analytical preparations data analysts should make for marketing activities . Help everyone solve their worries so that they can happily shop when big sales come.

01 Master the basic types of marketing activities

The rules of marketing activities are varied and the names are strange, which often confuses people. If you don't grasp its essence, you may have to list dozens of analysis templates, which will tire the data expert to death.

Putting aside the complex and specific forms, from a business management perspective, marketing activities can actually be divided into five categories, each of which has similar data focus points.

As shown below (click on the picture to see the high-definition picture):

Before doing activity analysis, first understand the activity rules clearly and classify the activities. In this way, each type of activity has a unified template output and unified standard assessment. It is convenient for data analysts to prepare reports and enable horizontal comparison to obtain richer conclusions. Some activities planned and operated may use fancy words that may confuse people. You can use this logic diagram to simply classify them and find their theme ideas.

02 Clarify the analysis ideas of marketing activities

Marketing activities are different from regular business activities. They are short-term, high-intensity actions carried out for specific goals. Therefore, the sense of purpose in analyzing marketing activities needs to be particularly strong. The entire analysis revolves around the following objectives:

• Whether the goal is achieved
• If not achieved, what is the reason?
• If the goal is achieved, can efficiency be optimized?
• What is the impact on overall operations after achieving the goal?

When multiple activities are carried out at the same time, follow the order of "categorized, from small to large". Start with a single event.

First look at the achievement of single activity goals and efficiency.

Based on the activity goals, make a good/bad evaluation of the current activity. The evaluation will directly affect the subsequent analysis. If it’s good, summarize the experience; if it’s bad, analyze the reasons. This is the most basic analysis. Make a judgment first and then find the cause. Otherwise, you may go in the opposite direction.

Let’s look at the same type of activities, past achievements, and efficiency.

The data is interesting when viewed together. For example, in order to attract new users, you may have done 4-5 types of activities. By putting the past records together, you can see whether the overall effect of such activities is getting weaker and weaker, and which activity is the best benchmark, and what is good/bad about it compared to the current activity. This will give you a clear benchmark when looking for the cause and make it easier to draw conclusions.

Third, look at the cross-effects of different types of activities to see whether they have improved the overall situation.

For example, there may be product activities and user activities going on at the same time. Will have an impact on user conversion rate. So under these multiple influences, has the user conversion rate been improved, and has the user structure reached our ideal state? If the superposition of multiple effects does not achieve the expected results, then we must seriously reflect on whether the overall strategy needs to be adjusted. (The monitoring idea is similar to the example in the figure below, of course there can be more dimensions).

Fourth, look at the overall marketing cost input-output ratio and the degree of dependence on performance marketing.

This can help us discover a warning of danger: Is the company too dependent on marketing? Is the marketing expense out of control like a runaway horse? (The monitoring idea is similar to the example in the figure below, but there are certainly more dimensions).

Often when planning or operating an event, too much emphasis will be placed on the effect of the event, spending too much energy on just one part. The purpose of doing this is simply to desperately prove that one has done a good job in this event. If data analysts only stay at this level, they will fall into sophistry, bickering, and endless arguments. It will not be able to reach depth and height. Therefore, before officially starting work, you must sort out your thoughts. This is where data analysts are more valuable.

03 Manage and record preset goals

It is very important to set goals. The goal is the only benchmark for measuring the effectiveness of an activity, so it must be discussed clearly in advance. If there is no clear goal beforehand, not only will it be difficult to start the analysis afterwards, but it will also make people question: if you don’t even know the goal and you design the activity in a muddle, how can you expect good results?

Point 1: Not all campaigns have sales targets.

For example, brand activities are not intended to drive sales, so they can set non-sales indicators such as reading volume and number of likes.

Some planning, operations, and promotions are very speculative. There are no jump sales links or means of bringing goods in the activities, but they insist on forcing a proof: I also promoted sales. This is absolutely ridiculous. There is not even a link, and it cannot be attributed at the data level.

When setting goals, keep in mind: if an activity is to bring sales, there must be means to bring sales and assessment requirements; if not, then simply don’t set sales targets. All those talks about "indirect influence", "deeper effects" and "mental inspiration" are just attempts to fish in troubled waters.

Point 2: Not all activities have a reference group.

If it is a big promotion event, the company will invest huge amounts of money and the goal is to attract as many consumers as possible. It is meaningless to set up a reference group at this time - if there is a reference group that is not affected, it proves that the promotion is not done well, and some people are not affected even though a lot of money has been spent.

For big promotions, more attention is paid to the marketing of overall indicators, focusing on total amount and maximum value. If it is a commodity, the focus is on the trend of the entire commodity life cycle and the rhythm of purchase, sales and inventory. When launching a product, one should focus on distribution and sales volume, so that the new product can occupy the market as quickly as possible. When it reaches the mature stage, you have to pay attention to the sales and inventory rhythm, control replenishment, allocate goods to places where there is still demand, and gradually reduce inventory. When a recession occurs, you need to get rid of goods as quickly as possible to reduce inventory costs. Commodity categories are often compared with similar products in terms of life cycle.

These two types of data views are shown in the figure below:

Point 3: There are two ways to approach the reference group, choose reasonably.

Generally speaking, user activity reference groups are set up before and after the activities, focusing on whether user behavior has changed habits and improved quality due to the activities.

For precision marketing, the same group of people are divided into two groups for comparison based on response/non-response. This way you can observe the precise effect. However, many current user activities based on APP, websites, SMS, and outbound calls are actually personalized recommendations, which close the promotion channels. Therefore, they can also be set according to response/non-response. The specific difference is whether the propaganda channels are closed. Only those that can be closed are divided into two groups, otherwise they are compared before and after.

As shown below:

Point 4: For process indicators, there must be an outcome indicator for assessment.

This type of question refers specifically to new users, active users, and retention users. These three indicators are often not the ultimate results pursued by enterprises. If they are evaluated separately, it is easy to cause false prosperity. Therefore, a quality indicator is needed. For example, new users’ activity within 7 days after registration, conversion rate, etc.

This is a long post because the biggest problem with activity analysis is the goals:

• No goal: I do what my boss tells me to do...
• The goal is empty: just to increase sales, but I don’t know how much…
• Mixed goals: attract new customers, promote activation, retain customers, and convert customers all in one go!
• Goal Bullshit: We have an immeasurable and far-reaching impact, mind-changing!
• The goal is false: There are many new users and the activity rate is high, so why are there no conversions?
• Random goals: Ah, the activity is not working well, let’s change the goals and the reference group.

All of these will turn subsequent analysis into meaningless wrangling. Therefore, setting a clear, specific and disciplined goal is to do 50% of the activity analysis well. Everyone should remember this.

04 Be prepared to monitor the activity process

Before the formal analysis, it is important to monitor the activity process. Especially when there are many activities, clear records should be kept of each activity’s page embedding, user data collection, business launch time, etc. If records are not kept beforehand and various data are missing, it will be impossible to analyze afterwards.

During monitoring, priority should be given to target achievement.

• Goal achieved: activity successful, summarizing experience
• Goal not achieved: Activity failed, review and lessons learned

Note: If during the activity, it is monitored that the target achievement rate is very low. We can immediately enter the second step: cause analysis and experience summary stage. Make timely adjustments to promote goal achievement. Instead of changing the reference group and trying to get away with it.

05 Do a good job of pre-event analysis

Marketing consists of at least 8 steps:

1. Set goals
2. Insight into user needs
3. Select your product
4. Packaging selling points (price, performance, brand)
5. Design communication content (copywriting, pictures)
6. Select delivery channels (time, location, content)
7. Delivery-User response (jump link, landing page, conversion page)
8. Post-response service follow-up (answer, delivery, after-sales)

Among them, 1-4 are the main considerations in the early planning stage, and 5-8 are the main considerations in the implementation stage. Before launching an activity, you need to have good insights and identify the needs and selling points in order to achieve good results. There may be many pre-analysis topics here, such as insights into user needs, AB testing of plans, activity benefit estimation, sales forecast, inventory quantity forecast, etc., which will not be expanded upon here one by one. If necessary, data analysts can conduct pre-analysis on a project-by-project basis. You can also take out past project review reports and summarize the existing experiences and lessons by activity type. If you plan well in advance, you will have less trouble afterwards.

06 Master the activity execution plan

During the course of the event, it is likely that the business department will make some temporary adjustments. Especially for links 5-8, this is where the most problems occur and where the most adjustments are required.

Such as low conversion rate of delivery channels, unreasonable distribution of delivery, poor copywriting effects, problems with jump links, etc. It is important to understand the planned activities and any unexpected problems and adjustment plans that may arise during the activities in order to analyze the activities.

These execution bugs and corrections are important factors in contributing to the final effect of the activity, and only by understanding them in a timely manner can a comprehensive analysis be made. Therefore, it is necessary to communicate well with the business, get the plan, and understand the progress in a timely manner, so that everything can go smoothly.

07 Summary: Good analysis results come from good preparation

Many students who work in data have been criticized for “not being thorough enough in their activity analysis” and “you can also do operations, so what are you doing here?” These are all due to lack of good preparation. Not enough understanding of the activities, not enough understanding of the execution, and no good accumulation of past experience. In the end, we can only talk about numbers and scratch our heads at the performance curve.

Or they are prepared but lack integrity, and dare not raise objections when faced with arbitrary changes in business objectives or modifications to goals, and dare not keep minutes of discussion meetings. As a result, post-analysis turned into following the trend.

These cannot be blamed entirely on students who work with data. After all, many companies do not have a formal analysis system and lack respect for data. But this does not prevent us from working in the right direction and striving for our ideal state. After all, there are arguments everywhere, but the skills you develop are your own. Let’s share this with everyone.

Author: Down-to-earth Teacher Chen

Source: Down-to-earth Academy