Nielsen Word Cloud 

Data Visualization

Concept · A Tool to Aid Audience Participation & Conversation

Nielsen hosts an annual conference, Consumer 360, to discuss the rapidly changing landscapes of media, retail, tech, and more.

Nielsen requested a tool to facilitate the aggregation of ideas during different panel discussions and to visualize these ideas in a live word cloud accessible on a url.

Real results from over 90 participants


  • MongoDB
  • Express
  • Angular
  • Node.js
  • D3.js

Challenge · Creating a algorithm to parse entries appropriately

The algorithm takes any entry (ie, a word or a phrase) and inserts unique words into MongoDB once, while increasing the count of repeat words. The count of each word then corresponds to the font-size of each word rendered in the word cloud through D3. Upon inserting each unique word, the algorithm gives it a unique color based on Nielsen branding.

Example API route of MongoDB JSON data:

Final Product

The algorithm parses the individual entries and creates a local JSON object to keep track of unique words within a given entry.

Then this JSON object is compared with the database to check if any of the words in this entry already exist in the database. If so, the algorithm marks the repeated word as a match in the database and increases its count value by one. If any of the words in the new entry are new, the algorithm markes them as a non-matched word and creates a new database entry for the new word. 

On the front-end, D3 accesses the word cloud data via an exposed api route and renders the appropriate word cloud.

Nielsen Word Cloud Github Repository

Parse Entry

Update Database