Text Analysis in Excel: Real world use-cases Text Analysis in Excel: Real world use-cases
Last month, we launched an Excel add-in, a solution for using ParallelDots NLP APIs to do text analysis on unstructured data without... Text Analysis in Excel: Real world use-cases

Last month, we launched an Excel add-in, a solution for using ParallelDots NLP APIs to do text analysis on unstructured data without writing a single line of code. The Excel add-in is very easy to use and provides a convenient, yet effective solution for your text analysis needs. In an earlier post, we provided you with detailed information of how the excel add-in works. In this post, we will discuss some real-world use cases where you can use the Excel Add-in to raise your analytics game without spending a fortune on building a data science team.

Text analysis on product reviews from E-commerce sites, Facebook Pages and other review sites

You can analyze a corpus of customer reviews to understand the general impression about your product. The Excel add-in works on ParallelDots AI APIs, which are being used extensively by developers and enterprises to empower their analytics since the last two years.

Excel Text Analysis

Furthermore, you can run keyword analysis on positive and negative sentiment sentences to discover why people like or dislike your product. Such an analysis will enable you to understand the key phrases contributing to the overall sentiment around your product. For example, a phone manufacturer company can analyze reviews from e-commerce sites, social media, and tech review blogs for their models. They can then extract keywords for both positive and negative sentiment sentences to find which features (screen, battery life, camera, storage, etc.) users liked or disliked  about a particular phone model.

Additionally, you can go a level deeper by analyzing the intent of the product reviews and categorize them to identify whether the review counts as the feedback, opinion, query or spam. This will help in filtering essential reviews and replying/acting on them faster.

The analyzed data, i.e. sentiment, keywords and intent, can be correlated with your internal business metrics such as marketing spends, sales data etc. to find actionable insights.

Analyse open-ended user feedback from surveys

Open-ended feedback forms have proven to be more useful than close-ended ones (Folks at our market research division, Karna AI, have written a extensive blog on analyzing open-ended user surveys. You can read it here) but analyzing them can be very time-consuming and expensive task.

Our Excel Add-in is a lifesaver when it comes to analyzing open-ended surveys. Once you have exported all the survey responses in xlsx or csv format and installed the add-in, you can start analyzing the responses straight away without writing a single line of code. The Excel add-in makes it simple for anyone and everyone to perform AI-powered text analysis.

Excel Text Analysis
A sample response of an open ended survey and analyzing sentiment of keywords.

Methodology can be same as the one mentioned in the product reviews analysis, and you can incorporate entity extraction function along with keyword analysis to discover broader entities (product name, person name etc.) talked about in the surveys.

Text Analysis for financial content

Financial data such as earnings call, news articles, transcripts etc. contain lot of rich information which can form basis for your fundamental investment and financial research. The BFSI sector is heavily equipped with textual data.

Excel Text Analysis
Analysing financial data

Since excel remains an integral part of any financial analyst’s toolkit, this Excel add-in can help to correlate many of the structured data points found in financial documents (balance sheets, trading history, P&L statements) with those found in unstructured financial documents.

Analyzing social media content from your social listening tool

While social listening tools do a good job of tracking every conversation about your brand or product on the internet, building good text analytics capability is only considered as an afterthought in most of these tools. The data from such social listening tools analyzed by a powerful text analytics tool like ParallelDots Excel add-in can provide a good overview of your social presence.

Excel Text Analysis
Analysing reviews and text on social media

Further, listening tools that do provide good text analytics capabilities can be an expensive tool to use when compared to the Excel add-in like ParallelDots.

These listening tools give a very convenient option to export all the conversations in csv format. You can then analyze these conversations similar to product reviews to get actionable insights such as sentiment attached to the conversation, keywords and key-phrases mentioned, emotions detected in the conversation, entities mentioned, etc.

Empowering business analysts to carry out text analysis on unstructured datasets

Business analysts capture, analyze and document business needs and changes. A business analyst is usually equipped with huge textual corpus from different domains such as market research, financial data, historical viewpoints, etc.

Excel Text Analysis

ParallelDots Excel Add-in can help analysts up their game since excel is heavily used in analyzing the data points in this sector. Business analysts can process the information faster using multiple functions from the ParallelDots Excel Add-in. They can gather relevant insights such as extracting the entities, categorizing products, services or markets based on sentiment and classifying text based on the IAB categories etc.

The use cases of ParallelDots Excel add-in are not limited to the ones mentioned above. Essentially, you can use the add-in whenever you require to process a large corpus of unstructured textual data, just download the add-in, sign up for your unique API key and start analyzing your content. Functionality info here.


Original Source.

Shashank Gupta

Shashank Gupta

Experienced Growth Hacker with a demonstrated history of working in the retail industry. Skilled in Data analysis on Excel, SQL, Operations Management, Microsoft Word, Computer Science, Operational Planning, and Java. Strong engineering professional with a Bachelor of Technology (BTech) focused in Computer Science from The LNM Institute Of Information Technology.