Implement your Interactive projects in to better way
When we creating something interactive , usability evaluation we need to consider some main points to do our work better way and more effective.
Heuristic evaluation
A heuristic evaluation is a usability inspection method for computer software that helps to identify usability problems in the user interface(UI) design. It specifically involves evaluators examining the interface and judging its compliance with recognized usability principles (the “heuristics”). These evaluation methods are now widely taught and practiced in the new media sector, where UIs are often designed in a short space of time on a budget that may restrict the amount of money available to provide for other types of interface testing.
Although heuristic evaluation can uncover many major usability issues in a short period of time, a criticism that is often leveled is that results are highly influenced by the knowledge of the expert reviewer(s). This “one-sided” review repeatedly has different results than software performance testing, each type of testing uncovering a different set of problems.
Walkthroughs
Walkthroughs are often presented as either a static or animated slideshow or with video. Keep it short and to the point as users often skip or breeze through in order to get started. A Walkthrough explains a product or service in terms of features, benefits, and in general what the product or service allows you to do.
Most of the software out there follows rigorous design rules which draw from familiar elements that create an almost universally accepted language and information is structured in ways that facilitate usability.
If a product is essentially doing a very limited amount of simple tasks that don’t require many steps, decisions, setup or customization, there really is no need to delay direct experimentation.
A very inefficient way of using on-screen guides is showing people around the interface.
Web analytics
Web analytics is the collection, reporting, and analysis of website data. The focus is on identifying measures based on your organizational and user goals and using the website data to determine the success or failure of those goals and to drive strategy and improve the user’s experience.
Critical to developing relevant and effective web analysis is creating objectives and calls-to-action from your organizational and site visitors goals, and identifying key performance indicators (KPIs) to measure the success or failures for those objectives and calls-to-action.
A/B Testing
A/B testing, also known as split testing, refers to a randomized experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drive business metrics.
Why we should consider A/B testing
If B2B businesses today are unhappy with all the unqualified leads they get per month, eCommerce stores, on the other hand, are struggling with a high cart abandonment rate. Meanwhile, media and publishing houses are also dealing with low viewer engagement. These core conversion matrix are affected by some common problems like leaks in the conversion funnel, drop-offs on the payment page, etc.
Predictive Models
In short, predictive modeling is a statistical technique using machine learning and data mining to predict and forecast likely future outcomes with the aid of historical and existing data. It works by analyzing current and historical data and projecting what it learns on a model generated to forecast likely outcomes. Predictive modeling can be used to predict just about anything, from TV ratings and a customer’s next purchase to credit risks and corporate earnings.
A predictive model is not fixed; it is validated or revised regularly to incorporate changes in the underlying data. In other words, it’s not a one-and-done prediction. Predictive models make assumptions based on what has happened in the past and what is happening now. If incoming, new data shows changes in what is happening now, the impact on the likely future outcome must be recalculated, too. For example, a software company could model historical sales data against marketing expenditures across multiple regions to create a model for future revenue based on the impact of the marketing spend.
Most predictive models work fast and often complete their calculations in real time. That’s why banks and retailers can, for example, calculate the risk of an online mortgage or credit card application and accept or decline the request almost instantly based on that prediction.
References ( Wikipedia , usabilitygeek.com, usability.gov, vwo.com, netsuite.com)