AdExchanger reached out to a group of programmatic media "top guns" and asked for their thoughts on:
"What is an algorithm?"
Click below or scroll down for more:
- Dean McRobie, CTO, Annalect (Omnicom)
- Jason Kelly, CEO, Sociomantic
- Rob Griffin, EVP, Global Director of Product Development, Havas Digital
- Matthew Goldstein, EVP Business Development and Founder, Korrelate
- Aaron Kechley, SVP, Products, DataXu
- Konrad Feldman, CEO, Quantcast
"To me, an algorithm is any piece of automated code that accepts some number of variables and data, [then] uses those variables and data to make decisions. But that’s the boring computer science definition. In the world of programmatic buying, algorithms represent the rules we use to place bids on biddable media: display, mobile, search, social, out of home, etc. Algorithms have to take into account the market, the marketing objectives, the budgets and ancillary factors around the individual bid (for example, how does the current search volume for a brand effect what they might be prepared to pay for a display banner?). The algorithm is the secret sauce in programmatic buying. The real challenge is how do the algorithms in disparate systems fit together to ensure more efficient and effective marketing for our clients?"
"An algorithm is a set of instructions for multivariate calculations that learn and adapt over time. To humanize this answer for digital advertising, an algorithm is a calculation that should simply meet customers’ goals creating value in the most cost-effective and transparent ways possible.
Unfortunately, the word ‘algorithm’ is often one of the first talking points that vendor partners in our space refer to but can say very little about given that most platforms are built on proprietary technology. This overuse of the word has created ‘algorithm fatigue’ and resulted in loss of meaning. Advertisers who want more than just marketing speak around algorithms should focus on customization to fit their needs and bottom line revenue results that are transparent."
Rob Griffin, EVP, Global Director of Product Development, Havas Digital
"Lets start with what it is not. An algorithm is not human-less automation. An algorithm is not a human-less tool. An algorithm is at its simplest a process followed in executing calculations for processing data and decisioning. To quote from Wikipedia’s definition of an algorithm, it is “more precisely, an effective method expressed as a finite list of well-defined instructions for calculating a function.” In our industry this is leveraged for improved analysis to generate more efficient and effective marketing communications and better optimization.
Now that said, an algorithm needs to be defined and told what to do. Whether the algorithm exists for the planning & buying of media, or within dynamic creative, a DSP, an SSP, a Facebook optimizing platform, a landing page targeting tool, and/or a bid manager for search we need smart professionals behind them in order to leverage what algorithms can do to help improve what we are trying to do which is create a better customer experience across paid, owned, and earned media … more efficiently.
Another way of looking at it is this, a high end race car is only as good as the driver."
Matthew Goldstein, EVP Business Development and Founder, Korrelate
"Five different, yet simple answers to define an algorithm.
- 'It’s a Proprietary Algorithm' is the stock answer when engineers cannot clearly identify how results were obtained
- Algorithms are a company's secret sauce -- think Google search results or FB news feed or Goldman Sach's investment strategy – a good algorithm is worth billions and other algorithms are worth pennies
- All good and valuable algorithms are proprietary so it is virtually impossible to define/understand the ones that really work
- The best algorithm I have ever personally created was a way to predict ad sales revenue, then RTB/programmatic entered the market and rendered my algorithm worthless; so I am now working on a new predictive algorithm, so wish me luck.
- Algorithm = wild-ass guess'"
Aaron Kechley, SVP, Products, DataXu
"Quasi-technical Definition: a well-defined and finite process for transforming an initial state and inputs into a final state and output.
Ad-tech Definition: varies depending on the day, but usually whatever people want it to mean.
Practical Definition: an automated way of making transactional decisions to maximize a quantified outcome, such as user actions, sentiment shift, or viewability. Algorithms can be simple or hugely complex. They can use advanced math or simple rules. Algorithms can be subject to constraints like budgets, targeting, or pacing. The more constraints, the harder it is for a given algorithm to maximize the desired outcome. In advanced marketing software, an algorithm is not static, but is continuously trained using live data.
There are no one-size fits all algorithms in marketing – different designs have different strengths and weaknesses. Rather than chasing “the best” algorithm, you’ll have more luck with a system that can provide flexibility and choice of algorithms designed for a wide range of marketing needs."
Konrad Feldman, CEO, Quantcast
"An algorithm is like a recipe. A recipe provides detailed directions that convert ingredients into a dish, and there is a wide range of different recipes. In the case of algorithms the ingredients are various types and pieces of data and the dish is information. So an algorithm is a precise method for converting data into useful information.
Within the context of programmatic buying, the data ingredients available relate to the placement, the time of day, the user’s location, the cookie ID and any related historical or third party data available. And of course the performance goals of the campaign, pacing or other constraints, and any observed performance to date (potentially the result of a prior output of the algorithm).
Traditionally these different dimensions are considered and decided separately by simple algorithms, generally simple enough that humans can execute them. Placement decisions, for example, might be based on human intuition about which sites make sense to advertise on, and refined later by turning off under-performing sites. The pacing algorithm might be as simple as tuning a bid CPM and a frequency cap.
But real-time bidding has opened the door for much more sophisticated algorithms that can only be managed by machines. The best of these make different decisions on each impression and take into account dependencies between dimensions. For example, rather than turning off a site that underperforms on average, a bidder might continue to bid for it only for a subset of consumers for which it performs well."