What is the difference between Segmentation and Personalization?

What is the difference between segmentation and personalization? This is the question that came up during one of the webinar on personalization by Optimizely. This blog post is for those who have the same question.

Basic definition of Segmentation is  - division into separate parts or sections.  For the purpose of marketing, it is a processing of grouping customer and prospects into similar groups based on various criteria such as demographic, geo, behavioral and psychographics.  You can use one or more of such attributes to define your segment.  The purpose of segmentation is to understand about a group (segment), and develop marketing strategy to better target those segments. 

Personalization is providing marketing messages and/or experience that is tailored based on a customer’s needs or preferences.  Personalization can be very basic that can start from simply recognizing the person by name or it can be very complex that includes all sorts of data about a particular customer combined with device and contextual data (1st party data + 3rd party data). Personalization is the action that you take based on the learning you have about the person (a segment of 1 individual).

So segment is a way to understand your customer based while personalization is the action you can take based on that understanding.

Let’s look at very basic example to clarify these two terms:

You look at your site visitors and identify that there are two main behaviors of your visitors:

1.       Visitors who mainly click on sports related content, that’s where they spend most of their time

2.       People who mainly read finance related content, that’s where they spend most of their time.

Using this information, you have two segments – 1. Sports Visitors and 2. Finance Visitors 

This is called Segmentation

When someone who fall into “Sports” segment comes back to your site, you rearrange the content to highlight latest sports stories so that these visitors can easily discover the content they love.  On the other hand, a visitor who falls into “financial” segment will see finance stories highlighted.

This is called Personalization. 

Now this is not 1:1 personalization but it better than no personalization at all.

Hope this clarifies the difference between the two terms.  

Questions? Comments?

What does 1st, 2nd and 3rd party data mean?

1st, 2nd and 3rd Party Data Demystified

I have referred to 1st party and 3rd party data in a lot of blog posts. Based on the queries I get, both via email and in the classes I teach, it is time to clarify what various data sources mean.

1st Party Data

1st party data is the data that you (brand/publisher/retailer) have collected about your visitors, customers, shoppers etc. You own the data outright and all the rights to it. You can use it for any purpose you want based on the agreements with your visitors, customers, shoppers etc. as specified in your data collection and use policies. Some examples of 1st party data are:

• Site registration data – name, email, address, gender etc.
• Visitors behavior data on your site – time of visits, minutes spent, products looked at, source of visits etc.
• Shoppers/customers purchase data – products purchased, transaction amounts, coupons used etc.
• Email data – emails sent, opened, clicked etc.
• It is most widely used data for the marketing purposes. Generally, you use the 1st party data for customer retention using email marketing, retargeting and onsite personalization.

2nd Party Data

2nd party data is the data that is collected by some other company and shared with you(brand/publisher/retailer), in other words it is their first party data. A strategic data sharing partnership between two brands/publishers can help both of them grow their customer base and monetize that customer base.
You can generally use 2nd party data to:

1. Augment the data you already have about your customers (or visitors) – for example, if you do not collect “Household Income” during customer registration/signup data but have a need for that data you can partner with another brand that collects that data to get that data to enhance user profile. Another example is Google Adwords sending the keyword/campaign data to enhance behavioral data collected on the site.
2. Add a list of new customers – for example, if you are hotel booking site, you can have a partnership with airline to share information about customers who recently booked. If a customer books a flight, then you can use the data from partner to reach those customers and offer them hotels. Similarly, the airline partner can reach the customers who have booked hotel on your site.

3rd Party Data

3rd party data is the data collected and aggregated by someone other than the 1st party (data collector). In other words, the data aggregator doesn’t directly collect the data from customers/shoppers/visitors but have relationships with several companies/sources that collect the 1st party data. Some examples of the 3rd party data provider are BlueKai, Acxiom and i-behavior. These data providers aggregate the data from different sources to build a comprehensive profile of a customer/person. These enhanced profile let you understand a visitor/shopper more than what a 1st party or 2nd party data sets can provide.

For example, if you are a Financial institution, it will be very helpful for you to know which of your customers travel frequently, this will help you offer them a credit card that provides added travel rewards and benefits. This is where 3rd party data becomes useful that can provide such information based on data collected from various data sources such as hotel booking sites, airlines, location based data on several other places, other credit card providers etc

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CMOs: Three Major Roadblocks to Insights

Data is the raw material for developing insights. If the complete data is not available to insights team then you can’t expect the insights to be very valuable. Insights teams will make the best out of what they have available but you will get far better insights if you spend little time with them to understand what they need and help them with these for major roadblocks.

1. Data Sources and Collection – Insights team has identified the data sources required for them to provide great insights, the data is all there either available internally or externally. The big challenges comes when the data teams actually start to figure out how the data will be collected. For internal data sources the organizational barriers are the biggest ones that prevent one team for getting access to the data that other team owns. Your team will need your help in navigating those barriers and help the free flow of the data. If external data sources are on their list then your help will be needed to provide appropriate funding and legal clearance needed to get those data pieces.
2. Data Storage – Storage per GB/TB is cheap and will continue to be cheaper but with that the amount of data will continue to go up (see the graph below) All in all, you will end up either spending a lot of money or will need to clear out the data repository to keep cost in check. Clearing the data means data gaps will emerge causing the gaps in Insights. For example, if all your data team can store is six months’ worth of data then you will be missing out on yearly trends, If all they can store for 1 year then you will be missing out on multi-year trends etc. Your team will need your support in ensuring that you have appropriate budgets approved to ensure that your team can store the required amount for their analysis.

Source: http://www.eweek.com/c/a/Data-Storage/Storage-Management-10-Business-Factors-That-Will-Impact-IT-Pros-in-2012-181588

3. Data Access – Having all the data collected and stored is half the battle, other half is making sure that the data is accessible by the insights team. Majority of the time the data will be stored in the cloud, Hadoop etc but is not easily available to the analysts who will need it for their analysis. In order to make any sense of the data, the insights team needs to have easy access to the data, not just in little chunks but to the whole set. You analysts might not be well versed with database technologies to make proper connection. They need an easy way to either connect their analysis tool e.g. Tableau, Excel etc. to the data sources so they can pull the required data to conduct analysis. They will need your help in pushing the other teams to make data accessible to them.

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Facebook lost my Email Notification settings

I got an email this morning from Facebook that they have lost my email notification settings. I did not believe that email, I thought it was a phishing email. I checked the url in the email and it seemed valid but for some reason I still could not believe it. “How can Facebook lose my email notifications? Not possible” I thought.




I logged into Facebook and found the same message on the home page. So, the email was legit and Facebook had indeed lost my email preferences.



It is very concerning to me. How can a company like Facebook lose data? Millions of people put a lot of data on Facebook and how can Facebook not keep proper safeguard to make sure data does not get lost and proper backups to restore the data. It is not clear if a programming error or human error cleared all the data or did somebody break into the database/file system and cleared it out. I am not sure if it was just me or others got affected as well?

Did you receive similar message from Facebook?

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Technical Consultant for Internet Marketing and Web Analytics at Unica (Waltham, MA)