Published in: Pricing

The history of the ‘Pottery Course’ and the impact on your pricing

Here’s an interesting story about a “Pottery class” which shows that there are different approaches to work, depending on the goals you set yourself.

The Pottery Lesson story

You might be familiar with the story known as “The Pottery Lesson”. In case you don’t know yet here is how it goes: “Once, there was a pottery teacher who divided his students into two groups. To one group, he assigned the task of creating a single beautiful pot, while to the other group, he assigned the task of making as many pots as they could. The teacher was surprised when discovered that the group focusing on quantity produces the most beautiful pot. They attribute their success to learning from mistakes, highlighting the value of experimentation and resilience over perfectionism.”

Guided vs Experimental approach  

This story talks of two opposing approaches when performing new tasks. You need to perform a task, so you need first to learn how to do it. On one extreme you have learning by guidelines coming from a maestro. This is the way of learning that is experienced in the university, where we learn from our professors. It would be the approach taken by the first group in the story, take all the pottery teacher lessons and try to apply them to create a single beautiful pot. On the other hand, it’s the try-and-error approach, you can try and try yourself, learn from mistakes, and let your accumulated experience guide you on performing the task. This is the approach taken by the second group in the story, who experimented, adapted, and improved with each new attempt, which finally made them create the most beautiful pot.

PricingHUB pricing approaches

Imagine now, pricing is the task. Imagine, also, you rule a company, whose main focus is providing a given product or a service to the end consumer. Your main focus is not doing pricing, not even of your own products. So, pricing is not where you have to master, but anyways, you don’t have a choice, you need to price your product,  you have to do it. So, then,  you might have learnt how to do it well, or you might have let yourself go and, accepting that you don’t know what to do, you copy what others do, and decide to follow other’s pricing, your competitors. Even when you don’t have guarantees that competitors know how to do pricing.

PricingHUB can help you in your pricing task using any of the two approaches we have seen above.

Case 1:

Let’s take for granted that you are an expert on your business vertical, and let’s assume you have managed to gain a lot of expertise, as well, on how to price your products. In that case you are the professor. You know the “how”. You just need some students to perform the task as you dictate. In other words, you set the guidelines, you set the rules. For that case, PricingHUB can offer you a pricing engine that is able to translate your experience into rules to generate everyday, automatically, a price recommendation. In this case, PricingHUB is all your student’s hands. Obeying your guidelines.

Case 2:

You are an expert on your business vertical but still you are not a maestro pricing your products. If you, with your full knowledge of your own business, can not tell how to price your products, PricingHUB, that does not have any experience in your vertical market, won’t be a maestro either. In this case, it is better to not take the professor’s approach, but the learning from experimentation approach. PricingHUB can offer an engine able to learn from experimentation. This engine tests different prices to acquire knowledge about the context and to understand the relationships between the trading KPIs and the prices. It does so faster and more accurately than any human can thanks to machine learning algorithms. For the engine, there is no right or optimal price. There are prices that drive more of a specific KPI and prices that drive more of another different KPI. With the Machine Learning capabilities it is able to identify which price suits best to your company needs.   

Note that, using this approach you don’t need to become an expert on pricing anymore. You just need to trade. More specifically, you need to express your company needs as a KPI growth.

So, if you are an expert, you dominate the trading dynamics of your business, then you can take the Rules Engine, and make the engine follow your guidance. If you are not that expert then you can let the Experimentation Engine learn and optimize your trading for you. But remember the pottery story, the most beautiful pot came from the group of students using learning by experimentation. You might not be as expert as you thought, your knowledge might get obsolete, or simply the continuous improvement of the experimentation learning can overperform the professor’s guidelines.

Obviously, the 2 approaches to succeed on a task, following expertise and continuous experimentation, are opposing but not exclusive. Both can benefit from each other and the sweet spot lies in the middle. This is why at PricingHUB we continue working, to find the halfway point where expertise and experimentation meet. We’ll keep you posted on our progress! Stay tuned!