Telling a Complete Story With the Data

Blog

Estimated reading time: 3 minutes

Most issues with a product, service, or company are identified in customer comments or reviews, but analyzing unstructured data has historically been difficult and burdensome, despite the value it provides.

And now, analyzing customer data quickly has become absolutely critical as it can ultimately mean the success or downfall of a business.

Why Did Speed Become so Important?

Until recently, the process of data compilation was done in batch with reports compiled daily, monthly, quarterly, or annually. With the rise of the internet and the interconnectivity of people, places, and companies, interaction and instances of providing and receiving feedback have increased significantly.

People have begun to expect that their voices be heard and have inadvertently established a precedent for response time by businesses when an issue arises. Our in-house experts estimate that a company needs to respond within an hour to mitigate the risk of a customer deflecting. And that timer starts ticking the second a user clicks “submit” on a comment box, making speed in analyzing feedback of the utmost importance.

Who Should Be Analyzing This Data?

As recently as 5-10 years ago, most data analytics projects were IT-led. These professionals would get the data, set the parameters, build the pipeline, and begin testing the results in 12-15 months. But businesses don’t have the tolerance for this kind of delay anymore, and they need a solution that offers true self-service to any employee.

The first step to correcting this issue is to democratize the data and get it into the hands of Line of Business teams.

Stratifyd Is the Solution to All Data Analysis Problems

We subscribe to a data connector market, meaning we have prebuilt connectors and are limitless in creating new ones. These connectors allow our platform to ingest data from Excel files, third party systems, CRM systems, chats, surveys, contact center calls, sites like Amazon, and everything in between. After democratizing the data, our platform allows for true self-service thanks to several beneficial features.

Reporting gives you an idea of what happened but lacks the reasoning. To account for this, we changed up the taxonomy approach. Breaking data up into categories inherently injects human bias into the system, causing you to miss underlying signals that aren’t captured inside that taxonomy. Stratifyd leads with Unsupervised Machine Learning (UML) to instantly remove any bias and surface the statistically relevant pieces of information. We also give you the best of both worlds by allowing you to overlay taxonomies and our machine learning capabilities help augment them, keeping them up-to-date and bias-free.

Next, we blend textual data with structured data, which we refer to as data fusion. Omni-channel insights are all compiled and displayed on one easy-to-navigate dashboard. This blending of qualitative and quantitative data allows you to see both what happened and why.

Stratifyd can also predict NPS/CSAT scores by analyzing chat and call transcripts, eliminating any gaps left by the inability to analyze unstructured data of the past.

And our platform does more than remove bias. It accurately assigns sentiment and classifies data by complaint versus feedback. This categorization makes the data actionable because it identifies customers who are loyal and ones who are at high risk of deflecting.

All of these features present insightful data in a matter of minutes. And when it comes to analyzing customer feedback, near real-time is everything.