What is your data telling you?
Specifically, the 80% of your data that you can’t analyze.
Datavox allows you to measure and monetize this remaining 80%.
What is your data telling you?
Specifically, the 80% of your data that you can’t analyze.
Datavox allows you to measure and monetize this remaining 80%.
Datavox is a purpose-built Generative AI platform that converts unstructured data to structured data. Unstructured data represents more than 80% of all data available to companies. Because it’s unstructured, this data cannot be analyzed or measured, meaning 80% of all information has no voice. Until now.
Datavox is the first commercially available platform that solves this problem and gives you the incredible value found in this data. Not only does Datavox transform this data through our patented Textual ETL™ platform, we provide industry-leading visualization and analysis tools to give you the deepest and most meaningful insights into what this data is saying to you.
Examples of our work traverse consumer goods, financial services, retail, hospitality, insurance and medical research companies. The benefit and meaningful impact is both subjective and objective. It shows value across brand, customer sentiment, financials, voice of the customer and medical research among other categories.
“If HP knew what HP knows, we would be three times more productive.” – Lew Platt – Former CEO of Hewlett Packard
“If HP knew what HP knows, we would be three times more productive.” - Lew Platt – Former CEO of Hewlett Packard
“Everybody needs data literacy because data is everywhere. It’s the new currency, it's the language of the business. We need to be able to speak that.” – Piyanka Jain, CEO, Aryng, Thought Leader Data Analytics
“People spend 60% to 80% of their time trying to find data. It’s a huge productivity loss.” — Dan Vesset, group vice president, IDC
"The world is one big data problem." - Andrew McAfee, Co-founder of MIT Initiative on the Digital Economy
“Executive management is more likely to invest in data initiatives when they understand the 'why.'” — Della Shea, vice president of privacy and data governance, Symcor
“Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.” – Suhail Doshi, chief executive officer, Mixpanel.
“We’re entering a new world in which data may be more important than software.” – Tim O’Reilly, founder, O’Reilly Media.
"Data is not just a bunch of numbers; it should tell a story." - Stacey Barr, Performance Measure Specialist
“Big data will replace the need for 80% of all doctors.” – Vinod Khosla, co-founder of Sun Microsystems and founder of Khosla Ventures
“The world is one big data problem.” – Andrew McAfee, principal research scientist, MIT.
"Without big data analytics, companies are blind and deaf, wandering out onto the web like deer on a freeway." - Geoffrey Moore, Author and Consultant
"Data is the new oil. It's valuable, but if unrefined, it cannot really be used. It has to be changed into gas, plastic, chemicals, etc., to create a valuable entity that drives profitable activity; so must data be broken down, analyzed for it to have value." - Clive Humby, Data Scientist
“If HP knew what HP knows, we would be three times more productive.” - Lew Platt – Former CEO of Hewlett Packard
“Most of the world will make decisions by either guessing or using their gut. They will be either lucky or wrong.” – Suhail Doshi, chief executive officer, Mixpanel.
“We’re entering a new world in which data may be more important than software.” – Tim O’Reilly, founder, O’Reilly Media.
“Big data will replace the need for 80% of all doctors.” – Vinod Khosla, co-founder of Sun Microsystems and founder of Khosla Ventures
If HP knew what HP knows, we would be three times more productive.
We’ll save them a ton of money and reputation in the form of averted strategic blunders, financial mis-calculations and lack of insight to the voice of the customer. We’ll also, make medical research and innovation unbelievably more streamlined, fast and powerful.
Datavox literally means “Data’s Voice.” We’re giving voice to the 80% or data they cant currently analyze. That’s the Holy Grail in business strategy and awareness.
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Consider all of the data your company receives – customer reviews, personal notes, pdfs, engineering diagrams – every day. Datavox allows you to load all of that unstructured data (that has no value today) to be run through our Textual ETL™ platform to convert it to structured data. As structured data, it can now be visualized and analyzed by the leading platforms on the market like Neo4j and Tableau. By allowing you to tease out meaning, draw conclusions, and gain insight, Datavox will save you a ton of money and reputation in the form of averted strategic blunders, financial mis-calculations and lack of insight to the voice of the customer. We’ll also, make medical research and innovation unbelievably more streamlined, fast and powerful. Datavox literally means “The Voice of Data.” We’re giving voice to the 80% of data that can’t currently be analyzed. That’s the Holy Grail in marketing, business strategy and corporate awareness.
Load all of your data that currently can't be analyzed - customer reviews, product opinions, PDF's, handwritten notes, engineering artifacts. illustrations, any data that is unstructured - and our platform will process it through Datavox Textual ETL™.
Textual ETL™ automates the transformation of large volumes of textual artifacts, by creating Metadata – data about data – to isolate what’s relevant and identify meaningful and valuable relationships. insights and meaning in the specific context of our customers' company.
Once converted to structured data you can seamlessly use the best analysis platforms available to visualize and drill into the data, uncovering enormously valuable subjective and objective insights from 80% of your total data that couldn't be measured previously.
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The voice of the customer/customer sentiment are the most sought after influences on contemporary data analysis for marketing, financial, brand and research. Datavox has particularly deep experience in the following broad categories:
Unstructured data, such as customer reviews, social media comments, and online discussions, provides valuable insights into customer sentiments and preferences. Analyzing this data helps retailers understand customer satisfaction, identify popular products, and address potential issues in real-time.
By examining customer reviews, retailers can gather information on what features are appreciated or lacking in their products, helping them make data-driven decisions for product enhancements and assortments.
By tracking social media, news articles, and customer reviews related to competitors, retailers can gain insights into market trends, pricing strategies, and customer perceptions, allowing for more informed competitive positioning.
By tracking online mentions and customer sentiments, retailers can address issues promptly, capitalize on positive feedback, and maintain a positive brand reputation.
Analysis helps retailers identify pain points in the customer journey. By understanding customer feedback and sentiments at different touchpoints, retailers can make improvements to enhance the overall customer experience, both online and in-store.
Unstructured data analysis contributes to evaluating the success of marketing campaigns. By measuring changes in sentiment over time, marketers can gauge the impact of their initiatives and adjust strategies accordingly.
By examining textual information from various sources, including news articles and reports, financial institutions can identify potential risks to their portfolios, assess the impact of geopolitical events, and make data-driven decisions to mitigate risks.
Monitoring competitor activities, assessing market trends, and identifying emerging opportunities or threats that may impact the financial landscape.
By examining patterns and anomalies in unstructured data, financial institutions can identify potential instances of fraud, helping to secure transactions and protect both the company and its customers.
Qualitative information about a borrower’s financial behavior or business operations, can complement traditional credit scoring. Analyzing this data provides a more comprehensive view of credit risk, enabling financial companies to make more accurate lending decisions.
Financial institutions can extract relevant information from various documents and textual sources to ensure adherence to regulatory requirements and reporting standards.
Financial companies can use natural language processing and sentiment analysis to make predictions about market movements, optimizing trading algorithms for better performance.
By understanding customer preferences expressed in reviews and social media posts, businesses can tailor their offerings, recommend personalized travel itineraries, and provide a more customized service.
Monitoring unstructured data allows businesses to stay informed about travel trends and popular destinations. This insight is valuable for travel agencies, airlines, and hospitality providers to adapt their offerings, develop new packages, and stay ahead of evolving customer interests.
Unstructured data analysis is crucial for managing crises and unexpected events that may impact the travel industry, such as natural disasters or global health crises. By monitoring social media and news sources, businesses can respond quickly, communicate effectively with customers, and adapt their services as needed
By understanding customer feedback and preferences, businesses can tailor loyalty programs to offer rewards and benefits that resonate with their target audience, fostering customer loyalty and retention.
Analyzing this data helps businesses understand customer sentiments, identify popular destinations, and address issues promptly to enhance overall customer satisfaction.
Unstructured data analysis aids in understanding customer preferences for specific dishes and beverages. By examining reviews and social media discussions, restaurants and bars can identify popular items, as well as opportunities for menu innovation, ensuring that offerings align with customer tastes.
By monitoring customer feedback and reviews, businesses can identify areas for improvement in service delivery, staff performance, and overall operations, leading to a smoother and more efficient operation.
Social media and review platforms provide real-time insights into customer experiences. Analyzing unstructured data allows businesses to respond promptly to customer feedback, addressing concerns, expressing gratitude for positive reviews, and demonstrating a commitment to customer satisfaction.
Understanding the strengths and weaknesses of competitors. By analyzing customer reviews and sentiments related to similar establishments, restaurants and bars can identify areas where they can differentiate themselves and excel in the eyes of their customers.
By understanding customer preferences, expectations, and pain points, restaurants and bars can implement changes that enhance the overall dining or drinking experience for their patrons.
Customer interactions with staff. Analyzing customer feedback helps businesses identify areas for staff training and development, ensuring that employees are equipped with the skills to deliver exceptional service.
Unstructured data, such as sensor data, maintenance logs, and field reports, can provide valuable insights into the condition of equipment and infrastructure. Analyzing this data allows energy companies to predict maintenance needs, optimize asset performance, and reduce downtime, contributing to overall operational efficiency.
Unstructured data analysis is essential for managing power grids effectively. By incorporating data from various sources, including weather patterns, equipment diagnostics, and grid performance reports, energy companies can enhance grid reliability, respond to outages more efficiently, and minimize the impact on consumers.
The energy industry is undergoing a significant shift toward renewable sources. Unstructured data, such as weather forecasts and environmental data, is vital for optimizing the integration of renewable energy into the grid. Analyzing this data helps balance supply and demand, manage fluctuations, and maximize the efficiency of renewable energy sources.
Energy companies often have complex supply chains. Unstructured data analysis helps optimize the supply chain by providing insights into factors such as vendor performance, logistics, and market conditions. This contributes to cost efficiency and ensures a reliable supply of resources.
By mining data from research papers, industry publications, and innovation forums, energy companies can stay abreast of technological advancements, emerging trends, and opportunities for research and development.
By analyzing regulatory documents, safety reports, and incident records, energy companies can identify potential risks, ensure compliance with industry standards, and implement measures to mitigate operational and regulatory risks.
Clinical notes and patient records, contains a wealth of information beyond structured datasets. Analyzing this data allows researchers to extract valuable insights into patient experiences, treatment outcomes, and the progression of diseases, contributing to a more comprehensive understanding of medical conditions.
The medical research landscape is vast, with an extensive body of scientific literature. Unstructured data analysis helps researchers mine this literature for relevant information, identify patterns, and stay abreast of the latest developments in medical science, facilitating more informed and innovative research.
By examining unstructured information from preclinical studies, research papers, and clinical trial reports, researchers can identify potential drug candidates, assess their efficacy, and streamline the drug development process.
Genomic and proteomic data are often unstructured and complex. Analyzing this data helps researchers identify genetic variations, biomarkers, and molecular pathways associated with diseases, leading to personalized medicine and targeted treatment approaches.
Public health surveillance by mining data from sources such as social media, news articles, and online forums. This allows researchers to track disease outbreaks, monitor public sentiments, and implement timely interventions for public health crises.
Analyzing unstructured data, including patient narratives and qualitative research, is essential for patient-centered outcomes research. This approach ensures that research aligns with patient priorities, preferences, and experiences, leading to more patient-centric healthcare solutions.
Unstructured data, such as customer reviews, social media comments, and online discussions, provides valuable insights into customer sentiments and preferences. Analyzing this data helps retailers understand customer satisfaction, identify popular products, and address potential issues in real-time.
By examining customer reviews, retailers can gather information on what features are appreciated or lacking in their products, helping them make data-driven decisions for product enhancements and assortments.
By tracking social media, news articles, and customer reviews related to competitors, retailers can gain insights into market trends, pricing strategies, and customer perceptions, allowing for more informed competitive positioning.
By tracking online mentions and customer sentiments, retailers can address issues promptly, capitalize on positive feedback, and maintain a positive brand reputation.
Analysis helps retailers identify pain points in the customer journey. By understanding customer feedback and sentiments at different touchpoints, retailers can make improvements to enhance the overall customer experience, both online and in-store.
Unstructured data analysis contributes to evaluating the success of marketing campaigns. By measuring changes in sentiment over time, marketers can gauge the impact of their initiatives and adjust strategies accordingly.
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High-level Whiteboard overview of Datavox and our corporate value
proposition -January 2024
This explainer Whiteboard covers our Call-Center-specific offering
which brings value from the millions of voice recordings that Call
Centers receive and store, but can’t analyze – February 2024
Overview Whiteboard of how Datavox allows corporations to organize,
correlate and retrieve their millions of impossible-to-find documents –
March 2024
Healthcare executives, especially those in medical research, can now
leverage the immense power of the patient medical record. Datavox
provides the capability to analyze 1000’s or millions, of patient
records simultaneously. Opening the door to revolutionary treatments for
disease – April 2024
All Datavox subscriptions include each of the following:
The following are other onging services and options that are included or available:
As necessary for your specific project or customized departmental requirements:
Datavox is built on Data Science, Analytics, Entrepreneurship, Channel Partnerships and Enterprise Sales.
Chairman and Co-Founder Bill Inmon (https://en.wikipedia.org/wiki/Bill_Inmon) – best-selling author, widely considered by most data leaders as the “Father of the Data Warehouse” and most recently, co-architect of the “Data Lakehouse,” has created the Textual ETL™ process and framework on which Datavox is built. Founder, Roger Lindsay – a seasoned entrepreneur with several successful technology startups and exits over the last 20 years – created the go-to-market approach for Datavox and runs strategy, channel sales and revenue.
The founders have created a platform that exposes the 80% of all corporate data that is not currently available for analysis. Now this data has gone from unstructured data to structured data which can be thoroughly examined for amazing insights into customer sentiment, voice of the customer, brand perceptions, areas for improvement, financial anomalies and corporate insights that have incredibly subjective and objective ROI.
Our team is comprised of serial entrepreneurs, best-selling authors, thought leaders on data science and a customer support staff that will ensure everyone provides the highest value, lowest complexity and outstanding value.
If HP knew what HP knows, we would be three times more productive.
If you’re interested in a career at a dynamic, cutting-edge technology company, we have several positions available:
We’re looking for problem solvers, innovators, and entrepreneurial thinkers who are searching for anything but business as usual. Like us, you’re a high performer who’s an expert at your craft, constantly challenging the status quo.
You know that success hinges on commitment, that our differences make us stronger, and that the finish line is always sweeter when the whole team crosses together.
Role: Responsible for selling at the most senior Marketing and Product Leaders and the C-Suite within larger accounts and implementing a broad strategy for earning customer acceptance and implementation. Collaborate with all appropriate Datavox to support customer success. You understand how to advocate for customers and balance that advocacy with Datavox’s business needs.
Responsibilities: Driving Account Development – Owning account relationships to maximize sales into enterprise accounts and being part of the customers’ overall business solution. Driving cross-sell and up-sell opportunities. Penetrating additional buyers within the accounts, identifying their needs and then configuring an appropriate offering from our portfolio to meet those needs. Establish positive relationships that drive value Driving Sales Execution – Leading enterprise agreements to close large-scale, multi-year subscription-based deals. Prepare accurate forecasts, building a funnel to cover bookings targe and documenting activities in HubSpot.
Qualifications: Minimum of 5 years of quota-carrying sales experience, as the lead account owner of an enterprise customer, at a software/technology company. Track record of closing multi-year and subscription-based SaaS deals Proven ability to cultivate relationships with a strategic customer based and advising on industry insights, best practices and strategy Excellent leadership and strong ability of working with and managing people across functions and geographies Viewed as an expert in advanced data analytics by accounts Bachelor’s degree or equivalent work experience Find yourself checking a lot of these boxes but doubting whether you should apply? At Alteryx, we support a growth mindset for our associates through all stages of their careers. If you meet some of the requirements and you share our values, we encourage you to apply. As part of our ongoing commitment to a diverse, equitable, and inclusive workplace, we’re invested in building teams with a wide variety of backgrounds, identities, and experiences. OTA: $200K+
The Channel Partner Manager is responsible for developing and managing relationships with channel partners to drive sales and revenue for Datavox. They identify and onboard new partners, provide support and training, and manage the performance of existing partners. Maintain and grow these relationships and drive to defined revenue goals. Help to build incentive plans and benefits for channel partners that drive to their revenue goals. Find partners who sell software or services that compliment Datavox.
At Datavox we’re proud to stand at the forefront of the Big Data revolution. Using the latest analytics tools and processes, we’re able to maximize our offerings and deliver unparalleled service and support. To help carry us even further, we’re searching for an experienced data analyst to join our team. The ideal candidate will be highly skilled in all aspects of data analytics, including mining, generation, and visualization. Additionally, this person should be committed to transforming data into readable, goal-oriented reports that drive innovation and growth.