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AI bots for customer experience: trends, insights, and examples

CIO

Here’s an example of how this could work: A customer calls his car insurance company after being in a minor fender bender. Could we see an increase in reverse handoffs where customers go from agent to bot? Yes, especially as processes near completion so that agents can free up more time.

Examples 290
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8 data strategy mistakes to avoid

CIO

Organizations can’t afford to mess up their data strategies, because too much is at stake in the digital economy. How enterprises gather, store, cleanse, access, and secure their data can be a major factor in their ability to meet corporate goals. Here are some data strategy mistakes IT leaders would be wise to avoid.

Strategy 340
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Patient data is at greater risk than ever. AI can help

CIO

Patient data represents a treasure trove for hackers. It’s little wonder that data theft is increasingly common in the healthcare sector. In the US, for example, the medical data of more than 88 million individuals was exposed last year alone. Are you ready to put AI at the heart of your data protection strategy?

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What happens when you mess up data modeling?

Xebia

There has been an uptick in discussions surrounding the modern data stack, data mesh and self-service promising to solve many of your company’s data problems. Knowing a data modeling technique versus implementing it are two entirely different things. Teams creating their own data definitions.

Data 130
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How to Operationalize Data From Multiple Sources to Deliver Actionable Insights

Speaker: Speakers from SafeGraph, Facteus, AWS Data Exchange, SimilarWeb, and AtScale

Data and analytics leaders across industries can benefit from leveraging multiple types of diverse external data for making smarter business decisions. Data and analytics specialists from AWS Data Exchange and AtScale will walk through exactly how to blend and operationalize these diverse data external and internal sources.

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Insights from your JIRA data to help improve your team

Xebia

Therefore, we have selected three different views on JIRA data that have proven their value in different organizations. Please remember, that data, while powerful, is context-dependent and only shows a part of the truth. Example: Showing the statuses, the transitions between them with the average time between them.

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CISOs are not just the keepers of our data – they must be its custodians

CIO

These attacks come in various formats, often including accessing private data through phishing, which AI is making harder and harder to detect. As our data becomes more and more vulnerable online, its protection has become more and more of a priority. CISOs stand not merely as overseers, but as architects of crucial security postures.

Data 299
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7 Winning Lead Generation Strategies to Drive Growth

As B2B companies pivot to keep pace with a quickly changing marketplace, a data-centric approach to lead generation can be the difference between remaining competitive or being left behind. In this whitepaper, you’ll see real-world examples from leading B2B businesses and learn new ways of using data to: Improve lead quality.

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Outrun Your Competition: Best Practices for Accelerating Sales Processes

By building a modern GTM motion that uses data, automation, and proven best practices to unlock insights, engage customers, and win faster. How can you speed it up?

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How Banks Are Winning with AI and Automated Machine Learning

Estimating the risks or rewards of making a particular loan, for example, has traditionally fallen under the purview of bankers with deep knowledge of the industry and extensive expertise. Today, banks realize that data science can significantly speed up these decisions with accurate and targeted predictive analytics.

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11 Email Deliverability Strategies to Reach the Inbox

Data Axle’s deliverability experts developed this guide to help you overcome the challenges that stand in the way of optimal inboxing. Real-world examples from 9 companies applying deliverability best practices. Yet, to reap the benefits, you must ensure your campaigns reach their intended recipients.

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Trusted AI 102: A Guide to Building Fair and Unbiased AI Systems

Numerous high-profile examples demonstrate the reality that AI is not a default “neutral” technology and can come to reflect or exacerbate bias encoded in human data. The risk of bias in artificial intelligence (AI) has been the source of much concern and debate.

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How Product Managers Can Learn to Love Reporting

Speaker: Eric Feinstein, Professional Services Manager, Looker

He will use the example of a product manager of a learning management software system and how she would go through the process of defining reporting for users of the product. Eric Feinstein, Professional Services Manager at Looker, has done workshops with product managers who are looking to add effective reporting.

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Realizing the Benefits of Automated Machine Learning

Real-world examples of companies using the DataRobot automated machine learning platform. This white paper covers: What’s new in machine learning and AI. The definition of automated machine learning and its benefits for organizations across multiple industries.

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The Retailer’s Guide to Marketing Data

Download this whitepaper to learn how innovative retailers use zero-, first-, second-, and third-party data to find their best customers and drive repeat purchases. You’ll learn: How to leverage consumer data to boost marketing ROI & customer acquisition. Techniques to build personalized campaigns & find the best prospects.