I used DeepSeek to write an impeccable marketing plan for Xiaohongshu

"DeepSeek empowers Xiaohongshu marketing, a new chapter of efficiency transformation." In the field of Xiaohongshu marketing, why is DeepSeek the key to improving efficiency? How does it play a role in strategy, data and public opinion? How can marketers correctly use DeepSeek to improve work results?

DeepSeek is not only good news for China's AI industry, but also good news for us marketers.

If you are also a marketing worker, and have not used DeepSeek to improve your work efficiency, or do not know how to use DeepSeek

Please read this article carefully, I will share my own application method

In my daily work, there are three scenarios where DeepSeek is used to improve performance.

They are: strategy combing, data analysis and public opinion monitoring, a lot of useful

1. Strategy review

Don’t be silly and ask DeepSeek: “Please help me write a brand placement plan for Xiaohongshu.” This instruction is like asking a doctor, “I’m sick, please prescribe some medicine.” All you get is Isatis root.

Think of AI as your super B-party. It has top-notch capabilities, but you need to give clear requirements. The more information you provide, the more accurate the strategy it gives. If the answer is too broad or too general, it is not AI's fault, but because there is too little instruction information. AI can only give standard answers.

Correct command example: "You are now the Xiaohongshu manager of a new skincare brand with VC fund background (customer unit price 389 yuan), and the main product is 'Blue Copper Peptide Anti-Aging Essence'. The core advantages are: ① Microcapsule packaging technology jointly developed with the Chinese Academy of Sciences ② The actual 28-day wrinkle reduction effect exceeds that of a brown bottle ③ Replaceable environmentally friendly packaging. Competitors are HBN di-retinol and Proya Ruby. The budget is 300,000 yuan, and the requirements are:

1) Design a 6-month seeding-harvesting path based on the reverse funnel model 2) During the 6.18 promotion, the Tmall flagship store’s gift mechanism should be linked 3) Three differentiated scenarios should be embedded: those who stay up late to watch TV series, those who work out without makeup, and those who travel light 4) ROI estimation needs to distinguish between the content seeding period (January-March) and the conversion harvesting period (April-June)

Please output a plan that includes competitor content analysis, budget allocation Gantt chart, and risk warning."

Then you will get a very logical solution. Of course, it is not recommended to apply it directly. You still need to optimize it and fill in the gaps before applying it.

Our team has integrated DeepSeek into the workflow, which is of great help to the efficiency of strategy formulation. You may wish to try it out.

2. Data Analysis

Humans need data analysis, but often fail to do it well

Because it is difficult for people to not be influenced by their own subjectivity when doing data analysis.

But DeepSeek can

Similarly, don’t just throw your data in for analysis. It’s better to pre-process the data first.

First, clean up the outliers. For example, is there a sudden surge in the volume of a certain note because of a celebrity's style? Manually mark it out, and then add dimension tags. You can mark it by content type: dry goods evaluation/collection implantation/single product recommendation, etc. Finally, add battlefield intelligence and synchronize competitive product information, such as the launch of competitive products during the 618 period.

Instructions should have requirements and standards.

Instruction example: Please use the DuPont analysis method to analyze the Q2 launch effect, focusing on the following observations:

① Whether the interaction cost of mid-level KOLs (50,000-100,000 followers) fluctuates abnormally due to the 618 promotion ② Compare the collection rates of "First Aid for Oily Acne Skin" and "Anti-Aging" ③ Warning notes with >10,000 interactions but <0.5% add-to-cart rate (suspected interference by water army)"

You can also create a library of popular articles by placing content and data from competitors

Command example: crawl or export 200 competitive hot articles from Qiangua

① Use the LDA topic model to extract the TOP3 content tags ② Draw a heat map of user comment sentiment fluctuations ③ Identify high-frequency non-standard scene keywords (such as: dating first aid/mask face)"

And use existing data to predict future ROI

Example of an instruction: Based on historical data and the following variables:

Xiaohongshu's on-site traffic costs increased by 12% quarter-on-quarter

Competitive products are expected to launch alternatives in Q3

The platform will upgrade the algorithm weight in September

Please use Monte Carlo simulation to predict the ROI distribution range of three budget allocation schemes

You should know that the parent company behind DeepSeek is Huanfang Quantitative. The strongest ability of quantitative companies is to predict future market conditions based on historical trading data. DeepSeek is extremely strong in this aspect of reasoning and prediction.

3. Public Opinion Monitoring

Before, there were no AI tools

Our approach is to write semi-automated scripts to capture all related notes in real time every day, and then check the public opinion system to see which notes have sent out keyword alarms, and then mark them for processing. This actually has a certain technical threshold. Not to mention service providers, many brands do not have such a public opinion monitoring system.

But for now, DeepSeek is enough

Feed your notes every day and use different sets of instructions for automated analysis, which is fast and accurate.

Note monitoring command example: Real-time monitoring of the following variant expressions:

① Direct negative: difficult to use/allergy/fraud

② Advanced black: "What else do you want a bicycle at this price?" (with angry expression)

③Fishing question: "Am I the only one who thinks that brand XX is useless?"

Example of comment monitoring instructions: Analyze user comments: ① Identify the rhetoric of "pretending to be a hater" (such as madly recommending a product but actually attracting traffic to competing products); ② Mark the key turning point of "passers-by turning haters" (the comment trajectory from "nice packaging" to "poor effect"); ③ Capture the subtext of emojis (the [smile] expression may express sarcasm)"

Example of a prediction instruction for the probability of a bomb explosion: "Assess the public opinion risk level based on the following dimensions:

Negative voice growth rate (≥50 new negative reviews per hour?)

Nature of communication nodes (ordinary users vs. industry KOLs)

The intensity of emotional contagion (the secondary transmission rate of negative comments)”

4. Final Thoughts

Believe me, if you find DeepSeek difficult to use and are not satisfied with the answers, it is definitely not DeepSeek's problem, but your problem. The limits of AI's answers depend on your cognitive limits.

AI output value = question depth × demand granularity × number of feedback iterations

When you can use DeepSeek to generate a set of Xiaohongshu marketing strategies based on the anti-funnel crowd strategy, data analysis of the weekly delivery situation and public opinion monitoring on a daily basis

You will understand that the reason that prevents marketers from leaving get off work is never the workload, but the prejudice that "AI is always unreliable"