11 Ways Data Analysis Can Boost Your Bottom Line

 
 
By Karen A. Frenkel  |  Posted 10-22-2014 Email
 
 
 
 
 
 
 
 
 
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    Don't Measure Everything
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    Don't Measure Everything

    It is best not to calculate everything. Concentrate on a few macro, actionable metrics, like revenue per customer or the cost to acquire new customers. Every action you take should be to affect one or more of these metrics. Measure before and after to see if you changed anything.
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    Know Your Customers Well
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    Know Your Customers Well

    To get beyond demographics, location and other standard user metrics, use session or event data to further segment and identify user groups. Their behaviors may be unique to how they interact with your product, which could help predict future actions.
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    User Behavior and Social Media
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    User Behavior and Social Media

    Integrate data from internal and external sources, like social media, to get a 360° view of the customer. If someone tweets immediately after a purchase on your site, you want to know whether they're saying good or bad things about the product.
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    Analyze Data in Real-Time
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    Analyze Data in Real-Time

    Real-time, in-session analytics make a huge difference. They help drive new revenue with customized offers and recommendations, targeted advertising, and custom user paths. Real-time analytics can also help save costs with fraud detection, network monitoring and inventory management.
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    Examine Entire Data Sets
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    Examine Entire Data Sets

    Study all your data, not just a sample. You must be able to search, analyze and visualize granular transactional data and web and mobile data on a massive scale. This will give you the true, full picture.
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    One Size Cannot Fit All
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    One Size Cannot Fit All

    A single analytics product cannot solve the data and analytics requirements mentioned in the previous. Find complementary tools to co-exist with your organization's analytics infrastructure, especially ones that don't require wholesale retooling of the infrastructure and personnel's skill sets.
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    Your Data Is Temporal
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    Your Data Is Temporal

    Examine data across all time-horizons, such as historical, current and predictive, especially for automated decision-making. This helps expose time-related variability, like seasonal effects.
  • Previous
    Statistics Is Your Friend
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    Statistics Is Your Friend

    Multidimensional statistical analyses, like regression analysis, market basket analysis and other mainstays of advanced analytics reveal correlations quickly and better slice and dice your data.
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    Simulate Many What-If Scenarios
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    Simulate Many What-If Scenarios

    Simulations can help you quickly test models and assumptions. You need to perform free form, what-if analyses to forecast alternatives without having to define rigid data models upfront.
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    Experiment Early and Often
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    Experiment Early and Often

    A/B test assumptions about your products and marketing campaigns and engage in other controlled experiments to gain insights quickly. This testing will lead to better-informed decisions.
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    Share Insights Broadly
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    Share Insights Broadly

    Share across your entire organization, not just at the executive level. Empower employees on the front lines to make better day-to-day decisions with the right analytics. For example, give customer support staff real-time information on what the customer did with a product just before he or she called the support line.
 

Companies recognize the need to analyze the data they amass, but the ROI is often unclear. Depending on the organization, industry and type of data at hand, analysis can either lead to lucrative insights or come up dry, according to Dev Patel, CEO and founder of BitYota, a data analytics company. Clearly, many companies also want to hire data analysts, as Gartner Group recently reported. By 2015, big data will produce 4.4 million jobs globally, making data analyst one of the world's most in-demand jobs, according to Gartner. CIOs should understand how to deal with hybrid data, the combination of structured and unstructured data, and how to shine light on dark data, which is collected but unused despite its value. Future-leading organizations will be distinguished by the quality of their predictive algorithms, says Peter Sondergaard, Gartner senior vice president and global head of research, who adds: “This is the CIO challenge, and opportunity." Below is 11 nuggets of advice from Patel, who discusses how data analysts can increase revenue for their company and help solve the ROI problem.

 
 
 
 
 
Karen A. Frenkel writes about technology and innovation and lives in New York City.

 
 
 
 
 
 

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