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market intelligence and discovery

Market intelligence

Market Intelligence describes the set of activities that provide a company with a view of a market using existing sources of information to understand what is happening in a market place, what the issues are, what competitors are doing, what customers or consumers are doing (eg social media) and what the likely market potential is for new products or services based on previous activities and responses. Existing sources of data include published reports, online data sources, journals, social media monitoring and internal data such as CRM or web journeys.

Public source data gathering

 

Market intelligence from external data is normally gathered by looking at secondary information sources. Often this means sourcing and analysing published information to build a picture of a market and to try and answer some specific commercial questions such as what is the market potential, what are competitors future plans likely to be, what prices might customers be willing to pay, what's the best means of entering a market.

Central to successful desk research is the ability to track down sources of information and to provide a skilled analysis to read the data and identify not just the data, but the story behind the data, for instance the ability to interpret financial reports or understand web metrics. Analysts may use automated tools such as web-spiders or scrapers to set up alerts or monitors that can be delivered via a dashboard or into newsletters.

 

Competitor intelligence

Competitive Intelligence

A specific form of Market Intelligence is competitive intelligence. This is typically undertaken on an on-going basis, often on an automated or semi-automated basis, and involves the collection of news, materials and other information about competitors from a wide variety of open sources. Examples might include collecting price-check information, or details of promotional and advertising campaigns, or monitoring news channels for information about new products or new technologies (eg patents). Competitive intelligence can also use primary sources of data, such as feedback from sales teams, suppliers or distribution channels. In analysis, the aim is to paint a picture of competitor strengths and weaknesses and opportunities and threats.

For legal and ethical reasons, the competitor research we carry out relies on open public data and we will not carry out competitor research that misrepresents who we are, or is otherwise unethical.

 


Online opinion and behaviour tracking

Monitoring opinions from social media

Social media monitoring is used to understand trending issues, to monitor customer sentiment and to provide an early warning system for issues affecting customers. Done well, it will also identify new opportunities and ideas - outliers and black swans - that also appear in social media feeds.

 


Data analysis and Big Data analytics

Data Science and analysis of Big Data

While much marketing intelligence is associated with collecting information externally, a great deal of insight can come from making better use of existing information. Companies have large stores of information available from web, CRM and sales databases that can be mined for insights to identify customer segments, purchase drivers and sales opportunities. We use statistical tools and data science approaches to investigating internal data and can combine this with research (why...) and experiments (what if...).


For help and advice on carrying out any market intelligence projects on-line or off-line contact info@dobney.com

 

Databases, data analysis and visualisation

Resources, tools and approaches for data analysis across different types of datasets, including our SpaceMap interactive data visualisation and analysis technologies.

Market and competitor intelligence resources

Articles and resources about collecting, analysing and using market intelligence and competitor intelligence from data sources, to data storage and sharing information in the business.

Customer knowledge resources

Articles about customer knowledge and pooling and blending data about customers into a generalised customer knowledge systems including tools, software, approaches and issues.


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