Why Pricing Matters
Pricing levers. Valley of death. Customer acquisition playbook.
Welcome to Infinite Curiosity. I recently came across an interesting question posed to me by a friend — Why should I care about pricing in the early days of my startup? I decided to tackle that question in this post.
In this post, we’ll talk about:
Pricing zip codes and the corresponding playbooks
Key reasons why pricing matters
Valley of death
Measuring the ROI of a product
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I wanted to see how people argued about prices back in 10th century Constantinople, so I asked DALL-E to generate it for me. The interesting thing to note here is the dude sitting down watching these two people. Looks like pricing has always been a fascinating topic! Let’s dive in.
Pricing is a key decision in the early stage of company building. This post is less about the exact dollar amount, but more about the mechanics of pricing. Let's consider two products here:
Product A costs $100 per year
Product B costs $200 per year
Even though one product costs twice as much as the other one, you will run the exact same customer acquisition playbook for both of them. They are in the same zip code. Let's consider two more products:
Product C costs $40,000 per year
Product D costs $90,000 per year
Now if you look at the dollar difference, product C is closer to product B as compared to D. Let’s say you make buckets such as:
Products that cost less than $50,000 per year
Products that cost more than $50,000 per year
You will end up bucketing B and C in the same bucket. But they're VERY different when it comes to the customer acquisition plan. The playbook is very different for B vs C, but you will run the exact same customer acquisition playbook for C and D.
Your pricing will continue to evolve over the life of your company, so you don't have to worry about setting anything in stone. You just need to understand your zip code and build a customer acquisition plan accordingly.
Here are four key reasons why a pricing playbook matters:
It helps you understand how your company makes money
You're running a business. And a business needs to make money. When customers come to you, they expect you to have information on how your product is priced. Consulting companies gather all the requirements first and then provide a quote, but product companies can't (and shouldn't) do that.
You need to have a clear idea on what customers are paying you for. Machine learning products are compute-intensive, so you need to keep that in mind as well.
Are they paying you per user? Is there a fee for data storage and compute? Is there a setup fee? How about professional services that they might need during the contract? Product companies should provide the pricing upfront and be clear on what the levers are.
It helps you understand how the product is consumed by customers
You need to know how your customers are using the product. You need to know what the unit of work is and charge accordingly. Here are a few examples:
If you are providing a data warehouse, it doesn't make much sense to charge based on the number of users. You need to charge based on how much data is being processed by a given customer.
If you're providing a platform that provides compute power to build models, it doesn't make sense to charge based on the number of users. You need to charge based on the amount of compute power used by the customer per month.
Similarly if you are providing a video conferencing product, it doesn't make sense to charge based on data. You need to charge based on how many people are using the product.
It helps you avoid the valley of death
You need to understand if you're selling to Enterprise or SMB. You will be tempted to do both. But in the early days, you need to pick one.
If your product costs $100,000 per year, then it's meant for Enterprise. If you try to sell that to SMBs, you won't get any traction. They don't have that much money.
Conversely if your product costs $100 per year, then it's a self-serve product meant for SMBs. If you try to sell that to Enterprise, you won't get any traction. They have many needs and they expect a full solution that meets all those needs. They won't stitch together 79 different tools that cost $100 each to build a solution to meet those needs. They will just go with one vendor who can meet all their needs in that area.
Here are two main buckets here:
SMB bucket: The price is low enough (usually less than $5,000 per year) such that your product can be self-serve. Customers can buy and use it without talking to you. You will need a large number of customers to hit any meaningful revenue milestone, but the cost of acquiring and supporting each customer is low.
Enterprise bucket: Let’s say the product is complicated and it requires you to do implementation work. You’ll need expensive salespeople to close the deals. And you need to make sure it works with your customer’s legacy systems. This is a lot of work, so you price is high enough such that you can account for all this (usually more than $40,000 per year).
The valley of death refers to a pricing window in the middle. The exact boundaries vary based on who you’re asking. But in essence, it’s when the price is not low enough to be self-serve for SMBs and not high enough to support a full Enterprise sales motion.
For example, a product that costs $14,000 per year will be in this category. You won’t be able to sell it to SMB or Enterprise. A good pricing strategy helps you avoid this valley of death.
It helps you understand what business value is being created by your product
Why does business value matter? Because your pricing is a reflection of the business value being created by your product for your customers. This is especially relevant in enterprise SaaS.
If your machine learning product is helping your customer reduce their energy consumption, you need to find a way to measure how much of that was due to your product. If your machine learning product is helping your customers sell more clothes, you need to find a way to measure how much was due to your product.
You need to understand how to measure the ROI of your product. You need to agree upon the metrics they will use to measure the impact of your product. You measure the status quo before your product is deployed, which becomes your baseline. You then deploy your product and measure those metrics after 3 months. The difference in the value of those metrics should be measured and converted to an annualized dollar figure. That becomes the ROI of your product.
You should aim to deliver 4-5X ROI. It means that if you product costs $100k per year, then it should generate $400-500k in business value for the customer.
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