Contextual Data Analytics - An Important Tool For Understanding Market Behaviour

Data is an asset for any business house or company but interpreting it is furthermore vital to understand market behaviour and trends. Contextual Data analysis throws light on the pattern of consumer behaviour, demographic evaluation, demands and more. An insight into the data and right interpretation can lead a company to the best position ever. This data can be derived from customer interactions, social media, weather, news, broader market changes, internet of things (IoT) devices, geography, etal.

Benefits of Contextual Data Analytics -

Contextual data and its interpretation can improve the customer experience strategy by analysing information and implementing the needed strategy. This data gives a wider outlook to improve, change or subtract any existing marketing technique vital to boost sales. Therefore, this will help in the decision-making ability of a company and improve customer interaction-level experiences.

There are mainly three sources of Contextual data collection -

1. Third-party businesses/organisations

Third-party organisations or business houses take up the responsibility to dig in data necessary for the business to grow. Marketing strategy depends largely on the data that shows the consumer behaviour and dynamic changes in the market. These third-party agencies use different tools to extract business information vital to that business. News, weather report, events, market changes, traffic et al can be source for contextual data analysis.

2. Customers or Consumers

Consumers are the biggest source for any kind of market-related data. They directly can share their demands, wishes or most important choices. Their behaviour can be recorded online through social media activity, feedback form, survey reports, location, preferences, and the option goes on.

3. Tools

Different tools are useful in extracting contextual data vital to the development of the business like GPS tracker, asset and inventory management sensors, context-aware promotional tools and more.

The business development or growth depends largely on the statistics derived necessary to analyse the trend and changes in the market. This can help the business house to take the necessary action needed to adapt to the market situation. Go for contextual data to understand market trends deeply, as this will immensely help in strategising decisions as per the situation and improve sales manifold.

Best 7 Deep Data Analysis Tools

In modern times, with digitalization across the globe data is the biggest asset for any company. Deep data means a chunk of high-quality data that is relevant and actionable. This ‘data’ answers and solves problems. Such huge data are always difficult and time-consuming to filter manually as per the need hence many tools help in analyzing deep data. Let us talk about the best 10 analysis tools for managing ‘deep data’.

1. Xplenty – It is a cloud-based ETL solution that analyses, manages, and transforms high-volume data without coding resources in few minutes. It is ideal for businesses with high volume data as this not only manages such nig data in minutes but also manages effectively without any error. This is a complete data analysis toolkit.

2. Zoho Analytics – Zoho Analytics operates on Windows, Mac, Linux, Android, iOS, and cloud. This is an Indian-based company, dedicated to offering solutions to data management for companies and business houses. There is a free plan; however, the basic plan starts at $22 per month.

3. Sprinkle – It is a cloud-based solution that helps with reports, segments, and dashboards with much ease. It is user-friendly as this does not call for high intelligence while operating it.

4. Hubspot – This software company helps in analyzing data, generating leads, marketing automation, and more. With the purpose to help the business houses grow, this company has a revolutionary inbound marketing technique. Its price starts from $40 per month.

5. Tableau Public – This is a free platform to share and visualize data online. With data visualizations, this platform makes data a part of everyday life. The features are good and with full functionality.

6. Rapid Miner – With an easy system and powerful GUI, this software is a data science platform that helps organization drives revenue, reduce costs and avoid risks. It concentrates on people, performance, and productivity.

7. KNIME – This software platform is free, open-source software for creating data science. It access, merge and transform data to derive solutions to business problems. It supports enterprise-wide data science practices and gives insights into the results derived.