Palantir Introduces Usage Based Pricing
One of the hardest challenges Palantir has had around selling it's product is that they never offered the ability to allow clients to pay as they use it.
Palantir sells a software with phenomenal margins, but they sell the whole software. This means that if clients want to buy the software, they need to buy the whole package.
This is obviously not the best for clients because they may not need the whole product, may not understand what to do if they got the whole product, don't know how to reorganize their existing IT departments around a whole new product, and quite frankly just don't have the budget for a whole product!
As a result, Palantir has begun to change how they offer their services.
Pay As You Go
Pay as you go pricing is one of the oldest forms of selling software. In fact, it's what has allowed for software behemoths like AWS to scale as quickly as they did.
Anyone could sign up for an AWS account, connect to their servers, and then pay as the usage of their product increased. For example, if you have a startup that uses AWS servers to handle users posting content on your platform, the more users you have, the more expensive the servers cost.
If you have days in which users post little content or don' engage as much with the platform, your AWS fees will be low for that day. On days of significant usage, the fees will be higher. For startups, this is incredible because they aren't locked into contracts with AWS to pay a set amount to even access to services - they use what is required and eventually pay more as their product gets bigger. If the product never takes off, neither do their server fees.
Palantir has openly admitted that it was a mistake to be adversarial with existing IT departments, and the best way to actually sell their software was to work with them and see how they can aid vs. replace everything that they already had built out.
As a result, in the Q1 2022 earnings presentation, the pay as you go model was introduced.
Pay as you go pricing is consistent with Palantir's latest "Data Mesh" product that they introduced in Japan.
From their website,
"Palantir Data Mesh can upgrade historical investments in data warehouses, data lakes, and other legacy infrastructure to unlock additional value. By meeting the enterprise wherever they may be along the digital modernization journey, Palantir Data Mesh seamlessly integrates the enterprise's legacy systems through its interoperable architecture and automated deployment.
Importantly, there is no charge for getting an enterprise's data into the Mesh or for getting it out. Pricing is based on flat-rate consumption — with no minimums and no extra fees."
This also allows Palantir to now charge customers based on what they use. From their website:
Palantir Data Mesh pricing is easy to understand, affordable, and completely transparent to users. There is no charge for putting data into the Mesh, and no charge for taking it out.
Pay only for what you use and value you create via:
Compute. Compute is the serverless fuel that drives your data connection, integration, analytical, machine learning, and operational workflows. Compute is measured as parallelized computational seconds performed in the platform by transformations, streaming jobs, live queries & models, or simulations.
Ontology volume. The ontology is the semantic backbone for your organization's end workflows. It translates data into operational outcomes, providing business-oriented data presentation layers, operational applications, scenario analysis, and closed-loop decision capture. Ontology volume, measured by GB-month, scales with the amount of data.
Time will tell if this model works, but historically, paying as you go as been a sound way to attract clients early and allow them to scale their spend as they scale their usage of the product.
If Palantir can fully modularize their offerings along with make it a pay as you go service, then they can unlock a whole world of customers willing to give the product a chance before fully committing.
Because, commitment is hard right? At least that's what I told my ex-girlfriend.