Give Business Users NLP Search Analytics and Get Results!

NLP Search Analytics Ensures User Adoption

These days, most people understand the term Natural Language Processing (NLP). It has been around a while, and represents perhaps the most significant information tool in the past century.

Machine Learning and Natural Language Processing (NLP) have unlocked a vast library of knowledge, making it accessible to the average person, requiring no significant technical skills, and leveling the playing field for millions of people, seeking to learn and understand the world.

‘NLP search technology significantly simplifies the user experience and encourages team members to learn and incorporate augmented analytics into their daily activities.’

Just a few years ago, Gartner predicted that, ‘50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.’ Today, this prediction is a reality.

When an enterprise wishes to implement augmented analytics and business intelligence, and make these tools available to its business user community, it must select a solution that uses natural language processing (NLP) search capabilities to allow business users with average technical skills to gather and analyze data and achieve results. Without these simple tools, the enterprise cannot ensure user adoption of the solution.

Natural Language Processing Search Analytics (NLP) is crucial component to search analytics in that it allows business users to perform complex searches without endless clicks, coded queries, or complex navigation and commands. Users can access and view clear, concise answers and analysis quickly and easily, leveraging a familiar Google-type interface to compose and enter a question using common language.

Natural Language Processing and NLP Search Analytics Give Business Users True Access to Analytics

When you choose Augmented Analytics with machine learning and natural language processing (NLP), your users can enjoy a self-serve environment that is easy and intuitive, and will increase user adoption, data democratization, and return on investment (ROI).

NLP search technology significantly simplifies the user experience and encourages team members to learn and incorporate augmented analytics into their daily activities. Finding information is easy! Let’s suppose a team member wants to understand the trends in regional bakery sales. With NLP, the user can simply ask, ‘how many bakery products were sold in the Southwest and Southeast regions in 2023?’

Natural Language Processing (NLP) and search capability allows users to avoid scrolling through menus and navigation. The user only has to enter a simply worded search query, and the system will translate the query, and return the results in natural language using an appropriate form, e.g., visualization, tables, numbers or descriptions. There is no advanced training required. Users can analyze data and receive results in a way that is meaningful to them.

The benefits of augmented analytics using natural language processing (NLP) enable swift, easy searching and allows business users to create context-rich searches that provide in-depth information and concise results and can be used to solve problems, identify opportunities, spot trends and patterns and present data and recommendations. There is no need to request reports or information from IT, business analysts or data scientists. The business user has the tools and the capability to get results when and how they need the information.

‘Just a few years ago, Gartner predicted that, ‘50% of analytical queries will be generated via search, NLP or voice, or will be automatically generated.’ Today, this prediction is a reality.’

To find out more about Natural Language Processing (NLP), Machine Learning and NLP Search AnalyticsContact Us. Discover the power of Augmented Analytics, Machine Learning, and Natural Language Processing (NLP). Read our free article, ‘Why is Natural Language Processing Important to Enterprise Analytics?

Choose Augmented Analytics Designed for Business Users!

Avoid Complex Analytics Solutions (Your Users Will Hate)

When a business is considering a business intelligence or analytics solution, it is important to recognize that today’s solutions are very different than the solutions of the past. Not only do they include more analytical techniques and features, but they have come a long way in providing access to sophisticated analytics for the average enterprise team member.

Harvard Business Review Analytics Service reports that

a) businesses can substantially improve business performance by giving frontline workers modern self-service analytics tools to enable fast intelligent action and,

b) not all self-service analytics provide this effective approach.

Choose Augmented Analytics Designed for Business Users and Get the Most From Your Solution

The Harvard Business Review Analytics Service surveyed nearly 500 executives and found that they reported significant performance improvement when they empowered frontline workers with augmented analytics. More than one-third of those surveyed noted improvement in customer and employee engagement and in product and service quality.

While some businesses may still be using business intelligence and analytics that are designed for data scientists and IT professionals, most of those are actively working to upgrade and/or migrate to augmented analytics and solutions that are designed for self-serve business user access.

Here’s why:

  • Search-based, self-serve analytics provides swift access to data and familiar natural language processing (NLP) search capability so business users can ask a question, get an answer and drill down to discover the root cause of issues. There is no need for the user to wait for IT or a data scientist to produce a report. They can continue to work on a task or a problem with full insight into results, challenges and possibilities.
  • The enterprise can enable data democratization and data literacy across the business landscape, thereby ensuring that there is a rapid response to market and competitive changes and to changing customer buying behavior.
  • Business users can leverage their industry knowledge and functional skillset and combine data insight with experience to produce the best results.
  • Intuitive, easy-to-use solutions help to combat user resistance and ensure user adoption. While there are always cultural issues surrounding this type of adoption and the perceived changes in responsibilities, when business users see the value of having crucial information at their fingertips, the enterprise can ease the transition and ensure user adoption.
  • No matter the role of the user, the team can enjoy the benefits of augmented analytics and make the transition to Citizen Data Scientists to improve collaboration, data sharing and fact-based decision-making.
  • The business can understand quality and maintenance issues, refine customer targeting and marketing optimization, and make appropriate financial investments, and they can analyze trends and patterns and make forecasts and predictions.
  • When the enterprise adopts these tools and techniques, they allow Citizen Data Scientists to perform analytics on a day-to-day basis and, where appropriate to effectively interact with and collaborate with the IT team and data scientists to refine data and prepare it for more strategic initiatives, so there is a seamless handoff from the business user to the analytical community, when and as necessary.

When the business is ready to acquire augmented analytics or to upgrade from existing, more restrictive solutions designed for professional analytical resources, it is important to choose the right solution – one with sophisticated tools that are presented in an intuitive user interface with auto-suggestions and recommendations to assist business users, and ample personalization of dashboards and reports.

With the right IT consulting partner, you can select and implement an Augmented Analytics Solution with business intelligence (BI) and advanced capabilities, and ensure that every user can leverage these tools, no matter their skillset or technical capabilities. Explore our free white paper, ‘A Roadmap To ROI And User Adoption Of Augmented Analytics And BI Tools.’

Natural Language Processing Analytics for Business Users!

Clickless Analytics in Augmented Analytics Solution Supports Users with Simple Searches and Results!

Every consumer and business user loves the new world of search and query. Google-type searches offer the ability to ask a question in simple form, and receive an answer you can understand. You don’t have to be a data scientist, a rocket scientist, a statistician or a data guru to perform the search or to understand the results!

Why Does My Business Need NLP Search Analytics?

The What and Why of NLP Search Analytics and How it Can Help Your Business!

If your business is considering an advanced analytics solution, your IT and management team has probably already done some research and concluded that the concept of augmented analytics designed to support business users is the right way to go. To democratize data, improve data literacy and transition business users to the Citizen Data Scientist role, the business must select the right solution and plan for success.

Include Clickless Analytics in Your Data Democratization Project!

How Can Clickless Analytics Help My Business Succeed in Data Democratization?

Gartner predicts that ‘… augmented analytics will be ubiquitous, but only 10% of users will use it to its full potential.’ One of the primary reasons that augmented analytics is not adopted and leveraged to its full capacity is that the business chooses a solution that is not easy enough for team members to adopt – one that is restrictive, inaccessible or requires sophisticated skills.

How Can NLP Help My Business Implement Self-Serve Analytics?

What is Natural Language Processing and Why Do I Need it in My Advanced Analytics Solution?

What is Natural Language Processing (NLP)?

Natural Language Processing utilizes artificial intelligence to translate computer code and language into real world, human language. While the goal is to simplify human interaction with computers, NLP is a complex mix of computational linguistics and computer science. When a business is considering an augmented analytics solution that leverages natural language processing, it need not concern itself with the complicated underpinning of code and design, but should rather consider what NLP can do for its users and for its business results.

Smarten Launches Clickless Analytics Natural Language Processing (NLP) Search Analytics for Business Users!

Smarten Launches Clickless Analytics Natural Language Processing (NLP) Search Analytics for Business Users

Smarten announces its Smarten Clickless Analytics, a Natural Language Processing (NLP) Search Analytics tool designed for every business user, no matter their technical expertise or data skills. Natural Language Processing Search Analytics (NLP) is an easy-to-use search analytics technique that allows business users to create complex searches without endless clicks and complex navigation and commands. Using this familiar Google-type Clickless Analytics, users can leverage these tools to discover trends and patterns, receiving results in simple, clear language the user can understand.

NLP Makes Every Business User More Comfortable With Analytics!

Natural Language Processing Defeats User Trepidation About Augmented Analytics!

Your business users probably fight you on improving data literacy and on implementing digital transformation. Many business users have a fear of analytics and envision having to become a business analyst or a data scientist in order to fulfill the vision of the business and its Citizen Data Scientist goals.

Increase Data Literacy And Enable Digital Transformation!

Enable Data Literacy & Digital Transformation With Augmented Analytics!

If your business wishes to enable Digital Transformation, it must create a roadmap to achieve results using new or modified technologies, streamlined workflow and processes that will leverage these technologies to enhance information sharing and ensure a consistent, uniform approach to business objectives and goals. It must also encourage and advance Data Literacy within the ranks of its teams. Why is data literacy important?