Algolia Pricing
July 3, 2020
Years ago I listened to a wizard from Verity explain that a query should cost the user per cell. Now that struck me as a really stupid idea. Data sets were getting larger. The larger the data set, even extremely well crafted narrow queries would “touch” more cells. In a world of real time queries and stream processing, the result of the per cell model would be more than just interesting, it would be a deal breaker.
Pricing digital anything has been difficult. In the good old days of the late 1970s and early 1980s, one paid in many different ways — within the same system. The best example of this was the AT&T/British Telecom approach to online data.
Here’s what was involved. I am 77 and working from memory:
- Installation, set up, or preparation fee. This was dependent of factors such as location, distance from a node, etc.
- Base rate; that is, what one paid simply to be connected. This could be an upfront fee or calculated on some measurement which was intentionally almost impossible to audit or verify.
- Service required. Today this would be called bandwidth or connect time. The definition was slippery, but it was a way for the telcos of that era to add a fee.
If a connection went to a data center housing data, then other fees would kick in; for example:
- Hourly fee billed fractionally for the connect time to the database
- Per item fee when extracting data from the database
- A “print” or “type” fee which applied to the format of the data extracted
- A “report” fee because reports required cost recovery for the pre-coded template, query time, formatting, and outputting.
There were other fees, but the most fascinating one was the “threshold fee.” The idea is that paid for 60 minutes of connect time. When the 61st minute was required, the threshold was crossed, and the billing could go up, often by factors of 2X or more. No warning, of course. And the mechanism for calculating threshold fees were not disclosed to the normal customer. (After I became a contractor to Bell Communications Research, I learned that the threshold fees were determined based on “outside” or exogenous factors. In Bell Head speak this seemed to mean, “This is where we make even more money.”
To sum up, online pricing was a remarkable swamp. Little wonder that outsiders would be baffled at the online invoices generated by the online providers. Exciting, yes. Happy customers, nah. No one at the AT&T/British Telecom type outfits cared about non Bell Heads. No Young Pioneer T shirt? Ho, ho, ho. Pay your bill or we kill your account. Ho ho ho.
Algolia announced a new pricing plan. You can read about it here. The idea is to reduce confusion and be more “customer friendly.” What’s interesting to me is the string of comments on the Hacker News site. You can read these comments at this link.
There’s some back and forth with Algolia participating.
Some of the comments underscore the type of “surprise” that certain types of pricing models spark; for example, from alooPotato:
We (Streak) are in the same boat. Looks like we’d be paying approx half a million dollars a month on their new pricing which would be ~100x more than we are paying now. Haven’t heard from our enterprise rep but starting to get nervous… Sounds like the new pricing is for their ecommerce customers given how much value they provide them, doesn’t seem to make sense anymore for SaaS use cases.
ysavir takes a balanced view; that is, some good, some bad:
Not the GP, but I figure their point is as follows: If I’m running an e-commerce website, I don’t mind pay-per-search since those searches may turn into sales, so the cost is justified. My income scales with search count, and the Algolia price is part of user acquisition costs. If I’m running a SaaS business, the search is a feature for customers who have already paid, so I don’t see any further returns from the search being used. The more a client uses search, the less I’m profiting from having them as a client. They could potentially even cost me money to service them!
The point is that any pricing model — whether the AT&T/British Telecom type pricing “simplification” or a made-up, wacko approach like the IBM J1, J2, J3, etc. approach — is not going to meet the requirements of every customer.
The modern approach to pricing is to obfuscate and generate opaque variable prices. You can see this model in action by navigating to Amazon and running a query for “mens golf shirt and then zipping over to AWS and check out the prices for Sagemaker models to drive Athena. Got the difference, gentle reader?
The nifty world of enterprise search has been a wonderland of pricing methods. I flipped through the pricing data files for the three editions of the Enterprise Search Report which I began writing in 2002. Here are some highlights:
- Base fee plus engineering services. Upgrades priced individually.
- Base fee plus fixed price over a period of time.
- Variable elements like the crazy “per cell” idea from the guy who is now the head of Google Search (Oh, yeah!)
- Free if the customer (the US government) licensed other software
- One time charge. Upgrades are easy. Buy another license.
- Free. The vendor is in the business of selling engineering support, training, and custom widgets to make the search system sort of work.
- Whatever can be billed. This is extremely popular because the negotiation process reveals the allocated funds and the search system vendor angles to get as much of the allocated cash as humanly possible.
- Free for the first budget cycle. Then when funds become available, prices are negotiated.
- Custom quote only. NDA required.
Today, life is easier. One can download a free and open source search system, hit the local university for some “interns”, and let ‘er rip. Another alternative is to look for a hosted search service. Blossom.com maybe?
Net net: Pricing has one goal: Generate revenue and lock in for the vendor. That’s one reason why vendors of what I can search centric services are so darned lovable.
Stephen E Arnold, July 3, 2020
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What do you mean by “cell”?