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[Audio] Welcome to Module 2, customers, value and market validation.

[Audio] Welcome to Module 2. In Module 1 you scored your research outcome on technical and commercial readiness. If you did the exercise honestly, there is a good chance that your two lowest scores include customer evidence or value proposition. That is very common, and it is the right place to start. Here is why. Researchers are trained to manage technical risk: will the method work, will the sensor be accurate, will the model generalise? Those risks are real. But when a promising agricultural innovation fails to reach the market, the cause is more often market risk. Nobody wanted it badly enough. It did not fit how the farm actually works. The person who would use it was not the person who would pay for it. Or it solved a problem that was real but not painful enough to justify the effort of changing. The entrepreneur and educator Steve Blank, who has written extensively on how new ventures learn about customers, gave a famous piece of advice that fits our situation well: get out of the building. His point is that the facts about your customers are not in your laboratory or your office. They are outside, on the farm, in the cooperative, in the advisory office. Blank and Dorf set this out in their 2012 book The Startup Owner's Manual, and Blank summarised the approach for a wider audience in the Harvard Business Review in 2013. In this module, we will do that in a structured way. We will map who your customers really are. We will learn how to run discovery interviews that produce honest answers. We will translate what we learn into a clear value proposition, put numbers on that value, and choose the first market segment where we can win. Let us begin..

[Audio] The first question sounds simple: who is your customer? In agriculture, it rarely has a single answer, so let us break it into four roles. The user is the person who works with your solution day to day. On a farm, that may be the grower, a farm manager, or a seasonal employee who operates equipment. The buyer, or payer, is the person or organisation that holds the budget and makes the purchase. Often this is the grower, but it can be a cooperative that buys a tool for all of its members, a processor that wants data from its suppliers, or an adviser who builds your tool into a paid service. The influencer is someone who shapes the decision without making it. In agriculture, influencers are powerful: agronomic advisers, neighbouring farmers, cooperative technicians, input suppliers and machinery dealers. If they do not trust your solution, many farmers will never try it. And the gatekeeper is someone who can block adoption. This might be a machinery manufacturer whose system does not connect with yours, a food company whose certification rules do not recognise your data, or a regulator whose requirements you must meet. Let me put this into a typical map of actors. Growers and farm managers. Cooperatives and producer organisations. Agronomic advisers and consultants. Input suppliers and distributors. Machinery dealers and manufacturers. Food processors and retailers, who increasingly want data on how food was produced. Public bodies, which can be both regulators and customers. And finance and insurance companies, which may value risk and performance data. Think about your own outcome. A disease risk model, for instance, could be used by a grower, paid for by a cooperative, recommended by an adviser, and blocked by a machinery platform that does not accept its data. If you only talk to growers, you have one quarter of the picture. So here is the task. For your outcome, write down the actors for each of the four roles. You will use this list in the exercise that follows shortly, and it will tell you who to interview..

[Audio] Now let us look at how to talk to customers. The method is called customer discovery, and its purpose is learning. It is not selling. Many researchers, when they first speak to potential users, make the same understandable mistake: they enthusiastically explain their technology, and the listener politely says, "That sounds interesting." You leave feeling encouraged, and you have learned nothing. The writer Rob Fitzpatrick, in his book The Mom Test, published in 2013, offers three simple rules that I recommend you adopt. The title refers to the idea that even your mother would lie to you about your business idea, just to be kind, unless you ask the right questions. His rules are these. Rule one: talk about their life instead of your idea. Ask about their work, their problems, and how they handle them today. Rule two: ask about specific events in the past, instead of generalities and opinions about the future. "Would you use a tool that does this?" invites a polite yes that costs the person nothing. "Tell me about the last time you had to decide when to spray" invites a real story, with real details. Rule three: talk less, and listen more. Your job is to draw out the story, not to fill the silence. What do you want to learn? Four things. What exactly is the problem, in their words? What do they do about it now, and what does that cost in time, money and risk? Who is involved in the decision, and how is it made? And what budget exists, if any? How many interviews are enough? There is no scientific threshold, but a common rule of thumb in the start-up community is that fifteen to twenty interviews within one segment are enough for clear patterns to appear. Treat it as a guide, not a rule. Choose a mix. Include enthusiastic early adopters, but also sceptics and people who have tried similar tools and stopped using them. Their reasons for stopping are some of the most valuable information you will get. Where do you find people? Through cooperatives, farmer organisations, advisers, field days, your own project's stakeholder networks, and referrals from every interview you do. Always ask at the end: "Who else should I talk to?" Finally, a word on responsibility. Tell people why you are asking. Ask for their consent if you record or keep notes with identifiable information, and handle that information in line with data protection rules. Trust is the most important asset in agricultural communities, and you want to earn it from the first conversation..

[Audio] Let us make this practical, with examples of questions that work and questions that do not. Questions that work all invite a story. "Tell me about the last time you had to decide when to irrigate. What happened?" "What did you do?" "How long did it take?" "What did it cost you, in time or money?" "What have you tried to improve it?" "Why did that not work?" "Who else was involved in the decision?" Notice that none of these mentions your solution. They explore the problem. Questions to avoid are the ones that invite flattery or speculation. "Do you think this is a good idea?" "Would you use an app that does this?" "Would you pay fifty euros for it?" People answer these questions politely and optimistically, and their answers are poor predictors of what they will actually do. Now, how do you read the answers? Learn to separate weak signals from strong ones. Weak signals include compliments, such as "that's really interesting", and vague promises, such as "send me some information" or "I would definitely try it someday." They feel good, and they should not change your plans. Strong signals include a specific, detailed story about a recent problem. They include workarounds the person has built themselves, such as a spreadsheet, a notebook, or a message group, because people do not build workarounds for problems they do not care about. They include money or time already spent trying to solve the problem. And they include requests for access, such as "When can I try it?", or offers to introduce you to others. So end every interview by asking for a next step. It might be a second visit, access to a field for a trial, an introduction to a colleague, or a letter of support. The size of the commitment tells you how serious the interest is: time, reputation, or money. A final practical point for agriculture: plan around the season. A grower in the middle of harvest will not give you an hour. Visit the farm if you can, and observe how the work is done. You will often notice things that the person never thinks to mention..

[Audio] Time for our second working exercise. Please pause the video when I finish. Step one: choose one segment to learn about first. For example, greenhouse tomato growers in one region, or cooperatives that supply a particular retailer. One segment, not all of agriculture. Step two: write down ten to fifteen people or roles that you could realistically reach within the next month, through your project partners, your institution, cooperatives, advisers, or personal contacts. Use the actor map from slide fourteen, so that you include users, buyers and influencers. Step three: write five questions about past events. Follow the pattern we just practised: "Tell me about the last time…". Check each question and remove any that mention your solution or invite an opinion about the future. Step four: write a learning goal in one sentence, beginning with "I want to find out…". For example, "I want to find out how growers decide when to apply treatments, and what that decision costs them." Step five: decide in advance what would make you continue, change direction, or stop. For example, "If fewer than five of fifteen people describe this as a significant problem, I will rethink the segment." Deciding this in advance protects you from seeing only what you hope to see. Take around ten minutes. Pause the video now..

[Audio] Now we turn what you learn from interviews into a value proposition. A useful tool for this is the Value Proposition Canvas, described by Osterwalder, Pigneur, Bernarda and Smith in their 2014 book, Value Proposition Design. The canvas has two sides. On the right is the customer profile, with three elements. Jobs are what the customer is trying to get done: functional jobs, such as protecting a crop; social jobs, such as being seen as a responsible producer; and emotional jobs, such as feeling confident about a decision. Pains are the things that frustrate, cost or worry them: wasted inputs, missed timing, paperwork, risk of loss. Gains are the outcomes they would value: lower costs, higher quality, time saved, proof for a buyer. On the left is the value map, with three matching elements. Products and services are what you offer. Pain relievers explain how your offer reduces specific pains. Gain creators explain how it produces specific gains. Fit happens when your pain relievers and gain creators match the pains and gains the customer rates as most important. Not all of them. The important ones. Let me give a generic illustration. Imagine a grower whose job is to protect a crop from a fungal disease while spending as little as possible on treatments. Pains might include spraying when it was not needed, missing the right window, and the paperwork required to document treatments. Gains might include lower costs, fewer residues, and records that satisfy a retailer. A risk-forecasting service might relieve the first two pains and help with the third, so the value proposition is built around those. A simple template helps you write it as one sentence: "For [segment] who [job and pain], our [offer] provides [main benefit], unlike [current alternative]." The current alternative is important, and it often includes doing nothing. When you write yours, resist the urge to list every benefit. Choose the top three pains from your interviews, and make sure your sentence speaks to them. A clear message to one group beats a general message to everyone..

[Audio] A value proposition becomes far more convincing when it contains numbers. Customers do not buy features; they buy outcomes, and they compare those outcomes with the cost and effort of getting them. So express your value in the customer's own terms. For a grower, that may be euros per hectare, hours of work saved, or risk of loss reduced. For a cooperative, it may be the cost of coordination, or the premium it can achieve with a retailer. For a processor, it may be fewer rejected batches. Then compare it with the total cost of adoption. This is more than the price you charge. It includes the time needed to learn the tool, any equipment or connectivity that must be installed, and the effort of changing routines. Net value is the benefit minus that total cost. Let me show you a worked example. I must stress that these figures are invented, purely to demonstrate the calculation. They are not real data. Imagine a grower with twenty hectares. Suppose a decision-support tool allows two fewer treatments per season. Suppose each treatment costs thirty euros per hectare once you include product, labour and machinery. The saving is twenty hectares times two treatments times thirty euros, which is one thousand two hundred euros. If the service costs fifteen euros per hectare, that is three hundred euros. The net value is around nine hundred euros per season. In reality, you would replace each of those numbers with data from your interviews and trials. Ask customers what their costs actually are. Compare your solution with a baseline, ideally with a control, such as a similar field managed in the usual way, so that you can show what changed because of your tool. Value is not always money. It can be risk, compliance, time, quality, or environmental benefit. Where possible, translate these into something concrete. Many growers will expect a solution to pay back quickly, perhaps within one or two seasons, but you should test this in your own interviews rather than assume it. One final caution. Be careful and honest with claims. An overstated claim may win one sale, but it damages trust across a community that talks. Say what you can show, in the conditions where you showed it..

[Audio] You cannot serve everyone at once, so now we choose where to start. The idea is called a beachhead: a focused first market that you can win convincingly, from which you expand. There are many ways to segment agricultural markets: by crop, by farm size, by region, by farming system such as protected cultivation or open field, by level of digital maturity, by the type of business, or by how people buy. Your interviews will tell you which differences matter. What makes a good beachhead? Five tests. The pain is acute, so people actively want a solution. They have the ability to pay. You can reach them through a small number of channels, such as one cooperative or one advisory network. They form a connected community, so word of mouth works. And your current product can serve them well, without major redevelopment. It also helps to understand how adoption works. Everett Rogers, in Diffusion of Innovations, whose fifth edition appeared in 2003, describes adopters in categories: innovators, early adopters, early majority, late majority and laggards. He also identifies five attributes of an innovation that influence how fast it is adopted. Relative advantage: is it clearly better than what exists? Compatibility: does it fit current practice and values? Complexity: is it easy to understand and use? Trialability: can people try it on a small scale? And observability: can others see the results? You can use these as a checklist for your own offer. Geoffrey Moore, in Crossing the Chasm, argues that there is a gap between early adopters, who tolerate rough products because they love novelty, and the early majority, who want complete, proven solutions with references. His recommendation is to focus on one niche, win it thoroughly, and use it as the reference for the next. In agriculture, this might mean winning one crop in one region, with a trusted cooperative, before you expand. Please choose your beachhead now, at least provisionally. You can change it after your interviews, but having a clear hypothesis makes your learning faster..

[Audio] Two final tools in this module. The first helps you judge how strong your evidence of demand really is. The second gives you a first, rough idea of market size. Think of an evidence ladder. At the bottom is expressed interest, such as "sounds good." It is the weakest. One step up is time commitment: the person agrees to a second meeting or lets you visit the farm. Higher still, a pilot sign-up: they agree to try the solution. Then a letter of intent, which states in writing that they intend to buy or participate if certain conditions are met. Higher again, a paid pilot or a pre-order, where money changes hands. And at the top, repeat purchase or renewal, which shows the value was real. For each of your target customers, ask yourself which rung they have reached. Most research outcomes at this point sit on the bottom two rungs, and the goal of the next months is to climb. Now, market size. Investors and funders will ask about it, and so should you, because it tells you whether the business can be large enough to justify your effort. The reliable method is bottom-up. Count how many customers fall in your beachhead segment. Multiply by the annual revenue you could realistically earn from each. Then apply a realistic share, based on your capacity and channels. For the number of farms or businesses, use official statistics, such as those from national statistical offices or Eurostat, rather than estimates from marketing reports whose methods you cannot check. Avoid the top-down argument that sounds persuasive and means nothing: "The global market is worth many billions, so if we capture just one percent…" Nobody captures a percent of a global market. They win specific customers, one by one. A small, well-defined market that you can actually reach is a stronger starting point than a vast market you cannot. As you work through this, write down your assumptions. Later, in Module 4, we will check them against pricing and costs, and in Module 5 against partners and funding..

[Audio] Let us consolidate what we have covered in Module 2. We started from the observation that market risk, the risk that nobody wants what you have built, is often the biggest risk, and that the way to reduce it is to get out of the building and talk to customers. We mapped the actors around your outcome: the user, the buyer, the influencers, and the gatekeepers, and we saw that in agriculture they are rarely the same person. We learned how to run discovery interviews following three rules: talk about their life, ask about specific past events, and listen. We distinguished weak signals, such as compliments, from strong signals, such as workarounds, time and money already spent, and requests for access. Then we turned what we learn into a value proposition, using jobs, pains and gains, we put numbers on the value in the customer's own terms, and we saw why claims must be defensible. We chose a first beachhead segment, looked at the factors that influence adoption, and introduced an evidence ladder and a bottom-up approach to market size. If you completed the two exercises, you should now have a customer map, an interview plan, a draft value proposition sentence, and a provisional beachhead. These are the foundations of your commercialisation plan. Please keep them with your scorecard from Module 1. One more thing before we move on. As you start talking to customers, you will be tempted to explain your technology in detail. Before you do, you need to know what you own and what you are free to share. Which brings us to Module 3: protecting and managing intellectual property and data rights. We will look at who owns research results, how patents, copyright and trade secrets differ, why publishing and disclosure timing matter, and how to handle the farm data that digital agriculture depends on. Let us continue..

References. Blank, S. (2013). Why the lean start-up changes everything. Harvard Business Review, 91(5), 63–72. Blank, S., & Dorf, B. (2012). The startup owner’s manual: The step-by-step guide for building a great company. K&S Ranch. Fitzpatrick, R. (2013). The Mom Test: How to talk to customers & learn if your business is a good idea when everyone is lying to you. CreateSpace. Moore, G. A. (2014). Crossing the chasm: Marketing and selling disruptive products to mainstream customers (3rd ed.). HarperBusiness. (Original work published 1991.) Osterwalder, A., Pigneur, Y., Bernarda, G., & Smith, A. (2014). Value proposition design: How to create products and services customers want. Wiley. Rogers, E. M. (2003). Diffusion of innovations (5th ed.). Free Press..

[Audio] Thank you!. thank you!. TALLHEDA has received funding from the European Union's Horizon Europe research and innovation programme under Grant Agreement No. 101136578. Funded by the European Union. Views and opinions expressed are however those of the author(s) only and do not necessarily reflect those of the European Union or the European Research Executive Agency (REA). Neither the European Union nor the granting authority can be held responsible for them..