Pricing for SaaS
How to fix a pricing misconception problem, what causes sales deals to lose on price, and how do you put together an effective pricing model structure.
Today, B2B SaaS buyers are more savvy and do 70% of their research prior to hitting your website. There are also agencies that come in to purchase on behalf of their clients, like Vendr (more on them further down) who already have a pretty good idea of what your software should cost their client.
In my experience
In a previous company I worked for we had a couple misconceptions in the market. One of them being we were perceived as being too expensive. The perception wasn’t wrong. There was no price book prior to my arrival and sales was making up pricing based on what they thought the prospect could pay. This is a common play in B2B SaaS as companies look for product market fit and determine how much someone is willing to pay for the value they deliver.
When you have a misconception of being too expensive, you miss out on smaller deals you would have otherwise closed. Many B2B buyers today also do their research way before they come to your website. They tap into the dark funnel (their peers, communities) or hire agencies like Vendr, the SaaS killer, to negotiate on their behalf.
How did I solve the misconception? I developed a price book in Salesforce. Trained the sales team on how to use and enter it into opportunities. Most importantly, I added it to the website in a nice easy-to-read table outlining what you get for what tier. We targeted SMB, MidMarket (MM), and Enterprise. We listed the price for SMB and the price for MM, but for Enterprise we said “starting at $40,000” and had a button for “Contact Sales” which allowed Enterprise companies to feel like we weren’t going to price gouge them. We then A/B tested the word ‘Pricing’ in the header and footer and surprisingly, for our website, it faired better when placed in the footer. (I am sure this is different for every company, so definitely A/B test this).
How to handle Vendr in negotiations
I only came across Vendr a couple of times early on before we had listed pricing on our website. The problem with Vendr, and why most SaaS companies label them the SaaS Killer, is they come in and negotiate on behalf of their client, usually based on information they [Vendr] obtained from another client using your service who signed a services agreement with you or who signed an NDA. If it’s from an NDA, it’s not legal for them to use the information. When negotiating with Vendr, just ask them where they obtained their information. Or put your pricing on your website, it’s hard to argue with it in print.
Common misconceptions about price being a deal breaker in sales deals
According to Klue Labs recent study of 3400 buyer interviews, that price is often not a singular deal breaker. It comes in second behind issues during the sales process (2nd) and product issues (1st).
However, when buyers cite price as a reason for not closing a deal, it often means:
Value and ROI concerns (22%)
Pricing structure and model issues (41%)
Actual price being too high (37%)
And interestingly enough, when they cite budget constraints, it has nothing to do with your pricing. (Klue Labs report)
Basics of creating a pricing model
While I wouldn’t label myself a pricing expert, I’ve implemented pricing a few times at a few different companies. The biggest mistake I have seen SaaS startups make when coming up with pricing is not truly understanding their costs to deliver their product. If you don’t understand your costs, you can’t possibly come up with a decent pricing model.
Your value’s lowest denominator. Understand your lowest denominator of your core value metric. What are you selling? Is it a base platform with feature flagging? Is it the entire platform? Is it on-premises? Is it based on a single user or action?
Your costs. Understand your costs to deliver the value metric.
Your competition. Understand what the competition is charging and how they are charging.
Unit of value
Jerry Chen of Greylock Partners developed the Unit of Value framework, which he defines as “the smallest measurable unit at which your product or service provides value.” This is probably the single most important thing when choosing a pricing model, as it will help you scale.
When defining your smallest unit of value, you need to take into consideration:
Will it be user-based pricing, consumption (usage-based) pricing, subscription/licensing, outcome/value based, freemium? User-based pricing discourages experimentation and viral adoption. Consumption-based pricing discourages experimentation. Outcome/value based is difficult to implement and harder to measure for both the buyer and seller.
How much does it cost to deliver one unit? When I was at SparkPost we knew how much it cost us to deliver 1 email. Whether you sell conversions, emails, revenue, etc, figure out what one unit costs. If it’s too complicated, you don’t have a proper handle on your costs and your pricing will be too high or too low as a result.
How do the market and competitors talk about your offering. For example, if the market is talking about it in “users” or “website visitors” or “emails sent” you should do the same. It needs to make sense, be familiar, and they need to be able to easily find/determine what you’re looking for. Can they count how many users? Do they know how many emails they send? Do they know their monthly website visitors?
AI Pricing
How does AI figure into this (h/t to Kyle Poyar of Growth Unhinged) for pulling this list together. Interestingly enough, companies are also pricing access to AI capabilities by unit of value.
Pricing is not linear
I’ve worked for a couple of companies who have struggled with pricing as they scale. They had a pricing model that was linear, but pricing isn’t linear. In fact, the higher the volume you are selling, the larger the discount someone expects.
At one startup I worked, Amazon came in as a prospect. When sales plopped their request into the pricing model the price was tens of millions of dollars. Amazon wasn’t going to pay that and it was absurd anyway. I put together a model showing our lowest denominator core metric scale with volume discounts.
Pricing Logic
Start with full price for smaller deals.
Introduce volume discounts as your core value metric increases, reduce the price to incentivize larger purchases
Cap the total price for very large companies to keep the offer attractive
Other considerations are competitor pricing, feature tiers, and value based adjustments. Remember to factor in economies of scale that reduce your per-value metric costs for larger deployments.
Why this works
This scaled model works because:
It maintains profitability for smaller clients
It offers incentives for larger companies to choose your product
It caps the price at a reasonable level for enterprise clients
Bottom line
Pricing is complicated but it can be remedied if you have the right data and tools. Price is often not the real reason you lose deals.