Big Data solutions for market intelligence for a B2B company
Holecz, Vivien (2017)
Haaga-Helia ammattikorkeakoulu
2017
Creative Commons Attribution 3.0 Unported
Julkaisun pysyvä osoite on
https://urn.fi/URN:NBN:fi:amk-2017120119247
https://urn.fi/URN:NBN:fi:amk-2017120119247
Tiivistelmä
Being part of the Big Data – Big Business project of HAAGA-Helia, University of Eastern Finland, VTT Technological Research Center and a handful of companies, the aim of the report was to create suggestions for improving one of the participating firms’ market information collection. The objectives were complex. In addition to gaining better understanding of Big Data and relevant technological solutions, the target company’s development areas were also researched. Furthermore, the feasibility of a custom solution was investigated too.
The research was conducted as constructive research. The three different parts used separate methodologies. First, a questionnaire was conducted to learn about the company’s practices and needs, while also examining the current market intelligence solution they are using. Second, a market research was carried out, aiming at finding relevant open source
and commercial software in the areas of lead generation, social media and competitor intelligence. Third, a proof of concept was created to gain experiences and insights about open source Big Data applications and offer suggestions related to acquiring custom built or commercial market intelligence solutions.
The research revealed, that the most promising improvements can be reached in the area of lead generation, considering both commercial and open source software. The findings of the proof of concept are two-fold: it showed that a whole application can be built exclusively from open source tools, such as Python libraries and Apache Spark, to extract information from Twitter, a freely available data source. Furthermore, twitter proved to be interesting, because there is relevant industry data shared there.
The report concludes that there is business potential in seeking out Big Data solutions to solve the problem of collecting timely market insights. However, it is important to keep in mind that it takes a lot of effort to extract relevant information due to the complex challenges of analysing vast amounts of unstructured data.
The research was conducted as constructive research. The three different parts used separate methodologies. First, a questionnaire was conducted to learn about the company’s practices and needs, while also examining the current market intelligence solution they are using. Second, a market research was carried out, aiming at finding relevant open source
and commercial software in the areas of lead generation, social media and competitor intelligence. Third, a proof of concept was created to gain experiences and insights about open source Big Data applications and offer suggestions related to acquiring custom built or commercial market intelligence solutions.
The research revealed, that the most promising improvements can be reached in the area of lead generation, considering both commercial and open source software. The findings of the proof of concept are two-fold: it showed that a whole application can be built exclusively from open source tools, such as Python libraries and Apache Spark, to extract information from Twitter, a freely available data source. Furthermore, twitter proved to be interesting, because there is relevant industry data shared there.
The report concludes that there is business potential in seeking out Big Data solutions to solve the problem of collecting timely market insights. However, it is important to keep in mind that it takes a lot of effort to extract relevant information due to the complex challenges of analysing vast amounts of unstructured data.