Insights on lead generation through trend analysis.

The Business Need

A Japanese multinational manufacturer of extreme sports equipment requested a process for generating insights on upcoming and current trends in the bicycle industry. They wanted to identify sources that can provide information on trends such as customer preferences, sales by geography, competitor analysis, etc.

The insights generated need to be relevant to the market segments and the components/ sectors served by the brand. These included bicycle components, fishing tackles, and rowing equipment.

Challenges we faced

Through vigilant examination, Mobius spotted the goals that were needed and identified the limitations challenging the process. We had to begin monitoring patterns of trends/ activities on social media platforms which were indicators of the amount of activity/ interest that was being generated on a particular entity. This was a highly mindful task as we needed to find a way to filter out the searches.

We approached the problem statement by first listing out the most popular social networking sites, sorted them in order of a number of users and activity.

How we solved the problem

Annual reports of more than 1000 companies with entity names and year of the report were given by the client. Previous year details were also provided to make the necessary calculations.

We identified base data like company’s zip code, telephone number, address, branch, C-suite details, parent-subsidiary companies, subsidiary, debt, balance sheet information and extracted. Performance ratio indicators were then expertly calculated.

The captured financial data from the annual reports and statements were consequently made available in a web application so that the populated data can then be validated by the client along with the previous year’s USD value & local currency value using an automated component.

Once their validation process was done, the financial records that were generated by the analysts were sent for QC approval, and the signed-off data received from QC were updated in their system.

A machine learning solution was built that intelligently identified tables and sections within the reports were critical financial data was located. The output was projected on our homegrown Mojo tool that helped human intelligence to be added to the ML output and improved accuracy.


We implemented an eight-step process that involved the following phases

  • Identify the social media that needed to be monitored based on popularity, relevance, number of users in the geography, and other criteria
  • Identify the third party aggregator tools most suited to monitor, analyze and generate insights from across the various social media platforms
  • Configure the tools based on the requirement such as the frequency of reporting, geography to monitor, keyword(s), other tool-specific configurations
  • Obtain output/reports generated from the third party aggregator tools
  • Identify consistency in trends/variables observed from across those tools
  • Record observations of trends/patterns from the output obtained in the most suitable format- as text, graphics, etc
  • Identify the overall structure of the report, based on available data and the possibility of linking data from across tools to build a bigger picture
  • Generate a report of observations, trends, and predictions


Upon integrating our trend analysis tools with the popular social media handles, the comprehensive process efficiency took a stirring improvement.

We were able to generate demographically accurate reports of observations, trends, and predictions in the bicycle industry. As a result, the brand was able to reap profits through well-informed business decisions.

Scraping data from sites

Using tools to analyze social media signals

Mobius employed two approaches simultaneously to generate the report

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