Interaction design evaluation

The golden rule that every designer must remember is not the user.The purpose of user interface is to improve the usability,understanding,and intuitiveness of product and services for users.We may design an assessment strategy and validate user interfaces using evaluation techniques and usability testing .

In this article I'm going to describe 5 evaluation methods.

1.Heuristic evaluation

2.Walk-throughs

3.Web analytics

4.A/B testing

5.Predictive models

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 specially involves evaluators examining the interface and judging its compliance with recognized usability principles. These evaluation methods are now widely taught and practiced in the new media see for,whereUIsare offer 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.

The main goal of heuristic evaluation is to identify any problems asso3with the design of user interfaces.Usability consultants Rolf Molich and Jakob Nielsen developed this method on the basis of several years of experience in teaching and consulting about usability engineering. Heuristic evaluation are one of the most informal methods of usability inspection in the field of human-computer interaction .

There are many sets of usability design heuristicss.they are not mutually exclusive and cover many of the same aspects of user interface design. Quite often,usability problems that are discovered are categorized. Often on a numeric scale according to their estimated impact on user performance otlr acceptance. Often the heuristic 3is conducted in the context of use cases to provide feedback to the developers on the extent to which the interface is likely to be compare with the intended users’ needs and preferences

Advantages of heuristic evaluation

· Helps to identify and fix usability issues

· A relatively quick method of gathering website feedback

· Can be relatively inexpensive as it doesn’t require much time and can utilise in house resources

Limitations of heuristic evaluation

· If your evaluator aren’t impartial biascan creep into the process. After if you have already worked on the website,it can be hard to maintain a fresh mindsetin which to conduct the heuristic.

· Doesn’t cover all issues in isolation,user research and analytics are also required to discover extra insight.

Walk-Throughs

A walk through is a peer evaluation of a product/system people who are roughly at the same level in the company gather to evaluate and discuss a piece of software methodically.

The walk through’sgoal is to discover as many problems as possible,not to solve problems. Critiques should be as favourable as possible and should be restricted to the portion of the presentation delivered by the presenter.

Structured walk throughs have been shown to be one of the most successful way for gathering feedback and improving software quality.

How to design a walk through

A design walkthrough is a quality practice that allows design to obtain an early validation of design decisio3related to the development and treatment of content,design of the graphical user interface,and the elements of product functionality. Design walkthroughs provide designers with a way to identify and assess early on whether the proposed design meets the requirements and addresses the project ‘s goal.

Use following steps to plan,conduct,and participate in design walkthroughs

1. Plan for a Design walkthrough

A design walkthrough should be scheduled when detailing the micro -level tasks of a project.

2. Get the right participants

It is important to invite the right participants to a design walkthrough.the reviewer should have the appro3skills and knowledge to make the walkthrough meaningful for all.

3. Understand key roles and responsibilities

All participant in the design walkthrough should clearly understand their role and responsibilities so that they can consistently practice effective and efficient reviews.

4. Prepare for design walkthrough

All.participantsneed to prepare for the design walkthrough. One cannot possibly find all the high-impact mistakes in a work product that they have looked at only 10 minutes before the meeting. If all participants are adequately prepared as per their responsibilities,the design walk5is likely to be more effective.

5. Use a well structured process

A design walkthrough

Should follow a well structured,documented process. This process should help define the key pur3of the walkthrough and should provide systematic practices and rules of conduct that can help participants collaborate with one another add value to the review.

6. Review and critique the product,not the designer

The design walkthrough should be used as a means to review and critique the product,not the person who created the design. Use the collective wisdom to improve the quality of the product,add value to the interactions and encourage participants to submit their products for a design walkthrough.

7. Review,do not solve problems

A desig walkthrough has only one purpose,to find defects. There may,however,be times when participants drift from the main purpose. A moderator needs to prevent this from happening and ensure that the walkthrough focuses on the weakness rather than identifying fixes or resolutions.

Web Analytics

Web analytics is the methodological study of online/offline patterns and trends.It is a technique that you can collect,measure,report and analyzeyour web site data.The focus is on identifying measures based on your organisational and user goals and using of those goals and to drive strategy and improve the user’s experience.

Important of Web Analytics

We need web analytics to access the success rate of a website and its associated business.Using web analytics we can,

· Have a clear perspective of web site trends

· Access web content problems so that they can be rectified

· Figure out potential key words

· Demonstrate goals acquisition

· Find out referring sources

· Identify segments for improvement

Web Analytics Process

To optimise the web site in order to provide better user experience is the primary objective of carrying out web analytics. It provides a data-driven report to measure visitors’ flow throughout the website.

The following picture depicts process of web analytics

These are the steps of the web analytics process

1. Set the business goals

2. To track the goal achievement,set the Key Performance Indicators (KPI)

3. Collect correct and suitable data

4. To extract insights analyse data

5. Based on assumptions learned from the data analyses or websitetesting,Implementinsights.

Web Analytics Tools

These tools offer an easy and inexpensive way to know everything about your website.

Eg: Google Analytics Chartbeat

Spring MetricsKissmetrics

Woopra User Testing

Clicky Crazy Egg

MintMouseflow

A/B testing

A/B testing also known as split testing or bucket testing. A/B is a user experience research methodology.This tests consist of a randomized experiment with two varients,A and B(web page,page element).It includes application of statistical hypothesis testing or “two sample hypothesis testing” as used in the field of statistics.

Why we should do A/B testing

· To solve visitor pain point

· To get better ROI from existing traffic

· To reduce bounce rate

· To make low risk modification

· To achieve statistically significant improvements

· To redesign website to increase future business gains.

What can you A/B test

Your website’s conversion funnel determines the fate of your business. Therefore even piece of content that reaches your target audience via your website must be optimised to its maximum potential. This is espresso true for elements that have the potential to influence the behaviour of your website visitors and business conversion rate.

How to perform an A/B test

AB testing offers a very systematic way of finding out what works and what doesn’t work in any given marketing campaign.

1. Research

Before building an A/B testing plan we need to conduct through research on how the website is currently performing. You will have to collect data on everything related to how many users are coming onto the site,which pages drive the most traffic etc.

2. Observe and formulate hypothesis

Get closer to your business goals by logging research observations and creating data-backed hypothesis aimed at increasing conversions.

3. Create variations

Create a variation based on your hypothesis and A/B test it against the existing version(control)

4. Run test

Before we get to this step,it’s important to zero upon the type of testing method and approach you what to use.

5. Analyse results and deploy changes

Analysis of the results is extremely important because A/B testing calls for continuous data gathering and analysis,it’s in this step that your entire journey unravels.

A/B testing tools

HubSpot’s A/B testing kitCrazy Egg

VWO A/B Tasty

OptimizelyFreshmaketer

Omniconvert Convert

Predictive models

Predictive modelling also called predictive analytics,is a mathematical process that seeks to predict future events or outcomes by analysing patterns that are likely to forecast future results

Applications of predictive modelling

Predictive modelling is often associated with meteorology and weather forecasting,but it has many application in business.

Bayesian spam filters use predictive modelling to identify the probability that a given message in spam.

Modelling methods

1. Decision trees

Decision tree algor3take data(mined,opensource,internal)and graphs it outin branches nto display the possible outcomes of various decisions. Decision trees classify response variables and predict response variable based on past decisions,can be easily explainable and accessible for novice data scientists.

2. Time series analysis

This is a technique for the prediction of events through a sequence of time. You can predict future events by analysing past trends and improves and therefore predictions can be made.

The most comp5area of productive modelling is the neural network. This type of machine learning model independently reviews large volumes of labeled data in search of correlations between variables in the data.

Common algorithms for predictive modelling

· Gradient boosted model

An algorithm that uses several decision trees,similar to RandomForest,but they are more closely related.inthis,each tree corrects the flaws of the previous one and builds a more accurate picture

· K-Means

Groups data points in a similar fashion as a clustering model and is popular with personalized retail offers.

Predictive modelling tools

Sisense

Oracle Crystal Ball

IBM SPSS Predictive Analytics Enterprise

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