This week in my digital marketing class, we are continuing our discussion about how companies can utilize different database marketing techniques to encourage consumers to act in a certain way. Database marketing is a form of direct marketing that uses different databases and the consumers previous purchase history to create personalized messages to prospective customers. “Companies personalize products, offers, content, and communications for a variety of reasons — to treat customers uniquely, to make them feel special, and to encourage them to spend more,” (Sridharan). Not only can database marketing encourage the consumer to spend more money, but it also makes them feel unique, which can quickly create a special bond between the consumer and the company.
One of the most complicated aspects of database marketing is harnessing the ability to make accurate and appropriate item suggestions based off of a consumers previous history. Nowadays, because of recent technological advancements, the process of reaching out and making these personalized suggestions is easier than ever before. Marketing researchers now have access to a wide variety of tools such as different analytical methods, including recommendation engines, business rules, and collaborative filtering. Even though these companies have access to these tools, that doesn’t mean they automatically know how to use them correctly. In the article Use Customer Analytics To Get Personal, the author discusses how companies can often times over simplify specific behaviors of a consumer. Companies tend to make the mistake of projecting entire an groups behaviors onto specific individuals based off one interaction, which doesn’t always work because consumers operate differently depending upon a number of outside factors.
While I was in the middle of reading the different articles that were assigned by my digital marketing professor, I kept getting side tracked thinking about the various forms of database marketing I was subjected to on a daily basis. I decided to take a deeper look at each of the websites I visited on a regular basis to see if I could find any forms of database marketing. What I found was not surprising at all, I was able to find numerous different examples of database marketing. I found hundreds of recommendations from websites such as YouTube, Amazon and Netflix, and I have been receiving hundreds of emails from websites such as Orbitz, Groupon and, Ticket Master. I decided to place three different examples into three different categories.
The Good: Netflix Suggestions
Anyone who has owned or used a Netflix account is probably familiar with the concept of the Netflix suggestions. Every time that I log onto my Netflix account I see this:
The idea is to promote new shows that you haven’t already seen based upon the shows that you have previously watched. Within the Netflix database the company has access to your account and they can see what you have already watched, and then they use that information to make different PERSONALIZED suggestions. Just this past weekend I logged onto my Netflix account to kill some time, as I was scrolling through my home page I saw that Netflix suggested that I watched a show called The Following. It said something along the lines of “Based off your interest in LOST and Breaking Bad…We suggest The Following”
I decided to give the show a chance, and now I am on episode five and I am doing everything I can to finish my homework assignments (this blog) before watching another episode. This is a perfect example of how database marketing can successfully encourage consumers to act in a certain way.
The Bad: Personalized Email
When I was looking through my emails to find any form of personalized messages, I kept coming across emails from three particular companies; Orbitz, Groupon, Ticket Master. On average I am receiving around 3-4 messages a week from each of these companies with headlines that say “Hey Brent!” or “Brent! Check out these great deals!”
While normally these specialized headers may catch my attention, I have trained myself to ignore these emails because the content inside no longer pertains to my interests. For example, I signed up for an account with Orbitz last year when I was searching for the cheapest flights to Cabo San Lucas for spring break. At the time, advertisements from Orbitz about scuba diving deals and hotel rooms made sense, but now 9 months later, I am receiving regular emails about cheap hotel deals in Costa Rica and Hawaii.
This is an example of poor database marketing because a larger portion of their advertisements specifically relate to that one single transaction. Their information on me is extremely skewed because the computer doesn’t recognize that I am not only interested in tropical vacations.
The Ugly: Elephant Shirt
The last example of database marketing that I am focusing on was by far the most surprising. Although my story doesn’t quite compete with the famous Target example, it still continues to blow my mind. It all started two summers ago when I started to notice multiple advertisements from a company selling realistic animal shirts. Initially I found the advertisements to be rather annoying, and I thought the shirts looked stupid so I never bothered to click on any of the advertisements. But one day, after weeks of noticing these advertisements on my Facebook, I caved and decided to look at the shirts. As I began to browse through the site, I started to find the shirts to be extremely funny and I found myself contemplating about purchasing one. After clicking on the link once, I started to see even more advertisements on Facebook and Amazon.
After that, everywhere I went I felt as though I was being bombarded with these clever little shirts. I didn’t understand (until now) how exactly this company so successfully convinced me to like these ugly shirts. Now I believe that the company decided to target me with these ads based off information from a database that stored my previous search history or purchasing behavior.
Long story short:
As time went on, I continued to see these advertisements. Finally, after weeks of being haunted by the advertisements…This happened: