AI in agricultural marketing is a topic that is increasingly coming up in discussions about the future of agribusiness. Is AI in agriculture actually changing the way manufacturers of fertilizer, machinery, feed or financial services reach farmers?<\/p>\n
Agriculture in Poland, since joining the European Union, has become part of a global system of interconnected vessels, and agro marketing must find its way in this game. So it is worth asking the question, where are we really with the use of AI in agricultural marketing? What is working? What is a myth? What is yet to come?<\/p>\n
Agriculture has long been referred to as <\/span>\u201ecloud factories\u201d<\/span><\/i>. In practice, this means that production planning is subject to huge risks, both weather and market risks. Weather conditions are one of the main risk factors in Polish agriculture and affect planning marketing activities<\/a>.<\/span><\/p>\n Since Poland joined the European Union, agriculture has ceased to be a purely local occupation. It has become part of a global system of interconnected vessels, in which demand and supply at one end of the world affect prices in Poland. The price of corn in Poland depends on the drought in Argentina, the supply of corn in the U.S. or currency exchange rates.<\/span><\/p>\n A farmer invests in inputs in advance, often not knowing what the purchase price will be 8-9 months from now when he harvests. Cattle, poultry or swine farmers also operate under conditions of uncertainty. Animal diseases (ASF, bird flu, bluetongue) can wipe out a season in a matter of days. At the production planning stage, it is important to identify and analyze potential risks that could affect farm efficiency. EU subsidies, which once stabilized the market, are now limited.<\/span><\/p>\n Polish agriculture today faces the need to adapt to modern technological solutions. Implementing modern technologies in agriculture involves adapting them to different types of farms and integrating them with existing systems. An example of such solutions is precision agriculture, which enables precise management of resources, optimization of crops and minimization of environmental impact through the use of AI, GPS, drones or soil sensors.<\/span><\/p>\n Under such conditions agricultural marketing<\/a>, and thus the activities of companies producing machinery, fertilizer, feed, crop protection products or financial services, is becoming a game of<\/b>. At stake here is <\/span>attention and trust of the farmer<\/b>, and the opponents are competing companies, the media, the digital giants' algorithms and the environment itself. The biggest challenge for companies is to reach the right audience among diverse holdings.<\/span><\/p>\n In this competition, competing companies and media are constantly raising the bar, and those who are quicker to innovate are gaining the advantage. Of increasing importance in the agro industry is the need for a holistic approach to marketing strategy, integrating various communication tools and channels. The agro sector requires specialized, integrated marketing activities that address specific market needs. Agriculture itself is not only a production activity, but also a key component of socioeconomic development, which requires appropriate marketing strategies for growth and competitiveness.<\/span><\/p>\n Several rules apply to this game: agriculture is chaos and risk, the structure of farms in Poland is based on small and medium-sized entities, and segmentation should be based not only on hectares, but primarily on <\/span>economic size (WEG)<\/b> and specializations (orchards, vegetables, poultry farms, mushrooms). An effective marketing process requires an understanding of the specifics of customers in the agro sector, their needs and preferences, which makes it possible to better tailor communications and offers.<\/span><\/p>\n Farmer<\/b> is the main player - he decides what he will buy. <\/span>Manufacturer and supplier<\/b> (machinery, fertilizers, banks, insurers) are vying for his attention. <\/span>Local distributor<\/b> is often the most important brand ambassador. <\/span>Marketing agencies<\/b> translate the language of the producer into the language of the farmer. <\/span>Digital giants (Google, Meta)<\/b> provide advertising infrastructure, a <\/span>publishers and industry portals<\/b> are responsible for content and traffic. Customer relationship management and marketing effectiveness are key to business development in the agro industry. Companies that better understand customer needs and implement modern solutions can gain a competitive advantage in the agribusiness industry.<\/span><\/p>\n Everything is affected by <\/span>environment<\/b> - Weather, prices, regulations. Smaller farms face additional challenges in managing and adapting to change, requiring dedicated solutions and support.<\/span><\/p>\n Three concepts are often mixed up in conversations about AI:<\/span><\/p>\n Artificial intelligence-based tools make it possible to analyze data, monitor trends and make more accurate marketing decisions in agriculture.<\/span><\/p>\n In marketing terms, AI would mean a system that analyzes the customer's needs, designs the product, sets the pricing strategy and conducts communication. <\/span>There is no such solution on the Polish agro market today.<\/b> Rather, what we have are elements of machine learning and automation.<\/span><\/p>\n Today we are using the word \u201eAI\u201d more often as a marketing buzzword. In practice, agricultural companies use machine learning algorithms or database-based systems. This is not yet AI in the strategic sense.<\/span><\/p>\n Google and Meta have advanced AI algorithms, but they are not created specifically for agriculture. Their goal is to optimize ad impressions - whether farmer or golfer, the mechanism works the same. Targeting is based on cookies and user behavior. In the EU, the RODO barrier comes in, which means that targeting is general, not precisely agricultural. Google and Meta always \u201ewin\u201d because they make money from ads, but do not build a product strategy for agro. So it should be emphasized that Google and Meta always make money, but the real value depends on the data the agency or publisher provides.<\/span><\/p>\n Portals depend on Google and fight for traffic. Clickbait (prices, subsidies, sensationalism) wins, and substantive content needs promotion. Massive reach does not automatically translate into effective sales marketing in agriculture. AI appears indirectly in cookie prediction, but is not used directly as a marketing tool.<\/span><\/p>\n According to 2023 data, there are 1.21 million farms in Poland, more than half of which are units under 5 hectares. A viable target group for agro marketing, however, are larger farms. Those over 50 hectares number 43,832, which amounts to just 3.6% of all farms. This means that agro portals boasting hundreds of thousands of unique users actually reach mainly the mass of small farms, which are not a key target for manufacturers of fertilizers, machinery or financial services.<\/span><\/p>\n SaaS tools (ChatGPT, Jasper, MidJourney) help write texts, make graphics and analysis. They can generate material about a farmer, golfer or tourist - it doesn't matter to the program. This speeds up the agency's work, but does not replace expertise. Massive AI - content can lose credibility with Google and farmers. AI is a helper, not an author. AI in agricultural marketing works well for research and personalization, but authority is still built by humans.<\/span><\/p>\n True AI needs massive data from users. In Poland, it is difficult to gather tens of thousands of farmers with complete data, and agriculture is too dependent on local conditions (soil, climate, regulations). Even global models may have trouble adapting. Moreover, if all farmers were given the same recommendations (e.g., sow wheat of variety X), supply would increase, while prices would fall. The competitive advantage disappears. AI in agribusiness as a full-fledged marketing \u201eplayer\u201d is an idea rather than a practice today.<\/span><\/p>\n Artificial intelligence is becoming a key tool that enables agribusinesses to build real competitive advantages in sales and communications. As in crop production, we are entering an era of precision in agricultural marketing. Intelligent systems allow real-time monitoring of farmers\u201e buying behavior, deep analysis of market data and early detection of customer trends and needs. Instead of \u201dsowing\" ads widely and ineffectively, marketers can now precisely get their message where it is needed.<\/span><\/p>\n Implementing AI in agro marketing is an opportunity to fully control the effectiveness of campaigns. Thanks to artificial intelligence, companies can react faster to the actions of competitors and changing industry sentiment. In a sector where seasonality and relationships are key, an approach based on data rather than intuition is becoming the foundation of market success.<\/span><\/p>\n Our capital group combines research, portals and agency. We reach tens of thousands of farmers every day. We use AI for analysis and campaign optimization. The biggest advantage is that we feed Google with fresh cookies from our portals, so campaigns are targeted precisely at farmers. Combined with content marketing and article publishing on the portals and synergy with Facebook, this gives better results in building brand, awareness and leads. In short, this synergy is an example that AI in agro marketing works best where technology is combined with proprietary data and industry knowledge.<\/span><\/p>\n Artificial intelligence is a game changer, but in agricultural marketing - an industry based on relationships and specific knowledge - technology alone is not enough. Algorithms are great at processing data, but it's understanding the farmer that determines success. That's why we've adopted a hybrid model in our work, where AI supports rather than replaces expert knowledge and intuition. What does this look like in practice?<\/span><\/p>\n From our experience:<\/span><\/p>\nRules of the game and roles in the era of artificial intelligence<\/b><\/h2>\n
What AI in agricultural markting is and what it is not<\/b><\/h2>\n
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Contexts for using AI in agricultural marketing<\/b><\/h2>\n
1 AI or just algorithms?<\/b><\/h3>\n
2. digital giants - Google and Meta<\/b><\/h3>\n
3. publishers and industry portals<\/b><\/h3>\n
4. AI in agricultural markting as a content creator<\/b><\/h3>\n
5. real AI in agricultural marketing - why is it unrealistic?<\/b><\/h3>\n
AI in agro marketing as a competitive advantage<\/b><\/h2>\n
AI practice in agricultural marketing<\/b><\/h2>\n
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Summary and vision<\/b><\/h2>\n