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July 20, 2022
Text data can offer invaluable insight into a company’s performance.
Numbers, charts, and graphs can help business leaders understand what is happening within their organisations, Yet these often fail to capture the true drivers of successes and shortcomings on their own. Fortunately, survey data, social media, reviews, and customer service text data offer an additional, contextual layer that supports a robust, holistic understanding of a company’s performance.
Given a number of trends that are driving an increase in text analytics adoption, this kind of data will be the future of business intelligence.
Businesses are constantly presented with an overflow of information that can be difficult to manage, process, and evaluate at scale. With consumer data flooding in from all directions, much of this is text-based.
Survey open-ends and transcripts, conversation data captured in contact centers, interviews and focus groups, online reviews and social media conversations…all of this qualitative text data can – and should – have a strategic influence on brand strategy, product development, customer care, marketing, communications, and more. Some of this data is real-time and extremely valuable in helping to boost true understanding of exactly how customers feel. But it can be used only if brands and insights professionals have efficient, robust ways to analyse it.
Most researchers and analysts use some form of text analysis, and are familiar with the ensuing ‘word clouds’ and sentiment graphs. Yet these tend only to surface rudimentary, obvious, or unactionable insights based on keyword frequency; with static reports which fail to help people stay on top of trends.
These challenges aren’t restricted to one industry or sector, either. From consumer goods to retail, insurance, and higher education, we’re seeing these trends take hold across the board. This proves how crucial it is for companies to dig into open data sources and efficiently surface actionable insights in order to remain competitive in an increasingly fast-paced environment.
Many insights professionals set out on a research initiative looking for a specific data point or hoping to solve a specific business problem. As they begin to analyse and understand the insights contained in the data they gather more fully, there’s often an opportunity apply these findings to other data sources, business questions, and functional areas. This is another key business intelligence trend that looks set to accelerate.
Let’s look at an example of an organisation that wishes to generate customer service insights from their contact centre call transcripts. In the analysis process, it realises that these transcripts also contain a host of insights that can be leveraged to inform product development.
In this way, a single data source can generate continual insights to support different functions. In doing so, the organisation increases the value it is getting from its data. Rather than data being siloed and analysed for a single purpose, businesses can release the potential of customer-driven insights and collaborate with other departments. Similarly, the approach used to generate competitor intelligence may also prove useful for generating local market insights for global companies.
Access to third-party data is becoming more and more restricted. In a privacy-centric world, consumers are getting increasingly empowered to make their own decisions about their own data. As privacy regulations become more stringent and third-party cookie deprecation comes into effect, companies will need to do more primary research in order to develop and maintain a robust understanding of their audiences.
There’s no doubt, either, that the volume of first-party data is rising. Today, growing numbers of insights professionals are seeking to analyse this data and uncover its business value. When companies are thinking about who their customers are and how their behaviour is changing, there is no doubt that first-party data is invaluable.
It’s important that businesses are tactical about how they seek out and collect first-party data. Open-ended survey questions should be crafted carefully to answer specific business questions or problems. By gathering data that is full of relevant customer insights, and using innovative solutions to analyse it, organisations will benefit from primary research. They’ll be able to reap the rewards of relevant, and sophisticated, business intelligence.
Today, the challenges of analysing text data alongside the mounting realisation of its strategic importance are driving growth in the text analytics market. Alongside the pressing need for innovative solutions that allow companies to get the full value out of all their text-based data sources, knowing how to find unique insights and make the most of data assets has never been more important.
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The views, opinions, data, and methodologies expressed above are those of the contributor(s) and do not necessarily reflect or represent the official policies, positions, or beliefs of Greenbook.
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