ANALYST REPORT

Gartner recognizesUnscrambl in it 2019hype cycles

Unscrambl has been recognized in the following Hype Cycles:

Hype Cycle for Data Science and Machine Learning, 2019,

Hype Cycle for Customer Experience Analytics, 2019

Hype Cycle for Analytics and Business Intelligence, 2019.

What is the Hype Cycle?

For the second consecutive year, Unscrambl has been
recognized in two categories in the Conversational
Chatbots for Analytics & Continuous Intelligence in
Gartner’s 2019 Hype Cycle Reports. These respected
reports help businesses understand the maturity of
emerging technologies and how they can help solve
problems and uncover new opportunities. Each report
provides trusted insights to help business leaders
comprehend the new technology or app, its potential
impact on their industry, how beneficial it can be to the
business, and where it currently sits in terms of maturity
and adoption. Within the context of their industry and
business goals, Hype Cycle reports provide decision
makers understanding and insight into the promise of
emerging technologies or applications, how those
technologies might evolve, and how their deployment
should be managed, if at all.

Conversational chatbots for analytics changes how users interact with data from what is currently mainly “drag and drop” elements onto a page, to more of a natural language processing that is supported by voice. This can dramatically improve the adoption of analytics by every employee rather than by predominant power users and business analysts, resulting in higher business impact.

— Rita Sallam

ANALYST REPORT

Conversational Chatbots for Analytics

Gartner surveys show that only around 35% of employees have
access to analytics and BI tools.

Conversational chatbots analytics allows any user to ask voice or
text questions of their data via a virtual personal assistant (VPA) or
mobile device and receive back a natural language and, potentially, a
visual analysis of the most statistically relevant and actionable
insight for that user.

Conversational chatbots for analytics applications are not available from most analytics, and BI vendors out of the box today and early integrations are immature. Promising technology is available from Unscrambl with qbo insights, although the number of customer deployments is still limited. Most other analytics vendors are using APIs and building integrations through partnerships to make them easier to deploy. We expect these to become more out-of-the-box and enterprise- ready over the next two to five years.

Conversational chatbots for analytics changes how users interact with data from what is currently mainly “drag and drop” elements onto a page, to more of a natural language processing that is supported by voice. This can dramatically improve the adoption of analytics by every employee rather than by predominant power users and business analysts, resulting in higher business impact.

People like to have at work what they have at home. This is a natural extension of integrating tech we use in our personal life into our work life.

HYPE CYCLE FOR CUSTOMER EXPERIENCE, 2019

Prioritize Investments based on thematurity, adoption and benefits ofCX analytics

The Hype Cycle for Customer Experience Analytics, 2019 addresses the ways in which customer experience expectations are now driven by the explosion of channels, digital interactions and the volume and connections of diverse data types. This Hype Cycle will help data and analytics leaders prioritize investments based on the maturity, adoption and benefits of CX analytics.

In this report, Unscrambl is again referenced in the section regarding Continuous Intelligence, this time in the context of customer experience.

Hype Cycle for Data Science and Machine Learning, 2019

Improve Expert and Citizen Data Scientist Productivity

The Hype Cycle for Data Science and Machine Learning, 2019 is intended to help data and analytics leaders modernize their analytics and BI programs. Key trends include the ongoing transition to augmented analytics, focus on building a digital culture, and the scaling and operationalization of analytics initiatives.

In this report, Unscrambl is included in the section about Continuous Intelligence, which Gartner describes as a design pattern in which real-time analytics are integrated into business operations, processing current and historical data to prescribe actions in response to business moments and other events.

It provides decision automation or decision support. Continuous intelligence leverages multiple technologies such as augmented analytics, event stream processing, optimization, business rule management and machine learning.

Continuous intelligence plays a major role in digital business transformation projects. A key benefit is improved situation awareness and a common operating picture across business functions by providing real-time dashboards and alerts. Equally important is the capability to trigger automated responses by sending signals to machines or initiating business processes in cases where the decision on what to do can be automated. Systems with continuous intelligence leverage real-time context data to support decisions for customer support, customer offers, risk, or allocating resources in the most efficient manner possible. However, enterprises that do not already have staff expertise in messaging, stream analytics, machine learning and decision management disciplines may need to hire outside service providers or train their staff on the new disciplines.

“at the heart of fast-paced digital business and process optimization, leveraging decision automation, AI, real-time analytics and streaming event data. Data and analytics leaders must prepare for the growing demand by starting experimentation and building capabilities.”

— W. Roy Schulte; Pieter den Hamer; Melissa Davis