An algorithm has multiple definitions yet in all well considered ones it is a procedure for doing a particular computation. As Aaron states above the word in adtech means whatever is needed that day.

That said, let's discuss what makes a GOOD algorithm.

A mathematician might say that an algorithm also needs to be shown to solve problems effectively, either in practice or theoretically. A good algorithm is one that is known to work well, for instance it can be proven to be optimal or at least (1-epsilon) optimal where epsilon is small.

In addition to optimality a computer scientist might be concerned with the efficiency of the algorithm. How fast does it run? Can it be parallelized? Good ones scale when needed without sacrificing effectiveness.

In business practice a good algorithm leads to an increase in efficiency of the business in some measurable way. Higher revenue per worker. Less repetitive effort, increased same store sales, higher order volume, etc.

What are classes algorithms in adtech? Executing targeting expressions to match supply and demand is done with an algorithm. Deriving the minimum pricing of inventory might be done with an algorithm. Calculating bid prices should be done with algorithms as well. The analytics in adtech is often performed with sophisticated sampling algorithms or might be a massive parallel computation of the whole data set. Forecasting inventory 'avails' is also done with algorithms, and this is actually a known hard problem if the targeting is rare.

What is NOT an algorithm? RTB is not an algorithm, it's a protocol for exchanging information. APIs are not algorithms, they are defined mechanisms of executing operations on an internal or external software system. As a computer scientist I would assert that a simple single rule "IF A then DO X ELSE DO Y" is not much of an algorithm... it's just a rule.

What is the state of algorithms in AdTech? I'd say mixed. What passes for an algorithm is not well correlated with any definition of 'good'.

Here's a fascinating data point: For yesterday 54.4% of all RTB bids Rubicon's real-time trading platform saw for the same creative had less than 4 distinct bid prices. What does this mean? The 'algorithms' that set the bid prices for 54% of the campaigns attempting to buy inventory are of questionable effectiveness.

Just thought that I'd weigh in from the perspective of a marketing attribution software provider: An algorithm is a systematic way of doing things – an approach that is repeatable. An algorithm can be good or bad at its intended job, but it's a path to get to where you want to go. Computers are great at following algorithms, but it takes human intelligence to build them, and to compare them to real world results/phenomena to evaluate their accuracy and effectiveness. As the old expression goes: "Man plans, and God laughs." Well in the marketing world, "engineers build algorithms, and the results produced by acting on them validate whether they are any good or not."

And that difference is bigegr the farther you get away from the big publishers. At a big publishing house it's the marketing department that decides the size of the advance, not the editor. So proposals from the get go are pitched to marketing departments. Writers who survive on advances structure the content of their book accordingly.

An algorithm has multiple definitions yet in all well considered ones it is a procedure for doing a particular computation. As Aaron states above the word in adtech means whatever is needed that day.

That said, let's discuss what makes a GOOD algorithm.

A mathematician might say that an algorithm also needs to be shown to solve problems effectively, either in practice or theoretically. A good algorithm is one that is known to work well, for instance it can be proven to be optimal or at least (1-epsilon) optimal where epsilon is small.

In addition to optimality a computer scientist might be concerned with the efficiency of the algorithm. How fast does it run? Can it be parallelized? Good ones scale when needed without sacrificing effectiveness.

In business practice a good algorithm leads to an increase in efficiency of the business in some measurable way. Higher revenue per worker. Less repetitive effort, increased same store sales, higher order volume, etc.

What are classes algorithms in adtech? Executing targeting expressions to match supply and demand is done with an algorithm. Deriving the minimum pricing of inventory might be done with an algorithm. Calculating bid prices should be done with algorithms as well. The analytics in adtech is often performed with sophisticated sampling algorithms or might be a massive parallel computation of the whole data set. Forecasting inventory 'avails' is also done with algorithms, and this is actually a known hard problem if the targeting is rare.

What is NOT an algorithm? RTB is not an algorithm, it's a protocol for exchanging information. APIs are not algorithms, they are defined mechanisms of executing operations on an internal or external software system. As a computer scientist I would assert that a simple single rule "IF A then DO X ELSE DO Y" is not much of an algorithm... it's just a rule.

What is the state of algorithms in AdTech? I'd say mixed. What passes for an algorithm is not well correlated with any definition of 'good'.

Here's a fascinating data point: For yesterday 54.4% of all RTB bids Rubicon's real-time trading platform saw for the same creative had less than 4 distinct bid prices. What does this mean? The 'algorithms' that set the bid prices for 54% of the campaigns attempting to buy inventory are of questionable effectiveness.

Just thought that I'd weigh in from the perspective of a marketing attribution software provider: An algorithm is a systematic way of doing things – an approach that is repeatable. An algorithm can be good or bad at its intended job, but it's a path to get to where you want to go. Computers are great at following algorithms, but it takes human intelligence to build them, and to compare them to real world results/phenomena to evaluate their accuracy and effectiveness. As the old expression goes: "Man plans, and God laughs." Well in the marketing world, "engineers build algorithms, and the results produced by acting on them validate whether they are any good or not."

And that difference is bigegr the farther you get away from the big publishers. At a big publishing house it's the marketing department that decides the size of the advance, not the editor. So proposals from the get go are pitched to marketing departments. Writers who survive on advances structure the content of their book accordingly.