Event operation analysis template, just copy it!

There are often friends in operations who don’t know how to do activity analysis after the activity is completed. It seems like a simple scenario, but it is difficult to analyze it. Therefore, the author has compiled a set of activity analysis templates to save you time and effort. Let’s take a look.

Let’s take a look at the simplest activity scene. A certain fresh food mini program launched a 30 yuan discount campaign for orders over 100 yuan in its mini program (30 yuan discount for every order over 100 yuan), which lasted for one week. Now let's analyze this activity.

Activities have the effect of hitting wherever you point , so when analyzing activities, first figure out: where to point: the time and target of the activity; where to hit: the conditions for achieving the target and the rewards.

1. Decomposition of requirements

Based on this, the activity requirements can be decomposed as follows:

• Activity time: 1 week (X month X day - X month X day)
• Activity object: Order as the unit (regardless of user or product)
• Eligibility criteria: Single order of 100 yuan or more
• Activity reward: 30 yuan off
• Redemption method: Direct reduction, no need to redeem

After breaking down the demand, we can deduce the effect of the activity: since there are rewards for orders over 100, it will stimulate users whose orders are less than 100 to buy more.

Of course, there will also be a counter-effect, because the reward is based on orders, so it is possible to encourage users who have orders of more than 200 to split one order into two and enjoy the discount for both.

If the campaign is done well, there should be a significant increase in orders for 100 units, and total revenue should increase.

2. Design Activity Analysis Table

With the above preparations, you can design the activity analysis table (as shown below).

After designing the activity analysis table, wait for the activity to end and then look at the data! Look, how simple it is.

Don't underestimate this simple analysis table, it can interpret a lot of situations

1. Case 1

Missing increment. As shown in the figure below. The activity did not bring enough incremental growth, with the total order volume only increasing by 490 orders. The additional consumption was not as much as the consumption reduced by 30 yuan off for orders over 100 yuan. In fact, the total amount after the activity was even less.

At this point, we can have hypothesis 1: the event promotion is not adequate, too few new users participate (only existing users participate) or too few existing users participate (the event page is not prominent). If you want to analyze it in depth, you can trace the cause in these two directions.

2. Case 2

There are many benefits. As shown in the figure below. The splitting of orders in the event was too obvious. One order of 200+ was lost, which means there were at least 200 more orders of 100 yuan, which were there to take advantage of the situation. Calculated in this way, the total amount during the event still decreased.

At this point, we can make assumption 2: there are many users taking advantage of the event, and users who spend less than 100 are not motivated enough. If you want to conduct a deeper analysis, you can trace the causes in these two directions.

If the activity rules are changed, the template can be adjusted accordingly. For example, the common "buy 4 items at a time and get one extra gift" can be adjusted as shown below.

If the activity is not targeted at all users but at some users, you can use the ABtest method, set up a reference group (users who do not participate in the activity), and compare the activity effects (as shown in the figure below).

In actual work, there are three common types of activities:

1. For orders (XX off for every order over XX yuan, full postage for every XX yuan)
2. For products (buy XX items of XX products, get XX extra gifts)
3. For people (new customers enjoy exclusive discounts, accumulated consumption of XX years and old customers enjoy XX discounts

For the three major types of activities, you can refer to the above method to make analysis tables. First, explain the effect of the activity clearly, and then look at the incentive effect of the activity on different levels of goods/orders/users.

Only after having a judgment of right and wrong, good and bad, can we further analyze and see where the problem lies. In fact, if there is a problem at a certain level, the direction of the analysis is very obvious. For example, in the above example, order splitting points to high-spending users, and insufficient participation points to low-spending users. Therefore, it is very easy to make a simple analysis table first, lock in the direction, and then go deeper.

Many friends often cannot even judge right from wrong, and have no clear direction, so they start to pull in a bunch of dimensions and break them down again and again, and finally confuse themselves.

3. Details

There is a small problem here, that is, the above template does not take into account the multi-step participation of the activity. For example, add a step: the reward is not deducted directly, but you need to collect the coupon first and then use the coupon. This adds operation steps and will cause new problems: some users may meet the requirements but forget to claim the coupon or claim the coupon but forget to use it.

At this point the analysis becomes more complex. This topic will be discussed specifically in the next article when we talk about new customer acquisition analysis.

Author: Coder Bear

Source: WeChat official account: Coder Bear