Why are most brands wasting their efforts on creating hit products?

For users, when a brand is mentioned, many people’s first reaction is its hot-selling products. If there are no particularly outstanding products, then there is a high chance that the brand is not well known. However, creating a hit product is not an easy process. Many companies have invested huge amounts of manpower and material resources but have not achieved the expected results.

1. Ask a question

I have come into contact with many brands in the past two months, and I found that many people only use the conventional understanding of ROI (return on investment) to evaluate the effectiveness of their campaigns, but do not know how to determine indicators through the overall chain, how to collect and analyze data, how to evaluate which methods are effective, and how to plan team tasks to be responsible for the overall results, etc.

There is no base point (benchmark data) for the delivery, and people only look at the ROI from a single point, and feel that no channel is suitable; people just follow what others do, but cannot find their own rhythm; they lose money on channels, and cannot see the end of recovering the funds; because individuals do not think clearly, the team can only follow behind and continue trial and error, and cannot establish a united front.

After struggling for a long time, we still haven't formed good insights and strategies, nor have we formed stable and productive partners in terms of resources. As a result, from beginning to end, nothing has been achieved and we are still very passive.

2. Solution

Target breakdown:

Before solving the above problems, you must first determine your goals, break down the traffic structure that affects the sales of a single product, and then determine how to obtain these traffics separately. The approximate data dimensions are as follows:

Filling:

When filling the data in the frame, how do you determine the specific data?

A quicker way is to find a benchmark. I want to achieve a certain scale. For example, if I want to be in the top 5 of a category, I need to sell * pieces per month. Then I can look for brands in the same category that have already achieved this scale.

Analyze its data, traffic structure, playing methods, etc. Some products may be marketed through distribution, some through Taobao affiliate marketing, some through off-site promotion to attract traffic and conversions within the site, and so on.

Through the above analysis, determine which style of play is suitable for your team, and then match the corresponding data structure. This forms the preliminary data target for your product.

In the data collection after the actual operation, the data in the framework will be corrected according to the actual situation, and finally the actual data suitable for one's own company will be formed to prepare for the future hit of single products.

Data Recovery:

After filling in the above data goals, what needs to be done is to sort out the resources and corresponding expenditures to achieve the goals, such as the delivery of Xiaohongshu, Kuaishou, Douyin, Bilibili, etc., and how much money is invested in each channel. Should we use the resources we have already accumulated, or look for new media, etc. All that remains is to get the process running and then collect the data.

How to recycle data? As we all know, the purpose of our advertising is to obtain the number of searches within the site.

The general consumer's path from seeding to conversion is as follows:

Being attracted by the product outside the site - Searching within the site - Clicking on keywords to enter the store - Immediate conversion/Not paying yet but thinking the product is good, collecting or adding it to cart - Placing an order from your own collection/add to cart after there is an event or the demand is confirmed in the future

Therefore, the data structure we need to recover is as follows (all the following data structures are for the link from off-site delivery to on-site transaction)

In the above delivery efficiency table, the number of searchers and the number of store visitors record the target data and the actual data respectively, in order to solve two problems:

• The number of searchers is closely related to the quality of the delivery. From the perspective of the entire chain, the number of searchers will largely affect the sales of single products on the site. We make up for the gap in the number of searchers by optimizing off-site delivery.
• Consumers who search for keywords on Taobao may not necessarily click to enter the store, but whether they can enter the store also determines sales. There are many factors that affect the store entry rate, such as whether the header image matches the product that is being promoted outside the site, whether it is obvious enough, whether the title contains the keyword nickname, whether the copy/activity is attractive. If there is a gap, or the proportion of searches to store entries is very low, this problem needs to be solved in a timely manner.

The number of searches is increased by external advertising. In the above picture, visitors and customer acquisition costs are related to expenses. Are our expenses only for the part that is advertised? How to conduct statistics?

The approximate dimensions are as follows (the specific dimensions shall be based on the actual channels and data of the delivery):

Some people may ask, why does the fee include Taobao? Everyone should understand that we are responsible for a single product, which is a combination of on-site and off-site efforts. If the off-site work is good and can attract traffic, but the on-site work cannot keep up, then it will still be difficult to sell this single product.

Well, now that we have spent the money, we need to know where the money is spent outside the site so that we can calculate the corresponding efficiency, so we need to count our channel data.

I believe some of you may find it strange, why are these channels still counted as incremental? I will explain this in detail in the channel data collection section later.

Calculation formula:

With the above data, it will be easier for us to calculate our ROI, search expected sales and corresponding expenses.

The data formula is as follows:

Calculate ROI = (number of payers * unit price + number of favorites * shopping cart conversion rate * unit price) / marketing expenses of manual search (including commission and product sales treasure)

Number of sales = number of visitors * search traffic to store conversion rate + number of visitors * average collection and purchase * shopping cart conversion rate

Estimated cost = target number of searchers / ratio of playback volume to site / CPM

In order to make the formula more efficient, you need to fill in the corresponding data based on the part that you quickly ran out before.

For example, the data I have here:

Current CPM = X

Conversion rate from off-site playback to on-site search = Y‰

The ratio of search number to store entry number = Z%

Direct conversion rate of search traffic into the store = A%

Average collection and purchase rate = B%

Shopping cart conversion rate = C%

After filling the above data into the formula and combining it with our target sales (corresponding number of sales), it will be easier to work backwards.

For example, based on Formula 2 above, combined with the number of sales, I can reversely infer how many visitors I need, and then use the number of visitors to infer my target number of searchers, and then based on Formula 3 I can deduce the budget I need to spend on the platform.

All that remains is to arrange relevant personnel to carry out the execution within this budget and CPM. But don’t forget one thing: during the execution process, you must continue to record data.

Because data is constantly changing, we need to constantly correct and update it through different delivery methods until we find that every data that can be filled into the formula is the best.

Observe changes:

Now that we are talking about obtaining optimal data through off-site testing. Let me briefly explain that in the actual delivery process, I may do one more step than everyone else does now.

This is the data of Kuaishou’s recycling:

This is the data of Xiaohongshu’s recycling:

If you look carefully, you should have noticed that I did not collect statistics on the experts in a certain period of time, but every day.

Yes, I will ask for the data of the experts to be recorded every morning. By recording this data I can learn a lot of additional information.

For example, which influencers’ data stagnated a long time ago, which ones have continued to grow, and how long is the growth cycle.

At the same time, I can judge how much I need to supplement through the changes in channel incremental data, and make adjustments to the subsequent delivery progress and delivery volume (answering the question of statistical increments in the channel data table above).

The most important point is that through these data, I can analyze the content involved in the delivery, such as which content angles or scenarios are more likely to bring sustained growth in traffic; in addition to the content, do these influencers with this growth have anything in common, such as fan range or personality positioning, etc.

If I want to use Xiaohongshu French Fries or Kuaishou Vermicelli to increase exposure, I will be very clear about which influencers I should prioritize, and whether I should have a secondary collaboration with these influencers or actively cooperate in live broadcasts, etc.

Therefore, when testing and recording in the above data framework, as the delivery method and rhythm change, the key data in the previous formula will also change. Make active adjustments while doing it, and keep finding the data that can have the best impact on the results.

On this basis, once you have determined that the production is satisfactory to you, do not hesitate and invest heavily until you destroy this channel.

Create hot products:

Having said so much, many people may ask, if we do this, can we definitely create a hit product? I can say with certainty that it is not necessarily the case!

Why? Because this is only part of the strategy for creating a hit product. If the strategy is out, it will not work if the product selection is wrong and the market does not buy it, it will not work if the execution is not in place, the content cannot be stuck, the path settings are redundant, the data statistics are wrong, you cannot find reliable suppliers to spend the money efficiently, you cannot spend money to achieve quantitative changes and qualitative changes, and you do not have the funds and mentality to trial and error.

Products, strategies, execution, resources, funds and mentality are all indispensable. Only when these six can grow together during the running-in process and always serve one goal, will it be possible to produce a hit product.

Conclusion

There are limitations on resources, time and money when doing anything, and our energy is also limited. Many times, people do useless work because they don’t understand the main theme of the work, whether the team or individual is working on the core value chain, and whether they have accumulated company/individual resources or advantages over the long term.

For brand executives or CEOs, creating a hit product is 70% strategy and 30% execution. Without insight and strategy, we will fall into blind and endless execution.

To solve the strategic problem of creating explosive products, several necessary capabilities are required:

• You need to understand the entire process from seeding to conversion within the site;
• Understand the data of each key funnel in the whole chain;
• After establishing the above framework and basic data, we will conduct continuous testing in practice to verify and calibrate the data until we find the optimal combination.
• Spend money boldly on the optimal combination to maximize benefits.

PS: The above content is the logic and method I use when promoting popular products. It is more suitable for use when there are few products and when doing early launch tests. It is difficult to be so meticulous if a brand is promoting many new products and channels at the same time.

Not only will the calculations for different time periods and different methods be different, but different companies will also have different calculation habits. The key lies in the implementation of logic, which can be used as a standard for evaluating the quality of a company's products. It must remain systematic, and specific situations must be analyzed specifically to find the rhythm that produces the highest output.

Author:Sally

Source: Sally