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Stratifyd launches ‘next generation’ data analytics platform

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Self-service data analytics specialist Stratifyd has launched its new ‘next generation’ platform. Stratifyd says the analytics engine was re-designed from the ground up to be intuitive and easy-to-use, enabling business users – regardless of education, skill, or job function – to harness the power of proprietary and third-party data to easily reveal and understand hidden stories represented within the data, thus delivering the benefits of a data science team to every organisation.  

The Stratifyd platform now provides the functionality to meet the data science needs of an organisation, but is specifically designed to be easy to use for those with limited data analytics experience. It aims to allow users of all skill levels to connect data sources to the platform, perform in depth analysis and data modelling, and discover insightful stories faster and more easily than previously possible. Through a graphical user interface, pre-built and customisable data analytics models, and simplified dashboards, the platform enables business users to extract insights (ie, stories) that are hidden in the data and essential in helping companies improve customer service, better understand customer requirements, deliver product enhancements that address gaps in the market, solve problems experienced by customers, rollout new product and service offerings that deliver a competitive advantage, and more.

“Stratifyd is a company with data science in our DNA. We were founded with a bold but simple mission to enable everyone within an organisation to not only uncover but also understand the hidden stories within their data,” says Derek Wang, founder and CEO of Stratifyd. “This release of our next-gen platform is a giant leap in bringing to life our vision of putting the power of data science into the hands of business users.” 

The platform was developed with the goal of helping employees from across an organisation tackle real-world business challenges by analysing and visualising structured and unstructured data from a variety of sources, including third party and social media channels, to discern the most complete stories about a company and its products based on customer insights. 

“Data is at the forefront of every decision a business makes and frames the narrative,” says Wang. “To better understand the stories hidden in data, it needs to be viewed from the lens of the business user as they are the storytellers that can consider the data in the appropriate context.”

If customers signal their unhappiness with a product or service through reviews or on social media, a business user can analyse the data to pinpoint the problem, making it easier to fix. Conversely, if customer churn rate has decreased, data can be used to connect the dots to see the bigger picture and the insights leveraged to replicate the successful outcome in other areas of the business.

A financial services company may lean heavily on call centre conversations, customer surveys, operational data, and complaints to help them identify pain points and improve the end-user experience. Auto manufacturers might look to social media, external user forums, and blog posts to help them understand issues related to the quality of their vehicles and overall perception of their brand. In both of these scenarios, the business user has the context with which to analyse the data and drive the necessary action.

By enabling “citizen data scientists” to gather and analyse structured and unstructured data from more than 100 sources, these business users can leverage their expertise to see patterns and anomalies within context to derive a holistic narrative of customer feedback. 
Stratifyd says its data analytics platform is the only truly end-to-end solution in the market helping organisations analyse and extract insights from omni-channel data. Its data storytelling flywheel includes everything that business users need to easily connect data, analyse data, discover insights, identify stories, and continually listen to empower data driven decisions as stories unfold:

First-time users can take advantage of the Quick Start Guide to accelerate their time to insights. The guide leads them, step-by-step, through the process of connecting data, deploying analytical models, and visualising insights as they build their first dashboard.  

The platform includes a library of over 100 Data Connectors that make it easy to analyse structured and unstructured data – from public sources such as Amazon reviews, Google Play and iTunes Store app reviews, and social media channels, as well as internal company data such as call centre conversations, customer survey results, and chat conversations – without the need for time-consuming, manual data cleaning.

Auto-learning Models analyse data and determine the best customised model(s) based on the data available; while advanced models enable data analysts to customise models based on use cases and specific data available.

In addition to making it easy to share insights across teams and departments, the platform includes Task Management features that enable customers to identify key findings in their data which require action, capture tracking tasks, and assign them to a relevant team or individual who can then take the appropriate action and track progress through to completion.

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