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Improving Business Decisions with Analytics

Depending on whom you ask, web analytics can have a wide variety of definitions but is ultimately focused on a single goal: understanding the online experience such that it can be improved. Making the right business decisions, especially when there is a high risk associated with poor decisions, is a challenge every business faces on a daily basis.

Here are three of the main ways analytics can work to improve decisions:

1) Make the most informed decisions to maximize ROI

Analytics is a software that generates metrics and metrics are measurements. There are all sorts of website metrics and measurements you can track. Today, any analytical platform, free or paid, can account for the most popular pages, how many pages were viewed, and many colorful reporting dashboards can be created with nominal effort. However, businesses who take full advantage of their analytics platforms are the ones who have very specific and realistic business goals and very well-defined success metrics.

Although we have gotten better over time at trying to capture an increasing amount of data and processing it into information, it has been observed that there is a much greater challenge – the challenge to take action on the information being provided by the data in a way that aligns with business goals. Looking at trends will help you highlight consistent misses or problems.  Benchmark data helps you understand how you are doing in relation to other organizations within your own sector. Overall, the data you collect should help you gain a better understanding of your customer’s needs and expectations against your competitors. It is not until then that business decisions become prioritized based on maximizing the potential impact on the business rather than reacting to daily fires.

2) Segment your customers for differentiated treatment

Market segmentation isn’t a new concept. It is a way for classifying a population into specific buckets (segments) that share common attributes. Understanding how your audience is interacting with your site is good. Knowing more about your visitors so they can be classified into specific segments is even better because treating different segments with personalized messaging and offers has proven to be invaluable to many businesses.

An effective way to implement segmentation within your organization would be to follow the following steps:

  • Define your objectives: Business objectives should be specific, measurable, actionable, realistic, and tangible. It has been proven that specific goals have a much greater chance of being accomplished than general goals.
  • Define key segments: Common segmentations in analytics consist of: new visitors, repeat visitors, registered visitors, campaign type, and referrers. Of course, numerous other segmentations are possible.
  • Measure segment behavior: Historical data for each created segment can be used as a benchmark for measuring “lifts” for any changes implemented.
  • Formulate optimization hypotheses: Create hypotheses and test those assumptions in a controlled experimentation with either an A/B or multivariate test.
  • Analyze data collected: The data collected should answer the following business question: Which treatment is more aligned with the organization’s business goals?
  • Implement changes: Based on the data collected, implement changes to any elements that you think will drive the desired segment behavior. These changes should be based on the pre-defined business objectives established at the beginning of this cycle.

3) Monitor your visitors and help predict future customer behavior

Armed with the right data and an accurate understanding of the different audiences and visitors to your site, analytics can be leveraged to estimate whether original business goals will be met. Based on historical data, plan numbers can be derived using regression analysis, which allow business issues to be discovered earlier and adjustments to be made faster.


Analytics replaces the guesswork with a scientific approach. Businesses using analytics can take hard data and confidently make important data driven decisions rather than reacting off emotions, personal preferences, or random presumptions.