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System and method to estimate software's Client Experience (Client Experience Predictor) Disclosure Number: IPCOM000239667D
Publication Date: 2014-Nov-24
Document File: 6 page(s) / 130K

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The Prior Art Database


Disclosed are a system and method to ensure customer satisfaction with a software product, and ultimately reduce development and maintenance costs. The novel system and method utilize a six-phase Client Experience Framework to predict the success of the end-to-end Client Experience before the customer implements the product.

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System and method to estimate software's Client Experience (Client Experience Predictor)

Software development companies are faced with the continuous costs of maintaining the software and making it available to customers. These costs typically include support of various levels, from customer support (front-end type of activity) to product support (code fixing activities). Cost is calculated in number of Problem Management Reports (PMRs) for front-end incidents/tickets and Authorized Program Analysis Reports (APARs) related to code fixes. This cost is referred to as the Cost of Warranty (CoW); it is a sum of other factors such as ease of deployment, usability of the interfaces, documentation usefulness, etc. These aspects comprise the Client Experience, as a more general definition of Quality, and represent a cost for the company

when customers require changes(e.g., the software is not in line with expectations).

Typical software development projects have best practices in place to ensure cost control. Developers identify a number of indicators in the area of quality, which affect the cost of warranty, set goals to improve quality from release to release, and estimate the warranty cost by predicting the number of PMRs and APARs for that particular release. Currently, developers predict quality by estimating the defects and PMRs - CoW as Cost (PMRs) + Cost (APARs). However, this does not take into account all phases of the client's experience.

The problem is that there is no way to predict and assess the overall Client Experience as a more general indicator of customer acceptance post-shipping. A method is needed to provide such an indicator to allow software development teams to take the appropriate corrective actions.

The novel contribution is a system and method for predicting the success of the end -to-end Client Experience before the customer implements the product. The proposed method establishes metrics to determine baselines, set goals, and evaluate the overall Client Experience, thus providing more accurate metrics for predicting the Client Experience (Cost of Warranty plus other metrics).

Rather than keep all pre-General Availability (GA) indicators in a typical quality certification process in the "Delivery" and "Usage" areas, with objectives set in quality plans and assessed before the release ends, the novel approach presents a complete view; allowing business decisions to be made according to the type of market or segment the product owner wants to address . Moreover, if compared to the prior art, the novel method provides a unique final indicator to express the forecasted customer experience. Currently, the product owners do not have this type of view. The best, yet inadequate, indicator is a projection of defects that post-GA customers are likely to experience. Current methods lack an indicator for the level of acceptance from the customer, measured from the first time the customer gets in touch with the products to...