21 Feb Few ways even Linkedin can improve by knowing and quantifying its users digital experience satisfaction

Author – Dr. Srinivas Kilambi,  Founder & CEO, Sriya DXI, LLC

Let me start this article by complementing LiN on creating and making available for free a great product for professionals, a truly tremendous collaboration platform. This explains their great blowout quarter financially and healthy stock price. Congrats from a great fan.

However, even LiN, can improve a lot by measuring and quantifying its user’s digital experience satisfaction (DX) and then implementing some of the recommendations to improve this DX.

Some of the recent or not so recent changes of LiN which have reduced my DX satisfaction are:

  1. Changes to the LiN messaging. It is nicer and a simpler interface and allows subject thread based conversations to be grouped. That is great but they have made the process of archiving a message, finding and retrieving a deleted message very tedious. Recently, I deleted a conversation by mistake and took me a while to figure out how to retrieve it. In the prior version, LiN had trash messages in a folder which could easily be viewed and deleted messages retrieved.
  2. Addition and deletion of members to messaging: While addition of members to a conversation is easy, sometimes LiN adds a member even before I have fully entered the name by matching the first few letters. This may prove both a boon or a bane depending upon whether a right or wrong person was entered. Now if a wrong person was entered by mistake then deleting that person is much more non intuitive.
  3. Knowing the number of your contacts. I may be dumb but now I am not able to see how many contacts I have as easily i could do before. It is lot more tedious. Also, why does LiN stop with 500+ contacts? Why cannot they show 1000+, 2000+ etc so that people who are very connected get greater credit and recognition is my humble suggestion.

I am sure many others have similar set of experiences which they would like LiN to adopt and improve and this will make LiN a better product and help LiN and their millions of users to have a better Digital Experience Satisfaction.

One way to do this is to explicitly measure this DX satisfaction because what is not measured cannot be improved. Next this measurement can be quantified into a set of easy to understand scores or benchmark indices for correct  DX comparisons and improvement.

I am sure LiN is doing surveys to measure DX and may then even quantify this into a score/index. LiN may also be using analytics tools to measure and analyze DX. Both are great techniques with some limitations (IMHO). Surveys have a very low fulfillment rate and are very biased or skewed while traditional analytics tools are good at data visualization and understanding data trends but they lack the ability to analyze multiple parameters at a time or simultaneously and see hidden patterns.  Sometimes looking at dozens of parameters and analyzing them maybe more confusing and detrimental than not analyzing at all as wrong analysis or solution is worse than no analysis or no solution.

Using quantitative math-stat techniques to measure and quantify DX for better understanding and comparison and then use machine learning to see hidden patterns and analyze multiple parameters simultaneously for DX improvement may be a solution. Maybe LIN is already doing that.

In the end, these flaws are a minor aberrations which can easily be rectified by this great successful product. Kudos to LiN and their team of scientists.

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