Real-life use case examples of NLP Dashboards
Now that you’re familiar with what a natural language processing dashboard is and how it can help your business, let’s explore some of the ways in which Fast Data Science can help you implement it from a sector-specific standpoint:
NLP dashboard for tracking survey responses in market research
You’ve probably answered a market research survey that made heavy use of questions on the Likert scale, which ranges from “Strongly Agree” to “Strongly Disagree”. This can sometimes be a frustrating experience as a survey respondent. A common problem encountered by market researchers is the difficulty of analysing free-text responses. Most market research surveys try to stick to numeric scales such as the Likert scale in their survey design, due to the greater ease of statistical analysis.
NLP dashboards allow researchers to explore free-text answers and even analyse them and cluster them in real-time, freeing up market researchers to use more dynamic survey designs with more free-text fields. This also gives survey respondents freedom to answer in their own words, rather than being constrained to a number of set questions.
NLP dashboard for Customer Service (monitoring customer complaints)
An NLP dashboard can be connected to a CRM, allowing stakeholders in a business to monitor the current sentiment in customer complaints, and spot and quickly react to emerging trends.
NLP dashboard for monitoring social media
We can set up an NLP dashboard to monitor sentiment about your business or product on social media and forums. A social media feed or API can be connected to NLP models such as sentiment analysis and named entity recognition, allowing you to detect emerging trends in real-time, and visualise topics on a map view.
NLP dashboard for exploring scientific literature
A common problem faced by researchers across fields, from pharmaceuticals to physics, is the difficulty of keeping up with the onslaught of abstracts that appear on a daily basis. It’s especially hard for researchers in biological sciences where names of enzymes and proteins can range from the mundane to the ridiculous (Sonic Hedgehog protein?). NLP can be used to sift through unstructured data and identify entities of interest, and a dashboard can display insights. For example, an NLP dashboard could display all proteins in a set of documents on a graphical view and link them according to their purported associations.
NLP dashboard for KOL insights in pharma
Pharmaceutical companies are often sitting on a goldmine of data in terms of their interactions with Key Opinion Leaders (KOLs). These are often transcripts of phone calls between pharma reps and medical professionals, who have stated opinions such as “we have seen an unusual number of AEs with Dabra” (AEs = ‘adverse events’ and ‘Dabra’ = ‘Dabrafenib’). An NLP dashboard allows the pharmaceutical company to sift through large numbers of transcripts and even identify correlations automatically (“68% of KOLs reported no AEs with Dabrafenib”). NLP dashboards are delivering huge value in the pharmaceutical industry.
NLP dashboard for CMO
The day-to-day job functions of a Chief Marketing Officer are varied and equally stressful. Each day, they must have access to a wealth of high-quality and up-to-the-minute data from a single source in order to make key decisions.
Our dynamic NLP dashboard for CMOs is full of interactive charts, metrics and KPIs that makes the ‘live’ decision-making process a more informed, timely, accurate and valuable one. Having access to in-depth information on unstructured marketing data will delight CMOs as they see their ROMI (return on marketing investment) rise higher each year.
NLP dashboard for customer feedback
What people are saying about your products, services or brand at any point in time can truly make or break your reputation. In case of the latter, it can be very difficult to rebuild something which has taken years of trust and loyalty to build.
Our NLP dashboard for measuring customer sentiment is a great way to stay on top of what people are saying about your business. Main KPIs in this case would be overall customer sentiment (positive, negative or neutral), feedback about specific services and/or products, and the total number of customers who are either completely happy or unhappy with what you’re offering.
A sentiment analysis natural language processing dashboard is a great way to showcase consumer data to stakeholders, investors or the general public, as well as share insights with your internal team. Spot trends and patterns and take the necessary action before any negative sentiments tarnish your brand name.