Cookies help us display personalized product recommendations and ensure you have great shopping experience.

By using this site, you agree to the Privacy Policy and Terms of Use.
Accept
SmartData CollectiveSmartData Collective
  • Analytics
    AnalyticsShow More
    warehouse accidents
    Data Analytics and the Future of Warehouse Safety
    10 Min Read
    stock investing and data analytics
    How Data Analytics Supports Smarter Stock Trading Strategies
    4 Min Read
    predictive analytics risk management
    How Predictive Analytics Is Redefining Risk Management Across Industries
    7 Min Read
    data analytics and gold trading
    Data Analytics and the New Era of Gold Trading
    9 Min Read
    composable analytics
    How Composable Analytics Unlocks Modular Agility for Data Teams
    9 Min Read
  • Big Data
  • BI
  • Exclusive
  • IT
  • Marketing
  • Software
Search
© 2008-25 SmartData Collective. All Rights Reserved.
Reading: “MySpace is the Bar, Facebook the Backyard BBQ, and LinkedIn the Office”
Share
Notification
Font ResizerAa
SmartData CollectiveSmartData Collective
Font ResizerAa
Search
  • About
  • Help
  • Privacy
Follow US
© 2008-23 SmartData Collective. All Rights Reserved.
SmartData Collective > Uncategorized > “MySpace is the Bar, Facebook the Backyard BBQ, and LinkedIn the Office”
Uncategorized

“MySpace is the Bar, Facebook the Backyard BBQ, and LinkedIn the Office”

TomAnderson
TomAnderson
4 Min Read
SHARE

Posting a brief follow up to yesterdays post.

Just got back from the MRANE event. Right after my talk which ended on some of the work we’ve been doing with Social Network Research, John from LinkedIn spoke about using  LinkedIn for B-B Sample. He mentioned how LinkedIn sample has helped their clients “cut down on the sample sizes through micro targeting”.

I thought this was rather interesting. Depending on the client, very little is known about sample size. I have clients who are perfectly happy with n=250, and some that want n=2500 for the same type of project. Many companies usually have no problems with selling more sample and charging more. I prefer to add value in design and analysis.

More Read

Image
3 Big Data Companies That Together Made $1 Billion Last Year
The MalStone Benchmark, TeraSort and Clouds For Data Intensive Computing
Social Media: Making It Measure Up
The General Theory of Data Quality
What Could IBM’s Watson Do for Your Organisation?

LinkedIn however is also very careful about sample size, because they don’t want to spam their user base with surveys. Better to sell less sample with higher margins right.

Many marketers are used to working with larger sample sizes than they need, building the sampling lan from top up rather than bottom down. LinkedIn asks clients to stop and think about it for a moment. The client is going to get to talk with VP’s at 1,000 large companies. Do they really need 1,000? According to John, some clients…

Posting a brief follow up to yesterdays post.

Just got back from the MRANE event. Right after my talk which ended on some of the work we’ve been doing with Social Network Research, John from LinkedIn spoke about using  LinkedIn for B-B Sample. He mentioned how LinkedIn sample has helped their clients “cut down on the sample sizes through micro targeting”.

I thought this was rather interesting. Depending on the client, very little is known about sample size. I have clients who are perfectly happy with n=250, and some that want n=2500 for the same type of project. Many companies usually have no problems with selling more sample and charging more. I prefer to add value in design and analysis.

LinkedIn however is also very careful about sample size, because they don’t want to spam their user base with surveys. Better to sell less sample with higher margins right.

Many marketers are used to working with larger sample sizes than they need, building the sampling lan from top up rather than bottom down. LinkedIn asks clients to stop and think about it for a moment. The client is going to get to talk with VP’s at 1,000 large companies. Do they really need 1,000? According to John, some clients are accustomed to purge as much as 30% of the sample as bad (speeders etc.). While this %age sounds a little extreme to me, I do agree, that sample sizes are sometimes bigger than they actually need to be. If the client can be assured that the sample is of high quality, this may be an easier argument for smaller sample sizes than a statistical or even a cost argument.

Finally, one other thing I found interesting from John’s talk was how LinkedIn views themselves vis-à-vis the other networks (MySpace and Facebook). They see “MySpace as the Bar, LinkedIn as the Office, and Facebook as the Backyard BBQ”. Interesting way of looking at it. We’re currently doing quite a bit of research on social media. I’ll check with some of my contacts at MySpace and Facebook to see if they have similar ways of thinking about the competition?

Tom 


Link to original postTom H. C. Anderson – Anderson Analytics

TAGGED:market researchsocial mediasocial network analysis
Share This Article
Facebook Pinterest LinkedIn
Share

Follow us on Facebook

Latest News

Diverse Research Datasets
The 5 Best Platforms Offering the Most Diverse Research Datasets in 2026
Big Data Exclusive
macro intelligence and ai
How Permutable AI is Advancing Macro Intelligence for Complex Global Markets
Artificial Intelligence Exclusive
warehouse accidents
Data Analytics and the Future of Warehouse Safety
Analytics Commentary Exclusive
stock investing and data analytics
How Data Analytics Supports Smarter Stock Trading Strategies
Analytics Exclusive

Stay Connected

1.2KFollowersLike
33.7KFollowersFollow
222FollowersPin

You Might also Like

big data for social media
AnalyticsBig DataExclusiveSocial Data

5 Tools That Use Big Data For Social Media Optimization

7 Min Read

#4: Here’s a thought…

9 Min Read

Stop Calling Social Analytics Intelligence

5 Min Read
big data and client communication
Big DataExclusive

4 Ways Big Data And Client Communication Technology Help Companies

6 Min Read

SmartData Collective is one of the largest & trusted community covering technical content about Big Data, BI, Cloud, Analytics, Artificial Intelligence, IoT & more.

ai chatbot
The Art of Conversation: Enhancing Chatbots with Advanced AI Prompts
Chatbots
ai in ecommerce
Artificial Intelligence for eCommerce: A Closer Look
Artificial Intelligence

Quick Link

  • About
  • Contact
  • Privacy
Follow US
© 2008-25 SmartData Collective. All Rights Reserved.
Go to mobile version
Welcome Back!

Sign in to your account

Username or Email Address
Password

Lost your password?