Our Hate List
In the last financial crisis (2007/2008) AWS existed only for two years and the likes of Snowflake, Databricks and Fivetran had not even been founded yet. The cloud has come a long way since then, but... a lot remains to be desired. Our Hate List consists of four - somewhat related - things we believe are wrong with The Data Cloud (note: by The Data Cloud we mean the collective of leading incumbents in this industry, i.e. the establishment).
#1 The Data Cloud prioritizes investor interest over customer interest.
#2 The Data Cloud embraces "price doesn't matter"-thinking.
#3 The Data Cloud relies heavily on "push-sales".
#4 The Data Cloud believes that retention is the same as true love. It is not.
Observation #1: The Data Cloud prioritizes investor interest over customer interest.
It is no secret that venture capital is in love with enterprise software, including the Data Cloud. This might be driven by 70%+ gross margins, recurring revenue and long retention periods. As a result, startups in the data infrastructure space are encouraged to create their business models around these financial metrics. That is... if they wish to obtain funding.
Driven by a wave of VC funding, this has resulted in hundreds of startups in the data space that all follow the same playbook. Many of these startups have become unicorns (check out the Bessemer Venture Partners Cloud Top 100 to get an idea about the players in this space). Each of these startups is focused on one piece of the customer's data infrastructure. This results in customers having to patch together multi-vendor solutions, each with a steep price tag. We believe this has inflated the overall price level in the data space. Great for investors, not so much for customers.
iomete's positioning | Put customers first.
We align our interests with those of the customer and avoid becoming solely dependent on VC funding to fulfill our growth potential. We're okay if that results - initially - in lower growth and a lower gross margin. Customers want to become data-driven in an easy and cost-effective way. We should facilitate that.
Observation #2: The Data Cloud embraces "price doesn't matter"-thinking
We went through Y Combinator and were hammered with the message that product is everything. We agree. We do believe that without a great product, a low price does not matter. But: We also believe that having a great product at an exorbitant price point makes one vulnerable to disruption through a new entrant that delivers on product and price point.
The Data Cloud today heavily relies on a carefully crafted "expertise" message fueled by billion-dollar marketing budgets (e.g. Gartner quadrants, summits in Las Vegas, MIT-sponsored research papers etc) to justify exorbitant pricing.
iomete's positioning | We believe that price matters also.
We realized that we had to offer radical value in order to help drive the democratization of data. If data (infrastructure) is cost-prohibitive, it will slow down innovation and progress.
In stead of the typical goal-seek of "what does my price need to be in order to obtain 70% gross margin so that I can convince a VC to give me funding?", we asked the question "what is the lowest price we can offer customers while staying in business without becoming totally dependent on investors for the funding of growth?".
Make compute prices equal to AWS on-demand prices. No mark-up. AWS users basically get our platform for free.
Observation #3: The Data Cloud relies heavily on "push-sales".
Snowflake - the leading Data Cloud - is still not profitable ten years after inception despite a 70% gross margin (their management recently announced at their annual summit it expects gross margin to increase to 80% -> Who will pay for that?)
That 70%-plus gross margin comes with a burden; one needs a large marketing & sales apparatus and - in our opinion - unpleasantries like cold emailing campaigns, cold calling sales representatives and data summits in Las Vegas to convince customers to use one's product.
We believe: the better the deal for the customer, the less push-selling it takes. If it takes you billions of funding to get to $1Bn in revenue and are still unprofitable, your product might not be as great as you think.
iomete's positioning | Grow through word-of-mouth and customer referrals.
80% of our team consists of engineers and we are passionate about building a great product that will be used intensively by many customers. We hate (pushy) selling, so we'll avoid it all costs. No cold sales emails. If we could have it our way people would come to us. Engineers are a critical bunch, but when you've earned their love, they'll talk about you.
Observation #4: The Data Cloud believes that retention is the same as true love. It is not.
Customer retention is a good thing, but it depends on how one achieves it. If after getting married, the husband locks up the spouse so that she cannot walk away, that might not be a great thing. If the husband then proudly explains to his friends that they have been married for 10 years, it might be factually true, but would that still be the case if the husband would have kept the door open?
iomete's positioning | Make sure that customers can walk away if they want to.
Our idea of a healthy relationship is that customers stay with us because we are the best alternative. Therefore we designed our proposition in such a way that the customer can always leave with no strings attached:
- Our data format is Apache Parquet, an open source format so customers can always access their data.
- Our platform is built on Apache Iceberg and Apache Spark, two leading open source projects.
- The customer's data is stored under their own AWS account. The iomete platform accesses the data in the customer account to run queries, but the customer owns her data, 100%, at all times.
The Data Cloud needs a Challenge(r)...
In this post we explained why we believe "The Data Cloud" - a reference to the establishment in our industry - is greedy by sharing our hate list: four observations that reflect the current state of the data industry around customer and value proposition...
We engineered our value proposition by doing the opposite. This results in a "challenger"-positioning for iomete. It looks like this:
#1 The Data Cloud: investor-focus -> iomete: put customers first.
#2 The Data Cloud: pricing is goal-seek exercise, price must lead to 70%-plus gross margin -> iomete: we believe that price matters. Our price is equal to the AWS on-demand price. No mark-up. Basically free for AWS users.
#3 The Data Cloud: big sales & marketing apparatus, push-sales -> iomete: grow through word-of-mouth and customer referrals.
#4 The Data Cloud: retain customers through lock-ins -> iomete: retain customers by being the best alternative.
Our goal is to create a high volume, lower margin business that is fueled by word-of-mouth and referrals from our customers. As volumes increase we can continue to drive prices downward, creating a flywheel that benefits both our customers and our team.