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Transforming data into informed business decisions
Saurav Verma, Senior Marketing Manager, 99Labels.com
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A meagre 18% of online businesses use web analytic data to make business decisions; reported a survey conducted by E-consultancy and Lynchpin.  Surprised? Well I am and I wonder why because the beauty of online marketing is our ability to track, measure, analyze and test our marketing efforts.

Data – A problem of plenty

For a very long time online marketers starved for data about their websites, data that could tell them about their website visitors – who they were, where did come from, what actions did they perform, etc. Enter web analytic and marketers had more data than they could sometime possibly use.

Conventional wisdom suggests that the more data we have about our website visitors, the more likely we are to make informed business decisions. However, there is a growing belief among marketers that excessive amount of data is now a part of the problem and not a part of the solution.

Too much data can be overwhelming and therefore it is imperative to understand – How much data do you need to make actionable business decisions and thereby maximize revenues?

Information overload

Take a look at the instrument panel of an airplane and you will get a sense of information overload. But seasoned pilots can easily identify primary gauges and instruments and can easily digest all necessary data required to fly the plane. More importantly, they know exactly where to look to verify the intended effect of the control input made by them. So if they increase power to the engines they would look at altimeter, airspeed, etc. to check the intended outcome. Actionable web analytics is a lot like this.

Most business owners feel the same sense of information overload as a non pilot does when looking at web analytic data, especially in the absence of formal training or experience. It is a daunting task to segregate data/information which is relevant to make business decisions from bits that are extrinsic.

Data Synthesis – Transforming data into action

Most online businesses these days are armed with web analytic tools though its utility is mostly confined numbers and pretty charts. Actionable information which can be used to optimize marketing efforts, increase conversion rate and customer retention is completely missing.

By answering few basic questions, business owners can easily synthesize a lot of raw data into actionable insights. Listed below are a few questions that will help you navigate the data maze.

  • Where are they entering?

Regardless of the analytic tool you use, it is fairly straightforward to identify the top landing pages of your website. You will be surprised to see that a large number of visitors do not enter your website via the home page.

This data point not only shows you the top landing pages (which can be fine tuned to improve performance) but also highlights non performing pages which need to be tweaked and tested for performance enhancement. This data point is also critical to conversion path analysis and optimization.

  • How are they entering?

Visitors come to website via various sources and can be easily grouped into organic search traffic, paid search traffic, direct traffic, etc. In case of organic and paid search traffic, the keywords that brought visitors to your site can help you understand your visitors.

  • Expectations

Each keyword portrays a searcher’s intent and expectation and can therefore be used to align your services (and the landing page) to meet their expectation. The more you meet up to their expectations, the better conversion rates you will have.

Visitors who come to your website after searching for your brand name or a line of product you sell are in an advanced stage of buying and more likely to convert. The treatment to this bucket of visitors has to be slightly different. 

  • Likely goals

Different set of people may use the same keyword with different expectations and it is not uncommon for business owners to miss some of the likely goals. For example: A person searching for “discount online stores” could be looking for discounted apparels to buy whereas someone else could be looking to buy discounted television.

By mapping each keyword to as many likely goals as possible and aligning your offer (and the landing page) to it will yield rich dividends.

In addition to this, marketing budgets can be suitably allocated by identifying top performing sources in terms of conversion rate. Here, it is imperative to note that certain traffic sources will most likely outperform others due to their inherent nature.

  • How are they navigating?

After having identified the top landing pages and likely expectations and goals of your website visitors, the next step is to look at the pages they navigate to in tandem with the landing pages.

After having identified the most popular ‘next’ pages, the job of the business owner is to see if:

  • The popular ‘next’ pages are the logical ‘next’ pages in the conversion funnel
  • These pages have strong call to action element and are accessible via top and/or side navigation bar
  • These pages answer all potential questions a visitor may have during the buying process.

By optimizing each step (page) of the conversion funnel, the overall impact on the top line revenue can be manifold.

  • Why are they leaving?    

Bounce and exit rate are other two common data sets to be watched at all times. Unless visitors can perform a predefined action on the same page, a high bounce rate for the page is bad.

In case of a landing page having high bounce rate, it is commonly assumed that the page is terrible at assuring visitors that they have come to the right place when it could also mean that the quality and/or type of visitors being sent to the page is wrong.

Exit rate could mean a few different things.

  • Planned and unplanned exit

Some exits are meant to be. You don’t expect a visitor to stay on after having performed the desired action i.e. from a “thank you” page.

After indentifying pages with high exit rate in the conversion path, look at major entry paths to that particular page to ascertain if there exists a mismatch of intent between the two pages.

  • Time of page

A visitor leaving a page within a few seconds is not the same as the one leaving it after a few minutes. The first is most probably triggered by wrong product or service whereas the latter is mostly due to lack of information/confidence.

And last but not the least – testing, the most important aspect of actionable analytic and my personal favourite. After having identified possible bottlenecks in the conversion path, it is imperative that you implement recommended change and test performance, one at a time. And to end my longish deliberation, I would like share with you a quote from web analytic guru Jim Sterne – “Web analytics reports are just lumber. It takes an architect, a designer, a builder and a lot of other skills to turn it into a house.”

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