Business Optimization and Testing Basics
Optimization and testing became buzzwords in the digital world when big technological companies like Amazon, Google, and Netflix shared their experiences and results. Business optimization is not a new concept created by the Internet era, but rather, one that has been a vital part of business for years.
Business optimization is an ongoing process driven by data intended to discover hidden opportunities that can shift or improve your business. If you have some known issues with your current product or a desire to keep shifting your business strategy, optimization and testing can prove valuable tools. Long-term goals, including cost reductions, increases in revenue, or improvements in customer satisfaction and general experience, can be accomplished through optimization and testing.
Unfortunately, when I meet with young digital analysts, one particular issue proves very common: the narrow view of the optimization and testing process only within the context of digital assets they can see. Expensive tools are purchased, but emphasis is given to testing the shape and color of buttons. While content testing is one of the areas we want to work on it, it is only small part of your digital optimization.
Optimization is based on scientific testing techniques that are used to arrive at conclusions when results are not absolute. For example, when a scientist develops a new medicine to cure certain disease, she needs to test her medicine with real patients to evaluate not only the results of the treatment, but its side effects, too. Not every medicine will cure every patient of the same disease because of each individual’s differences. In this case, optimization and testing yields the desired results, as the optimum combination of people will be cured (increasing customer satisfaction), with the fewest side effects (improving customer experience), and the greatest possible revenue will be produced for the firm.
Two examples in the airline industry can help illuminate the utility of optimization as a technique. Airlines have proven to be pioneers in the optimization area, using complex mathematical techniques for years. As an old airliner, I have great sympathy for those who are trying to optimize this process, as it proves very complex and must consider the safety of passengers, the profitability of the airline, and various rigid regulations.
Airline Optimization Example 1: I have X number of planes with different configurations and have Y number of destinations all around the world. I also have an average of Z passengers flying on these routes which can change depending on season, day of week, or by any other operation reasons. How should I assign airplanes to these routes to make sure operations run smoothly while still making a profit?
Low cost carrier Southwest Airlines knew the difficulty of this optimization dilemma, deciding to address it by using only one type of aircraft for all routes, saving money on maintenance costs while simplifying the optimization formula.
When you assign aircraft to routes, you also have to consider the sleeping time of an aircraft. Airlines generate money when their aircraft are in the air, creating a need to minimize the aircraft’s time spent sitting idly in the airport. “Sleeping” at the airport results in higher airport parking fees, more maintenance costs, and zero revenue.
As the example demonstrates, optimization proves a vital part of an airline’s business strategy, requiring the analysis of large amounts of data to accomplish automated optimizations.
Airline Optimization Example 2: Another airline example revolves around airline pricing models, which frequently result in two passengers paying different rates for the same trip, achieved by using revenue or yield management. You might feel upset discovering this pricing discrepancy (especially if your neighbor in the seat over paid less than you), but airlines must use this pricing model to keep flying, as they have some of the lowest profit margins in the business world.
Airlines sell seats for an exact route at an exact date and time. When the flight takes off, the airline loses its chance to sell its empty seats, so the product, in a sense, is perishable. Optimization techniques answer the question of how much an airline should charge for this perishable product. An aircraft’s take-off cost will be very similar whether it has 200 or 10 people on board. It will still have same amount of check-in personnel working, a similar amount of fuel used (depending on the weight of the aircraft), and you will have the same amount of in-flight crew employed, as regulated by the FAA depending on aircraft type. In this case, it is in the best interest of the airline to sell as many seats as possible to help cover the fixed costs of the flight. Consider an example where 200 seats are available on a flight and the break-even point would be reached if each passenger is charged an average of $250. Our knowledge of supply and demand would alert us that some passengers would be willing to pay more than $250 for the flight, while others wouldn’t even consider such a high price. Airlines find optimum price points by relying on revenue management systems which continuously check demand. Each fare and rule levels are associated to certain booking classes which are closed and opened depending on time of day and overall demand. For example, if you buy your ticket very early, you are likely to get cheaper tickets, as they were released at the very beginning of the booking process.
These examples demonstrate the vast potential of optimization in business and may help us evaluate digital businesses in a more careful way.
When you are using Google, you are part of an optimization and testing process that helps Google find more relevant search results in the shortest possible amount of time and with the least possible effort. It is in Google’s best financial interest to help you avoid irrelevant results. This motivation helps explain why Google’s AdWords algorithm does not move the advertiser who bids the most to the top of the page, as Google must ensure that the advertisement is relevant and the company behind it has a solid track record. Google will feed itself more data everyday to make this process better. That’s why older Google AdWords accounts with good track records can bid less than those who started bidding recently, which require Google to gather more information to ensure quality.
I hope this post gave you more ideas about what to test and optimize. Please remember that your content, mobile apps, and websites are vehicles to your end goal. Digitalization changed the business world dramatically, but the fundamental goals of a business remain: generating the greatest possible profit, continually-lower costs, and consistently improving customer experiences. We have to keep this concept in mind when we perform our digital optimization.