Unlocking actionable insights: Why AI Summary is your key to text analysis success

If you’re reading this, you already know that data analysis reigns supreme and efficiency is the name of the game. 

To simplify your analysis process, you’ve likely come across various artificial intelligence tools, each promising to lighten your workload with varying degrees of success.

To streamline your analysis and reporting, we’ve harnessed the core capabilities of machine learning, integrating them with Relative Insight’s powerful analysis tool to create our latest feature – AI Summary.

AI Summary leverages artificial intelligence to offer you an instant overview of your data. No more sifting through endless spreadsheets and reports – with AI Summary, actionable insights are at your fingertips, easily accessible from your dashboard. 

So how exactly can AI Summary help you make informed decisions quickly and effectively?

How AI Summary can help you revolutionize your text analytics journey?

Here are just some of the benefits you can reap with AI Summary.

Accelerated decision making: Time is money; and you’re probably short on at least one of the two. AI Summary accelerates your path to decision making by automatically identifying key metrics and top-level insights. No more wasting hours on analysis – with AI Summary, you can make informed decisions in record time.

Sharable insights: You can create a swift, sharable summary to present to your stakeholders. Whether you’re preparing for a board meeting or updating your team, AI Summary makes it easy to share insights in just a few clicks.

Increased productivity: By streamlining the analysis process, AI Summary frees up valuable time for other tasks. With less manual data crunching, you can spend time finding the solutions that matter, e.g. implementing changes to improve your customer satisfaction.

Use case: Understanding movie preferences

Now, let’s illustrate the power of AI Summary with a real-world example.

Imagine you’re analyzing customer feedback about movies. With AI Summary, you can quickly uncover key themes and connections within the data, such as:

Movie selection process:  The process of selecting a movie is a prevalent topic within the data, with individuals sharing their strategies or struggles when choosing what to watch.

Decision making: Terms like ‘pick’ and ‘choose’ indicate a highly involved decision-making process, where individuals actively engage in selecting movies that resonate with their preferences.

Viewing habits: References to ‘argue’ or ‘disagree’ highlight the viewing habits and inclinations of individuals or groups, indicating a shared activity that often involves negotiation or compromise.

Selection challenges: The data also reflects the challenges of making a choice, with individuals seeking help or taking an extended amount of time to decide, emphasizing the overwhelming nature of the available options.

Content preference: Lastly, terms like ‘soundtrack’ or ‘scenery’ suggest a preference for certain types of cinematic works, possibly distinguished by their artistic or cultural value.

The dataset reveals an overarching concern with the selection of visual entertainment, marked by personal preferences, social dynamics, and challenges around decision making. With AI Summary, you can uncover these insights in a fraction of the time, allowing you to make data-driven decisions with confidence.

Uncovering insights from CSAT scores with AI-powered text analytics

From a more practical perspective, understanding the fluctuations in NPS and CSAT scores has never been easier with AI Summary. 

Text analytics allows businesses to delve into customer feedback. Our AI Summary provides instant insights into why the scores are moving up or down – revealing specific pain points, desires, and potential recommendations. By translating qualitative feedback into actionable insights, businesses can directly address issues impacting customer satisfaction and revenue. 

For instance, consider a movie theater chain that utilized text analytics to analyze its CSAT responses. It found that the quality of food and drink in its venues was a significant driver of dissatisfaction among customers. By addressing these concerns and improving the offering, the brand not only boosted its CSAT but also saw increased sales.

With our text analysis tool, supported by AI Summary, companies can quickly identify areas for enhancement and align changes with customer feedback.

Without understanding the reasons behind falling CSAT scores, the company would not be able to make simple, yet necessary improvements to food and drink quality that resonate with their customers. Long term, this can stifle customer-centric innovation and result in a loss of revenue. 

AI Summary isn’t just another feature – it’s a game-changer for anyone seeking to unlock the full potential of their data. From accelerated decision making to increased productivity, the benefits are clear. 

So why wait? Try AI Summary today to learn how our AI features can decode your customer feedback and unlock your business’s revenue potential. Let’s turn every score and piece of feedback into a story of success.