If you have spent some time in marketing classes within your MBA, or involved with marketing/campaign team in your past experience then you would be knowing this, every marketing effort starts with one step called as Segmentation. STP (Segmentation, Targeting and Positioning) is something that we have all gone through. In this article I am going to talk a little bit about Segmentation and then in next post we will see how segmentation as a functionality is utilized with GA.
In classical sense segmentation is of 4 kinds:
1) Geographic
2) Demographic
3) Behavioral
4) Psychographic
1) Geographic: As the name suggests, we try to identify the group of people based upon their location. This can be extremely handy since people belonging to similar geography are expected to showcase similar traits. For example, people in North India are more probable to buy room warmers and air conditioners than people at the coastal regions, due to the extreme weather in North India.
Similarly many tourism websites showcase a background of beaches when people from non coastal region seems to be visiting the website, whereas when they are able to identify the visitors from coastal regions, they showcase pics of snow covered mountains in the background. All this definitely add up to the user experience and has resulted in significant boost in sales.
2) Demographic: When we classify our customers on the basis of gender, age, family life cycle (FLC), income and education. I am going to talk a little about FLC in detail, since rest all are pretty self explanatory. There are 8 basic groups within FLC where we identify our audience:
a) Bachelors: Young people, not living at home
b) Honeymooners: Young married people, no children
c) Full Nest I: Youngest child under 6
d) Full Nest II: Youngest child 6 or over
e) Full Nest III: Older married couples, with children living with them
f) Empty Nest I: Older married couple, no children living with them
g) Empty Nest II: Older married retired couple, no children living with them
h) Solitary Survival: As the name suggest, single older person, no children living with them
As you can imagine, depending upon the life stage a person is in, his/her requirements, purchase power, disposable income can differ a lot. As a marketeer we all do focus a lot on the customer life time value, but seldom do we put our efforts in knowing the customer life stage value. This is extremely important parameter to be understood before we create our targeting strategies.
3) Behavioral: We classify our customers on the basis of their attitude, knowledge, uses, and responses to the products and offers. As a web analyst, this is something we are extremely interested in, how people have reacted after seeing our mail, online banner, post, social media campaign etc. It's imperative for us to know how our customers in different groups react and understand our offers and products to identify our sales strategies for them.
We also utilize this information to educate our customers about usage of our products and/or services. Again as a marketeer, we all do understand that perceived value of our products is lot more important than it's actual value. Hence it becomes extremely important for us at times to educate our customers about they way how a product should be used before a customer starts using the product in a wrong way and then encounter issues only to form wrong perception about our products.
4) Psychographic: Also known as soft data, this was something extremely difficult to obtain. It's based on AIO, Activities, Interests and Opinions. Think about it this way, you may tell your bank whether you are married or not, but you will never tell them when are you getting married? What you think about a particular product? What you would like to do in your free time? But all this data is now available through social media. So, if as a marketeer you can engage with your customers/potential customers through social media, even you can get all this data to better understand your customers, and how and when would they be crossing their life stage.
Once you have understood these parts of segmentation, now in next post we will talk about how to create segments with Google Analytics and understand the behavior of our customers in these different segments.
In classical sense segmentation is of 4 kinds:
1) Geographic
2) Demographic
3) Behavioral
4) Psychographic
1) Geographic: As the name suggests, we try to identify the group of people based upon their location. This can be extremely handy since people belonging to similar geography are expected to showcase similar traits. For example, people in North India are more probable to buy room warmers and air conditioners than people at the coastal regions, due to the extreme weather in North India.
Similarly many tourism websites showcase a background of beaches when people from non coastal region seems to be visiting the website, whereas when they are able to identify the visitors from coastal regions, they showcase pics of snow covered mountains in the background. All this definitely add up to the user experience and has resulted in significant boost in sales.
2) Demographic: When we classify our customers on the basis of gender, age, family life cycle (FLC), income and education. I am going to talk a little about FLC in detail, since rest all are pretty self explanatory. There are 8 basic groups within FLC where we identify our audience:
a) Bachelors: Young people, not living at home
b) Honeymooners: Young married people, no children
c) Full Nest I: Youngest child under 6
d) Full Nest II: Youngest child 6 or over
e) Full Nest III: Older married couples, with children living with them
f) Empty Nest I: Older married couple, no children living with them
g) Empty Nest II: Older married retired couple, no children living with them
h) Solitary Survival: As the name suggest, single older person, no children living with them
As you can imagine, depending upon the life stage a person is in, his/her requirements, purchase power, disposable income can differ a lot. As a marketeer we all do focus a lot on the customer life time value, but seldom do we put our efforts in knowing the customer life stage value. This is extremely important parameter to be understood before we create our targeting strategies.
3) Behavioral: We classify our customers on the basis of their attitude, knowledge, uses, and responses to the products and offers. As a web analyst, this is something we are extremely interested in, how people have reacted after seeing our mail, online banner, post, social media campaign etc. It's imperative for us to know how our customers in different groups react and understand our offers and products to identify our sales strategies for them.
We also utilize this information to educate our customers about usage of our products and/or services. Again as a marketeer, we all do understand that perceived value of our products is lot more important than it's actual value. Hence it becomes extremely important for us at times to educate our customers about they way how a product should be used before a customer starts using the product in a wrong way and then encounter issues only to form wrong perception about our products.
4) Psychographic: Also known as soft data, this was something extremely difficult to obtain. It's based on AIO, Activities, Interests and Opinions. Think about it this way, you may tell your bank whether you are married or not, but you will never tell them when are you getting married? What you think about a particular product? What you would like to do in your free time? But all this data is now available through social media. So, if as a marketeer you can engage with your customers/potential customers through social media, even you can get all this data to better understand your customers, and how and when would they be crossing their life stage.
Once you have understood these parts of segmentation, now in next post we will talk about how to create segments with Google Analytics and understand the behavior of our customers in these different segments.
