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Business intelligence vs. predictive analytics: Turn key differences into advantages

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While many companies use these tools to better utilize the big data at their disposal, a quick Google search shows that these are still common questions. Business intelligence and predictive analytics are often used interchangeably to describe tools and methods for utilizing data to make informed decisions. A brave new data world.

Data 26
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Being Engaged at Work Is Not the Same as Being Productive

Harvard Business

While many studies suggest that increased employee engagement leads to improved business results in aggregate, a deeper look at the data suggests that this may not always be true at an individual level. At the second company, the data told a different story. Company 2: No Correlation.

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6 ways to renew (and stick to!) your CX vows

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Data is at the core of any customer experience strategy. You can also use data collection to build a more nuanced understanding for the “why” behind your customer journey maps. 3 questions to ask during this step: What metrics will you use to benchmark and improve the customer experience?

Metrics 26
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How One Company Made Its Analytics Investment Pay Off

Harvard Business

In the age of rapid advances in data science and artificial intelligence, many organizations still struggle to incorporate advanced analytics capabilities into their business models. Second, the ABU team is paid using variable compensation, based on projects that have been fully implemented and based on their ROI.

Company 28
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4 Ways Leaders Can Get More from Their Company’s Innovation Efforts

Harvard Business

While the execution of a conventional strategy lends itself to linear progress and clear benchmarks, innovation often proceeds by S-curves , moving at a slow crawl until it explodes at an exponential rate. That’s why good managers put so much focus on measuring and managing return on investment (ROI) as a basic operational practice.

ROI 28
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Track Customer Attitudes to Predict Their Behaviors

Harvard Business

The argument is that in-depth behavioral data already encapsulates underlying attitudes, and because decision makers are mainly concerned with customer behavior, there is not much need (any more) to worry about underlying attitudes. But downplaying attitudinal data seems rather too convenient.

Survey 28
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4 Ways to Improve Your Content Marketing

Harvard Business

With online technologies and targeted lists, this should be a cost-effective tool for separating the suspects from the prospects, accelerating customer conversion through the sales funnel, and, equally important, optimizing “data-driven marketing” by tying each piece of content to metrics like opens, reads, downloads, and so on.