The data and analytics space is booming and changing how we analyze and use data across industries.
This boom has only been further accelerated by the recent pandemic as industries are shifting to digital solutions to address expanded market opportunities.
This is also why companies that monetize their data – Google, Amazon, Uber, and others – are among the most valuable in the world (both in terms of market capitalization and innovation).
But how can you harvest the power of data and analytics for your organization? A good starting point is understanding the breakdown of the type of data available to you.
Quantitative data refers to data that can be counted, measured, or assigned a numerical value.
Quantitative variables answer questions such as “how many” or how frequently.” In terms of Customer Experience (CX) data, quantitative data would measure click-through rates, bounce rates, or time-on-site rates. The most common form of analysis for quantitative data is statistics: it collects, models, and presents larger amounts of data to infer patterns.
Both types of data come with significant advantages and disadvantages.
For example, quantitative data tends to be more straightforward and less prone to subjectivity or errors. But on the flip side, a quantitative approach cannot tell you the full story and thus could be inconclusive or overlook broader patterns.
Meanwhile, qualitative data provides contextual, predictive, and in-depth insights. But it is not always statistically representative and can be biased based on the host, respondents, questions, and other variables.
Hence, for a complete analysis, using both quantitative and qualitative data yields optimal results.
Using an optimized mix of quantitative and qualitative data is particularly powerful in optimizing your CX.
While there are many applicable use cases, there are three that should serve as every organization’s building blocks regardless of its product, service, industry, or market.
1. Optimize Your User Research to Inform All Of Your CX Decisions
Regardless of what product or initiative you’re working on, optimizing your user research process will be critical to your success.
Excellent user research doesn’t just help you organize a test or redesign a website. It helps you segment your target customers, prioritize items on your roadmap, and even inform your blog posts.
2. Use Customer Behavior Data to Drive Revenue
And there are 3 key ways to drive business impact with customer behavior analytics.
3. Leverage Observability to Power Business Transformation
Companies have been monitoring application performance for almost as long as we’ve had applications. But new trends (hybrid infrastructure, microservices, edge computing, etc.) make it difficult for traditional tools to keep up. And observability bridges this gap, bringing advanced analytics – both quantitative and qualitative – to applications running in a variety of modern environments.
While monitoring only collects the data from the system and alerts you to something is wrong, observability goes beyond monitoring to interpret the data. Observability helps provide answers about why something is wrong and how to fix it, allowing teams to pinpoint the root cause, minimize downtime, and increase operational efficiency.
And as companies move to modern observability platforms, they start to see the benefits in performance and availability. These benefits further accelerate as companies move along the maturity curve.
Germain UX is an end-to-end, GLDP-compliant application performance management, monitoring, observability, analytics, and automation software platform built to improve User Experience in the broadest sense of the term (e.g. User behaviors, Workflows, etc).
Depth of insights is key and provided at Behavioral, Process and Technology levels. Real User Recording and Replay offers millisecond precision, so it records everything a User “sees” and “does”. Yet Germain UX is GDPR compliant so that data privacy is respected at all times.
Germain UX is very customizable, so your organization can scale and always count on it to deliver the analytics and automations your organization needs. It can be configured in any way you want to monitor and manage the performance of your software and hardware, analyze user experience in real time, predict issues, and automate transactions to proactively resolve issues.
It works best if given access to your entire infrastructure and can be deployed on-premise, on your cloud, or our cloud. Get in touch with our team if you’re interested in learning more.
Regardless of the massive opportunities ahead, most organizations have yet to successfully monetize data, which will take a proactive strategy, investment, key talent, and other conducive strategies.
Thus, much more work remains to be done. Plus, a successful data strategy will have to be fully customized to an organization based on data availability, strategy, market, product or service, and much more.
For example, Dow Chemical started with a significant data problem. The organization had hundreds of dashboards and thousands of reports, but none of that information was generating better decisions. So Dow Chemical reviewed usage metrics and used that feedback to identify and solve unresolved user obstacles. The result? The platform’s consumption increased by 25% while the business value of Dow’s enterprise analytics and BI solutions grew by 4.2x.
Similarly, Turku City Data’s created an analytics framework that organized all data at a level of abstraction (such that every data point represented a person, object, location, or event). The company used this frame as a common language to explore business problems in their contextual and structural richness.
Lastly, instead of looking at data they already had, the ZF Group selected markets to target and took a close look at what type of data would create value for that market. They then created data that did not previously exist.
And those are just a few success examples for inspiration to get your organization started on its data and analytics journey.