Kensu, Maxime on DE, Pricing is hard; ThDPTh #63
I’m Sven, and this is the Three Data Point Thursday. The email that helps you understand and shape the one thing that will power the future: data. I’m also writing a book about the data mesh part of that.
Another week of data thoughts:
Pricing is hard to get right in the data space. Pricing can serve as an alignment tool, or do the opposite.
Maxime published another impressive piece.
Kensu.io is worth a look!
Unsexiness & Alignment as a "Moat"
What: NotBoring just published a piece about TrueAccord. It is called “unsexiness as a moat” but I stumbled over something much more interesting, Alignment:
“also missed just how important the incentive alignment narrative would become in 2021 and 2022. TrueAccord’s business model is aligned with both creditors and consumers: Recover, for example, only makes money when consumers get out of debt. As one sign of that alignment, TrueAccord successfully lobbied for the passage of the CFPB’s Regulation F, which limits debt collectors’ ability to hound people on the phone, among other things”
My perspective: I love how TrueAccord is described to have aligned its incentives with its customer base. One thing I did explore a bit when writing about how data companies need to design mechanisms to align themselves with their open-source users.
TrueAccords’ product “Recover” only making money when consumers get out of debt is a great example of alignment. It’s a great example of how this subtle thing called “pricing” actually can make or break the business. Because the question of “what” to price is so essential in a digital world where the information product character of products is so dominant.
A lot of digital companies, especially in the data space, default to cost-based pricing meaning they choose to price for what produces the cost. That might sound intuitive at first, but really the question is not about where the cost is, but what consumers of a product are willing to pay: what kind of value consumers of a product get out of it. Alignment & pricing is hard, but companies do get it done. TrueAccord does it in spite of serving two almost opposing customer groups.
I also worked in a B2B marketing agency back in the day. There the founder of the company had a very similar fun idea: He wanted to buy stock of every company he took on as a client, as a measure to align with his consumers.
For some reason, the data space seems to have a hard time with this. …
I think every company needs to think a lot about alignment and the incentives & mechanisms it uses to achieve that.
A small example: GitLab is a solution for teams or complete companies. It is meant to make pushing things into production fast and easy. And luckily, GitLab chose to financially align with that.
Customers of GitLab benefit from a degree of standardization as well as from pushing code more frequently into the pipelines. And that’s exactly what customers are paying for (in a very big chunked pricing model).
GitLab’s Product staff thus is incentivized to provide lots and lots of features which make it even easier for developers to push code into production more frequently as well as adding features that make adoption across a whole company very easy.
A bit of a counterexample I think is what dbtlabs is currently experimenting with. Dbt currently prices for numbers of developers on Dbt cloud as well as a bunch of very enterprise features like SSO.
Thus the company dbtlabs incentivized itself for providing things that drive up the number of developers using Dbt inside a company.
The problem? I am not sure the typical dbt customer benefits from growing the number of dbt users inside his company. I am also not sure they benefit from having just one data transformation solution.
These are definitely not opposite directions, but it’s also not straight alignment.
What would be alignment? For instance, a pricing cap for workload runs. This would incentive the dbtlabs to help create models quickly and get them into production quickly. It also would incentivize them to devise features that make models run fast. Sounds much more like alignment to me.
Additionally, this sounds a lot like dbtLabs should aim for a combination of different dimensions inside their pricing model. GitLab for instance combines at least three dimensions into one linear pricing model.
(Disclaimer: I love what dbtLabs is doing, and I might be totally off, this is mostly me thinking out loud, and having the feeling that something is off here.)
So, how about you: Do you feel aligned with your customers? Are the tools you’re using aligned with you?
What: Maxime is thoughtful and definitely one of the leaders in this space. He’s writing about the 10 big trends currently reshaping data engineering.
My perspective: I love everything Maxime writes. This is again impressive. Enough said.
What: Kensu provides a data observability toolkit that basically adds logs to everything you’re already doing. It then builds smart observability on top of this including lineage and some debuggability features.
My perspective: I just played around with their sandbox and really liked the general approach, although I am still waiting for them to put more focus on the DODD perspective they invented. One key idea they have is to put all of the observability right where the value is created, at the intersection of the running application and new data. They call this “synchronous monitoring”.
If you have time, take a look at their thing.
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