Real-Time Pricing Algorithms – For or Against Us?

Christmas ball

In 2012, Cyber Monday sales climbed 30% over the previous year’s results. Indeed, Cyber Monday benefits both online retailers as they gain massive Christmas spend in one day, and consumers can shop at work or home and thus skip holiday crowds.

And yet, underneath the bustle of ringing “cyber cash registers”, a battle brews as retailers now can easily change prices, even by the second, using sophisticated algorithms to out-sell competitors. Consumers aren’t standing still though. They also have algorithmic tools available to help them determine the best prices.

Christmas ballLet’s say you are thinking about buying a big screen television from a major online retailer.  The price at 12 noon is $546.40, but you decide to go get some lunch to think about it. An hour later, you check back on that same item and now it’s priced at $547.50.  What gives?  Depending on your perspective, you’ll either end up being the beneficiary of algorithmic pricing models or the victim.

A Financial Times article notes the price of an Apple TV device sold by three major online retailers changed anywhere from 5-10% daily (both up and down) in late November. Some HDTVs changed prices by the hour.

These up to the minute changes are made possible by real time pricing algorithms that collect data from competitor websites and customer interactions on their own sites, and then make pricing adjustments based on inventory, margins, and competitive strategies.

An algorithm is really just a recipe if you will, codified into steps and executed at blinding speed by computers.  Thus, a pricing algorithm may be using inputs from competitor websites and other data sources, and then based on pre-defined logic, churn out a “price” that is then posted on a website. Typically this process is executed in seconds.

Thus, it is increasingly common –depending on the specific item, day, hour, or even minute—that prices of online items change in a moment’s notice. If keeping up with rapidly rising and falling prices seems like a shopper’s nightmare, you’re right. However, consumers also have tools to fight back.

The same FT article points out that some consumers are using websites such as to determine the best if not the most “fair” price points. Using either, or Decide’s convenient smartphone app, for an annual fee of $30, a consumer can access pricing predictions of items based on Decide’s predictive pricing algorithms.  Simply look up an item, and gives its best prediction of when to buy an item and where.

Today, we take for granted that grocery store prices generally don’t change within the hour, and that prices at the gas pump (while sometimes changing intra-day) generally don’t change by the minute. As data collection processes move from overnight batch to near real time, expect more aggressive algorithmic pricing, coming to a grocer, gas pump—or theater near you!

Zero Latency: Faster Isn’t Always Better

Vendors often promise some derivative of the term “faster” in marketing and sales literature (i.e. faster decisions, quicker time to value, rapid implementations etc…). And to be sure, in plenty of cases, speed wins especially in terms of gaining insights into markets and customers before competitors get a clue. However, when it comes to decision making, too much speed without attention to improvements in logic and business processes can be disastrous.

It’s easy to confuse “fastest” with “best”. That’s what Jennifer Hughes writes in a Financial Times article on the arena of high frequency trading (HFT). The term HFT refers to buying and selling financial instruments in microseconds with the help of supercomputers, sophisticated algorithms, and in most instances co-location of equipment near stock exchange servers. In HFT, the goal is to make profitable trades faster than competitors, and this means that massive amounts of data must be examined in real time and buy/sell decisions executed in microseconds.

While an extreme case, high frequency traders are truncating the decision making window between “event” and “action” to near zero. In the previously mentioned Financial Times article, Kevin Rogers of Deutsche Bank says; “With some parts of the market we are getting to the point where the speed of light (is the only constraint).” And certainly, if one company can spot deals and trade faster than another, microseconds can be a significant advantage in profitability.

However, while in many cases speed wins, there are concerns, especially in terms of cost. After all, throwing millions of dollars in compute power to shave off a couple of microseconds might not be worth the investment. “We’re looking at a tipping point,” says Harpal Sandu, founder of electronic trading network Integral Development. “Trading isn’t going to get much faster than a few dozen microseconds—physical machines don’t run much faster than that.”

In addition, making decisions faster than competitors is useless if careful attention is lacking in data input, decision logic (possibly manifesting in algorithm development) and continual process improvement.  Moreover, the best decision today, or even ten minutes ago, might not be the best decision tomorrow, especially because external conditions make for a moving target with governmental policy changes, mergers and acquisitions, new technology development and more.

A final consideration is fragility. In high frequency trading for example, as trading decisions move closer to zero latency, there is less opportunity to remedy a potential mistake whether it consists of a “fat finger order”, or simply a poor trading decision that a company would like to correct. Adding insult to injury, in a complex environment such as stock markets, a poor decision made quickly can cause cascading effects to other players creating a massive market disruption.

In the countdown to zero latency, the focus is currently on speed. However, the returns on faster decision making are diminishing and equal opportunity should also be given to risk management considerations, business process improvement, and monitoring of business conditions to continually upgrade and refine decision making logic.


  • Can speed drastically increase without introducing fragility?
  • Does a focus on speed provide an opportunity for companies to “get better” in how they deliver products and services?

Zero Latency: The Next Arms Race

no speed limitIn the near future, your company may be competing with a computer.

In fact, companies with the fastest computers, most sophisticated algorithms, technical know-how and most complete data sets will begin to separate themselves from competitors. In a world where milli-seconds will make or break your company, how should you best prepare for this new arms race?

Zero latency is all about reducing the time between when an “event” occurs and subsequent action from your company. GPS phones, sensors and real-time analytics are just some of the technologies allowing businesses to sense and respond to changing market conditions in shorter intervals of time.

Let’s look at the world of high frequency trading (HFT) for a preview of a zero latency future.

In a gross oversimplification of a very complex topic, high frequency trading is a strategy where financial companies purchase ultra-fast computers that execute trades autonomously. By subscribing to data feeds from stock exchanges and other sources, these companies often use algorithms to analyze data (voice, video, html, stock quotes etc.) as they pass by and then execute an instruction (bid/offer) for a security. The capture of data and analysis is completed in milli-seconds.

In fact, for HFT speed is of the essence. To make a trade faster than competitors, some companies have seen fit to place their servers directly on the floor of the stock exchange—effectively giving them a direct pipe into the trading platform.

A Traders Magazine article notes that many HFT firms use, “chips designed for video games to more quickly process the market data that enters their models.” The same article also mentions that, “some (HFT) firms are investing $2m every other month on new servers.”

HFT companies are actively scanning multiple data feeds for anomalies, detecting events in real time, and then executing based on predefined business rules. In this new arms race, to make money, HFT companies have discovered that zero latency wins the day. In other words, high frequency traders know they must be milli-seconds ahead of their competition in transforming data streams into actionable insight.

And while HFT is all the rage in financial circles, it’s not far fetched to see how in other industries, the ability to respond faster—to customer needs or changing events is conferring competitive advantage. Some examples:

  • Netflix’s Cinematch algorithm serves up movie recommendations in real time, based on subscribers past rental history and movie ratings. The right recommendation keeps customers satisfied and inventory turning.
  • Airlines often reroute flights based on weather events in real-time, making sure connections are not missed for their most valuable customers.
  • sends out 25 million event-driven emails each week (each with a dozen personalized recommendations) to over 300 customer segments. Campaigns go out daily, whereas some marketers take weeks to build a campaign.
  • And of course, Google serves up real time recommendations (advertisements) in milli-seconds based on your browsing history via cookie and search input

Zero latency means much more than making a fast decision. After all, making a poor decision—faster—isn’t going to help a company win market share.

While companies rapidly upgrade their analytical infrastructure and clean their data, they must also have the right talent in place to constantly tweak and keep their algorithms and models current. That said, in some cases these algorithms will actually “learn” from their successes/failures and improve, without human intervention.

Thoughtful analysis of changing market conditions is a mainstay of successful companies. However, in the near future, some analysis (based on quick correlation) will no longer take days and hours—it will be done in milli-seconds.

In a fast paced global economy—in most instances—latency in decision making will not be your friend. The best execution will be based on collecting and analyzing data and then acting faster than the competition. Is your company ready for a zero latency future?

  • Advances in hardware technology and advanced analytical applications make zero latency possible. Will small to medium size companies with lower IT budgets be able to compete? Is this fair?
  • What impact will a zero latency future have on the skills marketers need to effectively compete?
  • With advent of Smartphones and location based services, accurate behavioral targeting will be a key beneficiary of “zero latency”. Is a Minority Report future that far away?