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    Getting More than Just Numbers from Your Web Analytics

    Web analytics has established itself as a major topic for discussion when planning for a Web application and building a business case. Before, Web analytics was often something added onto applications as an afterthought. Today, it is regarded with much higher priority and considered to be a powerful tool that can provide a number of business benefits. Businesses looking to better understand user behavior and application usage can utilize Web analytic tools to collect, analyze, measure and report on Internet data. However, it is important that businesses have planned for and understand Web analytics in order to take full advantage of the benefits it provides.

    Based on his experience with business development, business analysis, requirement management and, of course, Web analytics, Kishore Babu Nandanamudi, the lead business consultant at Virtusa, outlines 14 ways to make Web analytics more actionable and achieve the associated business benefits.

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    Click through for 14 ways you can make your Web analytics more actionable from Kishore Babu Nandanamudi, a lead business consultant at Virtusa.

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    What does it mean if users are visiting a particular section of help very often, or not using certain features at all? Web analytics can help the training team identify user difficulties and training needs by capturing the usage data. Since this data is supported by customer usage traffic, the training team can build tailored training solutions for their customers.

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    Web analytics provide a great platform for analyzing how a new feature is perceived by the market. Usage statistics can tell you if marketing efforts are enough to encourage clients to try the new feature and can help you understand if there are any specific market needs.

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    Customer centricity offers sustainability and long-term revenue. Web analytic tools offer ways to help the customer get the most value out of their investment. For example, a client’s ROI can be best optimized by analyzing their usage statistics and determining the right feature and entitlement mix.

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    Usage can be monitored for third-party content and tools used. This data helps in analyzing various investment decisions. Let’s say an application is using “News” content services from a third party. Based on usage statistics, management can justify the investment made, consider renegotiating the royalty/license fee if the feature is sparingly used, or evaluate building in-house expertise if the feature becomes a selling point, in order to reduce dependency.

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    It is possible to conduct “selling point research” using Web analytics to identify what additional functions and entitlements customers are interested in. Usage can be studied at different levels such as the customer level (company-wide statistics) or the user role/ level. These different benchmarks can be useful references while drafting customer-specific upselling strategies and for identifying selling points to new customers who have similar profiles to those of existing customers.

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    Trial users can be monitored by their application usage so that eventually they can be converted to subscribed/paid users. Using Web analytics, you can identify critical success factors for trial to non-trial user conversion such as frequency of usage. Web analytics also enable you to see which features are being tested by the user, analyze the failed cases, and subsequently use focused marketing and training efforts to target infrequent trial users.

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    Web analytics can reveal active and inactive clients and their usage during a specified time period. Inactive accounts, over a period of time, will tend to terminate their subscriptions, which affects revenue. Using this data, financial performance can be evaluated for the next period and this information can be communicated to the business so necessary risk mitigation actions can be taken.

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    Web analytics can measure order conversion rate by tracking how many items users added to their shopping cart and how many of them fall-out from order conversion. Similarly, while registering for a new product, the tool can measure how many users fall-out from completing their registration. Fall-out may be due to either requiring the customer to enter too much information or due to too many clicks during the process. Using Web analytics, complete path analysis can be done to optimize the UI flow so that the success rate can be increased.

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    Usage stats can inform the sales team if a customer is overusing the number of subscriptions bought by sharing their IDs. The sales team can use this information to notify the respective customer or use it as an upselling opportunity.

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    Loyal visitors can be counted on for assured revenue. Visit frequency determines the level of visitor loyalty to the application. Higher frequency generally indicates higher loyalty. Frequent reports can be generated on usage to study visitor loyalty and subsequently, appetizers can be sent to the visitor to entice him or her to use the application more frequently.

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    Printable or digitized welcome kits can be sent to all the new users who are registered and visiting the application for the first time. Personalized welcome kits sent after carefully reviewing user profiles will improve first-time visitor experience. Reports can be generated for all first-time visiting users along with other necessary information generated from Web analytics.

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    Web analytic tools allow you to establish correlations between two traffic variables that need to be studied in context. For example, how many users visited the application during last month from Japan? Or, how many users viewed a search result with highlighting on? Better correlations and the ability to drill down capabilities at various levels facilitate decision-making in new feature development.

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    At times, there may be a technical snag in a key functionality that needs to be communicated to a select audience. Web analytics offers a way to identify those who used that functionality in that specified time period, which reduces redundant communication to other users. Also, when a feature is upgraded, feedback can be obtained by reaching out to select users who use it most.

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    Web analytic tools can track browsers, OS, locale and bandwidth/domains used by the users while accessing the application. Application testing efforts can be invested in these areas accordingly so that UI experience can be optimized.

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