How To Leverage Machine Learning And AI For Market Landscape Analysis

Market landscape involves the broad mapping of various players in a specific industry, segment or geography with characteristics like business health, drawbacks and opportunities. Market landscape analysis helps to understand competition and create broad business strategies using specific business insights. 

 

Why and when to use market landscape analysis?

Market landscape analysis gives a wide canvas for brands, so the boundaries have to be defined and purpose driven. For example, it involves the mapping of existing players in a segment, competitor’s strengths and weaknesses, demographics targeted etc. The availability of tons of data helps to understand where a brand stands vis-à-vis competitors.

With such an analysis, making data driven decisions which are in sync with business objectives and emerging trends becomes easy. It allows organizations to build holistic go to market strategies or leverage on gaps left unexplored by competitors.  

The process of mapping various characteristics is useful when considering significant expansion or planning for diversification from core business. Market landscape analysis helps in building a superior strategic plan apart from playing a key part of setting up a collective impact collaboration.

 

Traditional approach to market landscape analysis

Traditional approach to market landscape analysis involves a combination of qualitative and quantitative techniques to understand size of the market, needs of the consumer and competition in the market. 

Qualitative research involves ethnographic study, focus group discussions, in-depth interviews etc whereas, quantitative research involves survey and statistical analysis of secondary data. Such a research project is considered to be time consuming and the sample size plays an important role in defining the accuracy of resultant insights.

The time consumed by similar research projects are very high thus, the chances of missing newer trends with rapidly changing technological landscape might arise. To mitigate such unforeseen risks, we at Setuserv have created a platform which helps in being dynamic with your market landscape analysis, the platform is called CRIS. It uses customized machine learning algorithms as per requirement of a brand to ensure actionable insights are mined.

 

CRIS Platform: Dynamic approach to market landscape analysis

The market landscape module of CRIS platform augments traditional approach of analyzing data with a specialized machine learning algorithm. The algorithm helps analyze data at granular level and gives easy to understand information about:

 

  • Share of Voice
  • Ratings of specific brands and their products
  • Customer sentiments
  • Trending Brands

 

Market landscape

 

The above diagram depicts the data from the health, household and wellness segment. 

Advantages of CRIS platform

CRIS platform is robust and allows to capture accurate insights by mining data about new entrants without dislodging existing information. Gathering similar data helps in effective competitive bench-marking.

The platform’s true potential is in ability to take more structures of data, this helps it to be scalable. i.e. The brands have their own proprietary data can be interlace with existing data being mined by the platform thus, creating highly customized and brand specific solutions. 

By combining the specificity of human intelligence which understands the emotional aspects of consumers with data mined from the abundant unstructured data using AI algorithms you have a strategy which is validated using data. This approach helps increase the confidence in actions taken as the insights of the human brain are validated through data from artificial intelligence.