Summary:
The State Changers' meeting revolved around optimizing a proof FTW WeWebb editor, mainly focusing on database disambiguation for company names and managing user input. A critical task faced is how to handle variations in company names, like Walmart, where users might type the name differently. The State Changers considered a pre-populated drop-down list of the top 3,000 public companies, but it appeared inefficient due to long load times. To manage the disambiguation problem, the State Changers proposed an initial approach where raw input data is gathered and analyzed to figure out what company a user might be referring to. The user input will be kept untouched, and a separate process will be implemented to identify the actual company from user input. They also emphasized building up a database of accurate employers over time, and at a certain point, subscribing to a database to import comprehensive company data to ease the process. Eventually, the aim is to provide a search engine-like experience where users can type in part of a company’s name and get accurate suggestions, potentially using XANO or Algolia for this feature. While no specific tool from the keyword list was discussed in-depth, the overall conversation was focused on architecting a workflow to collect, clean, and use company data more effectively. This discussion was valuable in shaping a strategy to handle company name variations and ensuring better data quality.
(Source: Office Hours 2/6 )
