Low-Code development is the way to build apps more quickly by reducing the need to code. But that’s not the whole story. Continually evolving expectations are forcing you to accelerate operations, improve the customer experience, and be nim…
When you step back and look at the big picture, the rise of RPA represents a pivot from people to software, from high-volume, highly transactional manual processes, to the emerging digital workforce—a fast moving pivot. As a bu…
Organizations need new skills to effectively implement an expanding set of digital capabilities, such as artificial intelligence (AI), deep learning, the internet of things (IoT), and robotic process automation (RPA). Deploying digital technologies one…
New technologies—and the opportunities connected vehicles present—are changing the way automotive industry players need to think about value chains, business processes, and data management. Automotive leaders are embracing intelligent au…
Low-code is a game changer on many levels. It can accelerate development by 20x over traditional full-stack coding, and business context can be incorporated into development continuously. Yet the acceleration enabled by low-code platforms has thrown…
Automation has been on a steady march through business for more than 200 years: nevertheless, the past three years or so have seen a huge step-change in the variety of technologies being promoted to help businesses automate aspects of their work. Gi…
New customer expectations across all facets of engagement are challenging how traditional contact centers operate. Pressure is building to optimize customer experience, improve agent productivity, and deliver on strategic business initiatives. But, …
As many businesses work on improving the customer experience, they look to efficient, cost-saving technologies like IVR and chatbots. These avenues often seem the most logical for customer service managers who are charged with cost-cutting, but they of…
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Many companies put analytics projects on the back burner for so long they eventually fall off the “analytics cliff.” They see minor indicators of trouble—such as declining average sales price or increased customer churn—and assume they’ll continue to be incremental. Plenty of time to implement a different service pack and address analytics in the next release, right?
Wrong. It’s not a slow decline, it’s a cliff. And application teams risk falling straight off it. Fortunately, if you know what to look for you can act quickly to avoid a catastrophe. Companies that are approaching an analytics cliff will pass clear indicators before they fall. This eBook outlines the five most common indicators your embedded analytics are failing you. |
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Why do some embedded analytics projects succeed while others fail? Many application teams don’t realize that the features they embed and how they develop them have a lasting impact on revenue, customer retention, and competitive differentiation.
We surveyed 500 application teams embedding analytics to find out what separates successful projects from failed ones. In the 6th annual State of Embedded Analytics Report, you’ll learn:
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