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Good Points Blog

using data to make business decisions

Controlling risk and optimizing performance through data-driven decisions

Every decision an organization makes has a cost – whether it’s as commonplace as sending email A or email B or as pivotal as choosing between multi-million-dollar software solutions. And while there’s no single right way to come to those decisions, program managers and executives open themselves up to inherent vulnerability when making strictly intuition-based decisions. When reinforced by data and analytics, however, decisions can be made on insight and sound guidance without relying on intuition alone.

Organizations have their own internal analytics resources, work with external data partners, or oftentimes use a combination of both. However it is handled, having designated resources to spearhead data collection and analysis is critical to the organization’s success. This is particularly true in the case of customer loyalty programs. After all, when an organization’s most valuable customers are affected, so is their bottom line.

“Your intuition can sometimes lead you astray with potentially dire consequences or missed opportunities,” said Rachel Bicking, Senior Vice President of Data and Analytics at Connexions Loyalty. “Investing in data and insights can help you avoid significant missteps and also identify new growth opportunities undetected by intuition. Data-driven decisions can translate into a more seamless and remarkable customer experience that ultimately distinguishes an organization from its competitors.”

One of the most important uses of data and analytics is to support organizational risk and reputation management, including support for both internally and externally impactful decisions.

“When an organization utilizes its data, and has the capability to effectively manipulate and analyze that information, they’re able to better identify problems, underlying causes, potential solutions, and their financial implications,” said Bicking. “They can leverage this information to help inform future recommendations that improve the chances for business success.”

High Frequency, Low Value

To illustrate the point, in the case of a global financial institution, Connexions recently conducted an analysis on their seven customer clusters. Initially, the client’s intuition had them believing that a given cluster was going to be the most valuable due to its relatively high purchase frequency – however, after Connexions dug a little deeper using a data-driven approach, it was discovered that the cluster was buying in bulk and was actually lower value. By leveraging data insights Connexions had for similar customers, we were able to increase revenue by converting them into high-value bulk buyers.

productive time on site

For another national financial institution, we used web traffic data analysis to outperform conventional thinking and intuition. Typically, when a customer is on the site for a long time, they’re likely not finding what they need. That said, with our analysis we found that if someone stayed on the site in excess of 9 minutes, they were three times more likely to convert. In fact, performing a flight search and viewing 1-2 pages of results, or performing a hotel search and viewing 1 page of results, showed even higher conversion rates.  Therefore, the key metric isn’t necessarily time spent on the site, but productive time spent. We found that valuable customers are willing to invest the time if they are finding what they need.

The foundation of informing your decisions is collecting as much transactional and behavioral data about your business interactions and your customers – from what customers are searching for to how frequently they’re converting to what they’re complaining/happy about. Making this investment pays off in the longer term by helping organizations go beyond their intuition to instead creating a gold mine of insights that inform its strategies and decisions.

 

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