From Ogilvy to Zuckerberg: How did Amazon, Apple, Facebook and Google change consumer research and targeting ?

Conventional (TV, print, radio) advertising often relies on research and targeting methods such as focus groups or demographic targeting to increase brand awareness and sales. These methods seem to be more and more outdated as targeting technology is already delivering better results.

A (very) short history of advertising research and targeting

In the past, as media was unidirectional (broadcaster to consumer), there were few ways retailers could efficiently target potential consumers. Advertisers would use consumer profiles and split purchasing options through demographic indicators (age group, location, education, sex etc.). By using statistic results they could outline marketing opportunities for certain demographic groups (Ex. “Women between 25 to 35 years, urban, having higher education are more likely to buy Product X”).

Having (theoretically) discovered a potential consumer profile they would then buy media in newspapers, radios or TV stations that would best appeal to that certain demographic group.

David Ogilvy
David Ogilvy

Of course this is just a skeletal description of the whole targeting process but it explains the process pretty well. Many companies have benefited greatly from this targeting and advertising system. Most of the brands we now know and buy were built this way. Even now, decades after the likes of David Ogilvy were setting up the rules on research-based advertising, the system is virtually unchanged.

“I notice increasing reluctance on the part of marketing executives to use judgment; they are coming to rely too much on research, and they use it as a drunkard uses a lamp post for support, rather than for illumination.” – David Ogilvy

How did the Internet change research and targeting?

Few could have predicted the impact Internet was to have on commerce and economy. Even less would have guessed how this initially “exotic” media would impact research and targeting.

20 years ago there was no marketing concept that could explain AdWords targeting and not be considered science-fiction.

Internet targeting and advertising renders most of conventional knowledge on research obsolete as technology has achieved what was once impossible. 30% of all human population is now in reach of all advertisers and they can now target more than just demographics.

Behavioral marketing is a concept that could not be possibly be achieved with conventional media. Using consumer behavior rather than demographics advertisers can target real time preferences and individuals rather than demographic groups. Say a user is known to have previously visited a car dealership website. He then browses websites in search of reviews on different car models. The car dealership could potentially target this exact user and serve him the most informative ads. Advertising ROI is sure to increase this way.

Some companies have become increasingly good at Internet research and targeting. One of them is now the most valuable company in the world in terms of market capitalization. Let’s have a look at how Apple, Amazon, Facebook and Google use large data to target and monetize consumer traffic.

How did Amazon, Apple, Facebook and Google changed consumer targeting ?

Amazon personalized recommendations

amazon logoAmazon is well known for its personalized products recommendations. How can it do this? Short answer: large data on consumer purchases and mathematics. Longer answer: Amazon holds a patent on its product recommendations which you can have a look at here (issued in sept. 2006). Although rather technical it focuses on certain key elements:

  • user profiling: Amazon holds valuable data on user demographics and previous purchases. Using this data it can map users in specific consumer groups. User profiling combines shopping cart contents, item ratings and recent purchases as purchase intents seem to change in time.
  • similar products information: say you bought three SF books. Similar products would be other books in that category. Some of these books would be more popular in terms of item ratings, reviews, views and purchases.
  • item affinity is the probability of some products to be purchased together. Say you are buying a Kindle on Amazon. You are very likely to buy a cover or case to protect your device. That means these products have a high affinity index
  • driver items are those products that are most likely to drive traffic to store. Again – the Kindle, Amazon’s best seller is not only a driver item but also a platform that insures further product purchases.
  • user path: the consumer will follow a certain path until it ads a product to the shopping cart or confirms a purchase. These paths are very important as they can be used to “guide” consumers to products they are most likely to purchase.

Using these information (and probably more) Amazon can first map users in consumer groups (1), extract popular, affinity and driver products (2), compile most profitable user paths based on previous history and other users actions (3) and than recommend the items most likely to increase basket size.

Recently Amazon announced the launch of its Kindle Fire product. This product is built on a Android platform and uses a proprietary web browser called Silk. The browser optimizes web traffic by routing it through Amazon’s servers. As Amazon already holds information on user profiles (users will have to login to synchronize their book collection) and now data on web traffic it can further improve its recommendations.

Apple Genius recommendations

apple logoAlthough Apple does not explicitly state it monitors iOS user actions it doesn’t deny it either. If it does, however, it might access a huge pool on users data such as web traffic, mobile purchases, locations, call history, social networking information (through access to contacts information, call history, SMS and iMessage history etc.). Basically everything there is to know on its customers profile.

For now the most visible way Apple uses data to increase sales is iTunes Genius, the music and video recommendation system. iTunes Genius uses purchase history and iPod activity to recommend potentially interesting songs, albums or videos.

Although iTunes Genius probably uses a system similar to Amazon’s it is not yet known to be as accurate. The performance issues are probably connected to the number in customers and items on sale. Amazon has a wider products inventory and a larger pool of potential customers. This leads to a larger database and increased accuracy.

Technology based companies have changed the way we think of consumer targeting and advertising. Innovation lead to profits and behavioral targeting will probably develop in the future. Tomorrow we’ll have a look at how two of the largest advertising – revenue based companies, Facebook and Google, use large data to improve consumer targeting. Stay tuned.

Behavioral Economics and Social Media

Humans are not usually rational. The neoclassical economists were wrong. We don’t make the best economic choices given more information. We do not plan for the future. We care about what others think of us. We act on impulse. All these things are the basis for Behavioral Economics Theory.

This (rather) new economics theory has caught momentum and is now one of the hottest topics in theoretical economics. Well… as hot as an economics theory can be. It blends psychology and neoclassical economics (the thing we generally call economics) to help explain why we act the way we act and to help policy makers increase the likelihood of better economic decisions.

There are many variables and a lot of information on the subject but for a better understanding we can look at some principles outlined by The New Economics Foundation:

  1. Other people’s opinion matters: we take great interest in what others think or do. We don’t usually get informed on economic topics. We usually copy behavior and decisions. Why? First of all we are a social species. We want to be socially acceptable and we can do that easiest by mimicking. It’s also easier.
  2. We are creatures of habit: even if what we do is economically wrong we will continue doing it out of convenience or because we have a habit that forces us to do what we do.
  3. We want to do the right thing: we have an innate sense of justice that leads our behavior. Most of us pay our fines not because we might go to jail but because “it’s the right thing to do”. We help others because it makes us feel good, not because there is any financial incentive in it. Actually such incentives may actually be counter-productive as they take out the primarily motivation – doing the right thing.
  4. We act according to our self image: we care about our commitments and we like to stand up for what we believe in. We see ourselves in a certain way – that leads us to certain kind of behavior in order to avoid cognitive dissonance.
  5. We are more loss averse than gain interested: we hang on to what we believe is ours. We treasure our possessions more than we value what we could potentially gain.
  6. We are not very good with data: we don’t really understand numbers, we’re bad at calculating probabilities and we take decisions based on how information is presented to us.
  7. We need to feel empowered to take action: too much information can lead to the inability to act. Too many options make us feel helpless. People need to have a clear understanding on how their actions affect the world around them to fully commit to any activity.

Behavioral economics in social media

Feelings, sharing, likes, friends, fans are not words we usually hear in business economics. We do hear them pretty often these days in social media. Business are starting to understand the importance of customers behaving socially. Social behavior is what drives companies to success or into the ground. There are no formulas in financial economics that can describe the feelings people have toward one company or another.

Classic economic behavior can be described in numbers on a spreadsheet but is not the way real people act. It is a flawed economic model in an economy that results in debt and frustration. The first result can be seen in the financial models we’re currently looking at. The second one cannot.

There is a growing media that helps express and amplify the principles of behavioral economics. That is the Social Media. With the growth of such social networking companies such as Facebook or Twitter, people started acting more and more connected. We now have an way of observing behavior with the help of social media. As it turns out all the principles of behavioral economics can be seen in social media. Let’s have a look at them:

Behavioral economics principles at work in Social Media

  1. Other people’s opinion matters: we care what our (Facebook) friends think of us. That’s why we share interesting quotes, we “like” only certain brands and we are very careful before posting something online.
  2. We are creatures of habit: first of all have a look at your behavior today. You have probably checked your Facebook timeline or Twitter profile at least once today. Why? Because you are accustomed to Facebook. You can’t give up checking the news, the photos your friends posted or the new products your favorite brand advertised on Facebook. Increase in mobile internet popularity is only enhancing this behavior.
  3. We want to do the right thing: people are sharing more and more social causes through social media. With over almost 1 bn users, Facebook acts as a catalyst for social causes. Social causes spread fast and users are very likely to share social messages. But that’s not all. Individuals as well as organizations now know that anything wrong-doing can have a long term negative impact on their life. Here is a video of a police officer pepper spraying demonstrators that quickly lead to a large negative social media response. If you were to search Google for the phrase “Sgt. Pepper Spray” you will find no less than 213 000 pages that frown upon his behavior. Eventually his email address and home address leaked to the internet. You can imagine the outcome.
  4. We act according to our self image: People have a certain self image that translates into social media behavior. For example: Barack Obama’s “Hope” presidential campaign was not really about the soon to be president. It was about the people that he represented. People found in the campaign a positive message for change. They’ve seen that the presidential candidate expressed a need for better people to run the country. People such as themselves. A lot of Obama’s success story happened on the internet where people expressed their views on “Change”. The messages they’ve spread were positive expressions of self image. People were not “like”-ing Barack Obama. They were “like”-ing themselves and the way they wanted their friends to see them.
  5. We are more loss averse than gain interested: Think about how often you see messages like “don’t lose the opportunity”. Why? Because they work. Groupon cashed in on the feeling people have regarding limited time discounts. So did Woot. Using loss-aversion works really well in online retail.
  6. We are not very good with data: If neoclassic economics theory would be true and if we really were rational beings, Groupon would never had caught on. Buying a discounted sky dive or a night lamp when we have ten already does not make sense economically. However, people did buy those things. Why? Because social media goes hand in hand with presentation bias. Suppose we see a 70% discounted offer on blue handkerchiefs that were already bought by 300 people. We think – “oh my, I must buy that handkerchief now or they will go out of stock. Look – 300 people already bought it”. The information has been framed (70%) and enhanced by other people’s behavior. We do not think whether we need the handkerchief or not, whether it is an economically safe behavior. We see the deep discounted price, we see that other have already bought this (see point number 1.) and we “need” to buy the handkerchief. Now.
  7. We need to feel empowered to take action: there are millions of products on Amazon. Billions of web pages indexed by Google. If we were to browse rather than search we would probably get frustrated and quit. However – we still use Amazon and we still use Google. Why? Because of targeting. Both companies dig through millions of terabytes regarding other people’s behavior to serve us the products and results we are most likely to buy or open. That makes our choices easier and we feel empowered to act.

I believe behavioral economics are here to stay. The kind of human behavior they explain has always been here. Social media is just acting as a catalyst to this kind of behavior. If we are to look deeper into behavior economics we need to use social media data to better understand the way we act and how can we get to economic results. The internet economy is growing at a faster rate than any other sector because successful online entrepreneurs already know the seven principles outlined here even if they’ve never heard of behavioral economics.