How can you set up a more efficient information analysis process?

Information managers face challenges in collecting, analyzing and disseminating information. This process can be optimized using intelligence tools. The development of automated mechanisms and AI-based analysis supports saves valuable time for the core business of business intelligence: data analysis.

Automating information gathering and source identification

Market intelligence officers face several challenges when it comes to data collection. The first is the source of the data itself and the way to identify new sources. Because information managers cannot afford to miss out on information that is crucial to the company! That is why it is important to have several effective tools to reduce this uncertainty in a constantly changing environment. Information and data are generally acquired through two types of channels: known sources on the one hand, and unknown sources on the other hand.

Cikisi meets these challenges, first by collecting information from known sources: online newspapers, specialized databases, competitor news, product magazines or financial reports, for instance. At the same time, the SaaS software also collects data from unknown or unidentified sources.

When you enter your monitoring topic into the platform, it will launch an automatic daily scan of the visible web and the deep web. Structured information will be retrieved from these searches every day so that you never miss information that is crucial to your decision-making. This process allows you to discover new sources, but also to retrieve information that is not indexed by public browsers (such as Google, Qwant, Yahoo, Bing…).

The monitoring officers then have all this information at their disposal through their search and analysis engine. The information is enriched with new data, and is also structured and capitalized so that you can communicate and analyze it in more detail.

Data enrichment for business intelligence

The second challenge facing business intelligence managers is the categorization of information.

The Cikisi platform offers automatic and customizable modules that automatically enrich all information with new data.

• The artificial intelligence (AI) and machine learning (ML) features of the SaaS software help classify information by analyzing and structuring it through automatic detection of named entities (name, organization, country, date…).
  
  
• You can also customize the enrichment of your data on your monitoring topics or core business. This is possible thanks to the IXXO thesaurus, which is integrated into Cikisi. It enables the development of a structured and hierarchical directory of terms for content analysis and multi-level document classification.
  
  

Data visualization modules allow you to make this data more visual through dynamic dashboards and relational mapping.

Data visualization for analyzing and communicating data

Two other important challenges for the market intelligence managers are: how to analyze their corpus of information more quickly? and how to make it readable for their various communities?

The Cikisi software platform offers various modules to make reading information faster and to create customized deliverables. Once the data has been enriched, it is easier to produce graphs representing market trends and status. This contextual information attached to the document corpus can then be used to generate high-quality reports and visuals.

• Dynamic dashboards allow you to navigate your data graphically and intuitively. It is also possible to cross-reference business information with companies, technologies, locations. The graphs and associated data can be easily downloaded to customize your deliverables and disseminate information to different groups of readers.
  
  
• Relational mapping graphically links technologies, actors and domains. It facilitates the visualization of entity relationships, trend authentication and weak signals. There are many advantages to consider, including its dissemination and intuitive visibility.
  
  
• The Clustering Algorithm is useful for partitioning a large document corpus into homogeneous data subsets. Information managers can then understand the trends in their monitoring and filter the results obtained.
  
  

This set of features allows data to be put into perspective to obtain a more qualified set of information. The process of disseminating and delivering the right information to the right people can then begin. Collaborative monitoring can follow an iterative process involving business experts (analysts, researchers…) in data qualification.

Collaborative and iterative monitoring

A strategic intelligence system is a decisive organizational element that facilitates decision-making within the company and stimulates innovation. It must be structured around monitoring needs by combining the business expertise and informational skills of the analysts. The Cikisi platform is a powerful and flexible intelligence tool that adapts to each monitoring project and facilitates its collaborative nature.

This means that the dissemination of information within the organization can be fully or partially automated. The monitoring unit can choose to disseminate information in a targeted manner, leaving it to the choice of the monitoring officers.

All of the platform’s tools enable the alignment of monitoring needs and resources in order to optimize data analysis and thus provide a set of more accurate and better qualified information.

Want to discover the tool?