With the in-depth development of the Internet, the food industry is facing unprecedented challenges and opportunities. Traditional marketing methods can no longer meet the needs of consumers, and the rise of private traffic has provided food companies with a new, low-cost and efficient marketing method. This article will explore how the food industry can solve three pain points in the private sector.
1. The importance of private domain operations
Private domain operations refer to the user traffic that enterprises gather on their own platforms and can be directly accessed. Compared with public domain traffic, private domain traffic is more accurate, stable and cheaper. In the food industry, as consumer demands become increasingly personalized and quality-oriented, the importance of private traffic becomes increasingly prominent. By establishing their own private domain, food companies can better understand consumer needs, provide personalized products and services, and improve consumer experience, thereby increasing user stickiness and repurchase rates.
2. Three pain points in the food industry’s private sector
User portrait is unclear
If a food company wants to establish its own private domain, it must first clarify who its target users are and what their needs and preferences are. However, when many food companies operate in the private sector, they do not clearly portray user profiles, making it difficult to accurately reach target customer groups, unable to provide accurate products and services, and affecting user experience and repurchase rates.
Sales expenses are high but efficiency is low
Many food companies do not use marketing automation tools and rely on manual operations and experience, resulting in high labor costs, low efficiency, and the inability to accurately reach high-value customers .
Lack of effective user operation methods
In the private domain, user operation is the key to improving user stickiness and repurchase rate. However, many food companies lack effective user operation methods when operating in the private sector, resulting in serious user losses and low repurchase rates.
3. Strategies to solve pain points
So, how to solve the above pain points, and how can users operate it and make profits? Feisuan Technology provides corresponding solutions.
As a "new generation of digital technology service expert", Feisuan Technology has been deeply involved in the fields of digital technology and artificial intelligence technology for many years. It has successively launched SoFlu software robot, SoData data robot, AI.Modeler modeling robot and overall industrial digital solutions. It comprehensively covers the three different stages of digital transformation: business systematization, data development and governance, and applied digital intelligence. It improves the technical capabilities of Chinese enterprises in a fully automatic and intelligent way, and comprehensively assists the digital transformation and upgrading of Chinese enterprises.
In terms of private domain operations, Feisuan Technology has launched a solution of “automation + artificial intelligence + large model”.
First, “Large Model + BI Enhanced Analysis”—AI.Insight
Through AI.Insight, the generative AI of large models is introduced, and large models are combined with small models. The small models perform analysis and recommendations, while interaction and decision-making are implemented by the large models.
AI.Insight generates functions such as customer portraits, trend analysis, attribution analysis, and difference analysis to meet the needs of business departments. The process supports natural language interaction. Users can use natural language and semantics to search for any questions, and the answers are displayed in the form of insights, reports, and recommended dashboards, thereby lowering the barrier to use and allowing business personnel to participate.
At the same time, it also has the function of "intelligent insight", which can automatically perform time series anomaly detection, causal correlation, fluctuation attribution and other reason analysis on the data, and give a conclusive description; perform Auto OLAP analysis on data insight points, supporting roll-up and drilling Multi-dimensional analysis such as taking, slicing, and dicing. Customer characteristics can also be analyzed based on data insights to locate abnormal customer groups.
Secondly, “automated modeling tool”—AI.Modeler modeling robot
AI.Modeler modeling robot is a modeling platform for data processing and model development, covering the entire life cycle of analysis, cleaning, derivation, selection, iteration, and online in the field of data modeling. Through the "AI.Modeler modeling robot", compared with hiring algorithm experts, automated modeling has a low threshold, high efficiency, good results, and can quickly produce results to meet business needs.
Finally, "automated marketing"-automated marketing platform
Through the "automated marketing platform", various marketing systems are opened up, marketing effects are integrated into one platform, and automated marketing is realized through closed-loop marketing management, marketing strategy optimization, marketing resource management, event design, and event execution.
At the same time, the "automated marketing platform" can also be linked to "AI.Insight" to form customer insights; it can be linked to "AI.Modeler" to obtain accurate shortlists to help business personnel formulate effective marketing strategies.
It is reported that the "automation + artificial intelligence + large model" solution has been verified by several customers in multiple industries. Feisuan Technology won the "2023 Digital Transformation Practice Award" with its original technology and outstanding achievements in assisting enterprises in digital transformation. ", "Breakthrough Technology Achievement Award", "Innovation Leading Enterprise" and other heavyweight awards.
Summarize
With the development of the Internet and the upgrading of consumer demands, the food industry is facing unprecedented challenges and opportunities. Building a private domain is an inevitable choice for food companies in the future, and solving the three pain points of unclear user profiles, difficulties in content production, and lack of effective user operation methods is the key to success. Through strategies such as accurately portraying user portraits, improving content production capabilities, and strengthening user operation capabilities, food companies can better establish their own private traffic pools, improve user experience and repurchase rates, and thus stand out in the fierce market competition.
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