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Month: August 2017

18th of August — 2017

Why Growth-Driven Design is Critical to the User Experience

Chris Risner

G rowth-driven design (GDD) is the answer to the frustrations of such businesses. Simply put, GDD is the process through which websites are structured in a manner that optimizes traffic, focuses on the user experience, and results in the growth of the business.

Most dread when the time comes to redesign their website. They know that a fresh and more productive look is overdue, but they are horrified of the long and costly process that lies ahead of them. As such businesses weigh their options and continue to procrastinate redesigning their website, they repeatedly incur losses and slower growth due to the poor user experience on their current website.

Growth-driven design (GDD) is the answer to the frustrations of such businesses. Simply put, GDD is the process through which websites are structured in a manner that optimizes traffic, focuses on the user experience, and results in the growth of the business. With growth-driven design, businesses can prioritize on the implementation of the highest impact changes to their website, allowing them to avoid wasting time and resources on designing an entire website that does not lead to growth opportunities for the business.

Traditionally, businesses would redesign their entire website during a one-time period that was costly and lengthy to implement (anywhere from 3 months to 2 years). Such a strategy involved heavy investment in a project that contained high levels of risk and unpredictable results. The new website would be built almost entirely on assumptions, and with no strategy for continuous improvement.

How Growth-Driven Design impacts the user experience

The growth-driven design gives rise to a scalable and more adaptive website that is based on actual user engagement in order to provide opportunities for continuous improvement.

There are several critical components that define the internet users of today. These characteristics represent the pain-points of these users and how growth-driven design can be used to implement more engaging user experiences.

Short attention spans and Attractive visuals

With all the information that is out there today, the attention span of most internet users has been reduced to less than that of a gold fish. To put a number on it, most users have an attention span of less than 8 seconds before their minds wander to the next thing on the list. Therefore, the challenge for designers and web developers is to get their message across in the shortest time possible.

One of the best ways to do this is through creating attractive visuals. Hubspot has uncovered that a message along with a relevant image attracts 98% more views. Through growth-driven design, a business can begin to strategically tailor its message around strong visuals that align with the brand and the messaging technique. They can then use the user response and engagement to continuously improve this messaging design.

Adapting to Mobile

More internet users are relying on mobile devices to browse the internet. In fact, slightly over 52% of people worldwide are using smartphones and tablets (over desktops) as their main devices for surfing the web. Growth-driven design, therefore, aims at optimizing websites for easy viewing on mobile devices.

A best practice for growth-driven design is to develop a website for mobile before scaling up to larger screens. In this way, challenges with mobile viewing can be appropriately addressed before taking the next step. And because mobile devices may not have steady and reliable internet connections, the website is designed to be responsive even to poor environments of connectivity in order to minimally interrupt the user experience.

Attractive Content

One of the main concepts of growth-driven design involves engaging users with attractive and relevant content. A website that is structured around such layers of material draws traffic and immerses users into the overall experience. Creating powerful content requires deep audience engagement and user research in order to develop personas and to understand what the customers need.

With growth-driven design, businesses can develop and continuously improve their content based on actual user engagement. They can also optimize material for specific groups of users, based on responsiveness, quality, tone, and style. 

Easy Navigation

Today’s internet users are impatient. They desire smooth customer experiences that have minimal interruptions. If a business’s website is choppy and has many layers of sub-pages that make the overall browsing experience slow and disruptive, users will tend to engage less with the website. The message will also be lost upon the users.

Growth-driven design emphasizes a single page layouts, where parallax scrolling allows developers to fit more content onto a single page without disrupting the customer experience. With parallax scrolling, an illusion of depth is created on the page through a blend of background and foreground images.

As the user browses across content, each segment that the person highlights is shown in the front, while background content is slightly blurred out. Different sections of material are highlighted as the user navigates the page. The end result is an immersive user experience where customers are exposed to more content and attractive visuals.

Key Components of Growth Driven Design

Developing a Strategy

In line with tailoring growth-driven design efforts to suit the user experience, businesses need to develop a strategy that incorporates the goals of the business and the personas that the company wants to interact with. The first step is therefore to develop a “wish list” of what the company would want to achieve when users come to their site.  This can serve as the foundation for the website because the initial version will contain the must haves, i.e. the most important website components.

When developing a growth strategy, understanding the needs of customers will be key towards designing the user experience. Businesses should dive into the customer’s world and try to understand how they can solve the problems that users experience when navigating websites.

A business will be quickly on the path towards launching a new and improved website if they have a clear strategy. The decisions that should guide strategy include clear objectives that will reduce the need for constantly revising the website in its early stages, focus on customer needs and pain-points in order to develop an immersive user experience, and executable plans that turn wish lists into actionable ideas that can be implemented to achieve tangible results.

Designing the Launch Pad

In growth-driven design, a launch pad refers to the foundation upon which a business can build a website that is geared towards performance improvement and continuous growth. The launch pad is not the final product, but a solid foundation upon which users can begin to engage with the new business outlook. The company can begin to collect real user data that it can analyze and draw results from.

With a launch pad website, businesses can get a product up and running in 2-3 months. They can also save on costs by following a more targeted data-driven approach. This low-risk option is optimized for driving results because every decision that is made is done with the user experience in mind.

In addition, the budget for the new website can be optimized for continuous improvement, as opposed to taking the risk of building a finished product without considering the rapidly evolving needs of customers.

The launch pad website should contain the following key components:

  • Page plans: all the key pages are first laid out and the purpose and content for each page is outlined. Strategies for SEO are also put in place for each page.
  • Prototypes: After creating page plans and content outlines, prototypes for the website can be explored. These prototypes should echo the page outlines and desired content, making content easier to find.
  • Designing and Finishing: commonly referred to as the design sprint and the finish sprint, design involves implementing the chosen prototype and gathering feedback in order to develop the final design. The finish sprint involves coding, inserting links, metadata and testing the browser.
  • Emphasize on quality over speed: while the launch-pad is meant to be up and running in a short-amount of time, the process should not be rushed and quality should not be compromised.

Improving on the Design

After the launch-pad goes live, the business can start collecting data about the user experience. They can also identify critical actions that they can take in order to improve this experience and grow the business. Websites that are able to obtain maximum-performance and immersive user experiences are not built overnight. They have to be constantly tweaked according to the insights that data provides. These websites are both responsive and adaptive to the user experience, allowing them to attain high levels of productivity.

When seeking continuous-improvement, the secret lies in having key areas of focus where performance can be tracked and analyzed. Start with a focus metric that is important to improve the business. Ideas that highly impact the focus metric and lead to measurable results should be prioritized and implemented on a specified-timeline. In a nutshell, the basic-principle is to build, learn and adapt.

With having worked with multiple companies like HockeyShot, Rather Outdoors, Scoperta and many more, BlueBolt is uniquely positioned to help your company engage your users and fuel your growth. Please connect with us, so that we can best help you.

16th of August — 2017

Why a Headless CMS is Important

Chris Risner

O ne of the latest trends in the world of content management is known as a headless CMS. Also referred to as decoupled CMS, the content management system provides valuable benefits not obtained from the singular access point CMS application.

The utilization of a content management system (CMS) has proven vital in the continued development of data management for everything from Web developers to enterprise networks. Typically, a CMS managed the data through a single portal, where data is displayed through a very specific means. Using the software application, a user searches for information and recalls data through a linear approach. This requires the individual to go through the head of the CMS before navigating further into the content management system. However, one of the latest trends in the world of content management is known as a headless CMS. Also referred to as decoupled CMS, the content management system provides valuable benefits not obtained from the singular access point CMS application. Due to this, understanding why a headless CMS is important should prove enlightening for everyone from the IT department to the senior officers of an enterprise. 

The Problem with a Traditional CMS

The age old saying of “if it’s not broke don’t fix it” may seem to apply itself to a traditional content management system. With the right management application in place it can prove especially helpful in monitoring and maintaining data within an enterprise network. However, there are several substantial downfalls connected with the standard CMS. 

Both traditional and headless CMS provide a way to store data and a CRUD UI. However, the standard CMS provides a way to display data while the headless option offers an API to the data. In essence, the data in a traditional CMS can only be viewed in one way. A user performs a create, read, update and delete (CRUD) command when connected with the API, which then sends the information to the database. The database then sends the created, read, updated or deleted information back to the API, which is then displayed in a uniformed manor, regardless of the device accessing the information or the data in general. This singular method of viewing data significantly limits not only users within the network, but customers and clients attempting to access information. With the growing number of devices capable of accessing information from the API database, this singular viewership portal reduced functionality and the end-user experience. 

What is Headless CMS?

Whether referred to as decoupled CMS or headless CMS, the architecture behind this form of content management system has grown in popularity over the last several years due to the improved flexibility it provides not only designers but the end user. A traditional CMS uses a monolithic design, in which the information is tied tightly into the design itself. A headless CMS removes this connection between viewing and accessing the information, which opens up the content management system to a world of new potential. 

A headless CMS allows for several different presentation methods. It also makes information accessible through a Web based API and not just a network API. By utilizing this opportunity, users no longer need to remain connected to the internal network of an enterprise but can instead access the CMS through any Internet connection (this also opens it up to usability with cloud services). 

One of the main reasons why an IT department should consider migrating to a headless CMS is due to the viewership potential. While a traditional CMS regulates how the information is viewed, a decoupled CMS allows for disability through a wide range of devices and methods, including widgets, native applications, a website, mobile website, syndication partners and even digital billboards. Essentially, the information can be viewed anywhere and everywhere on nearly any device (CSS Tricks, 2016).

The Importance of Varying Viewership Opportunities

Up until 2007, nearly all Internet activity took place through a desktop or laptop computer. Outside of a handful of operating systems and a few Internet browsers, most information more or less appeared the same on every device. Due to this, having an individual display method did not prove all to detrimental. Outside of some basic scrolling of the mouse, everything would appear on every computer screen in a similar manor. 

With the release of the Apple iPhone in 2007, everything changed. Although it took a few years to catch up, nearly all major mobile technology developer had its own smartphone on the market. Even with a handful of mobile operating systems, each OS used a slightly different Internet browser, plug-ins and display tactics to connect users with the Internet. In 2017, most mobile users are on either iOS or Android, but there are varying screen sizes, Internet browsers and OS versions in play, each of which requires a slightly different methods for displaying information. A headless CMS makes producing content, accessing and viewing the information easier as it isn’t handcuffed to a specified formatting, but instead the flexible API allows for viewing through applications, smart devices and computers (BizTech, 2016). 

Why Should An Enterprise Consider a Decoupled CMS?

Moving from one content management system doesn’t happen overnight. The migration process can prove time consuming, not to mention there is an initial upfront cost to making this kind of a migration. However, even with the initial time and cost connected with it, an enterprise should consider taking advantage of a headless CMS. 

For starters, moving to a headless CMS helps to future proof a company’s website implementation. With the continued development of smart devices and more mobile designers entering the market on a regular basis, the need for open viewership is essential. As a traditional CMS does not provide this, the decoupled CMS becomes far more beneficial. 

The frontend developers within the network no longer need to spend a good portion of their time working on eliminating problems and connecting the structural elements with the backend. Instead, frontend developers can spend the majority of their time creating specific application tools in order to improve the experience of users on the website. 

By cutting out the frontend element associated with a traditional CMS, a user receives a more interactive experience. This is because the end user interacts with the backend system in real time, instead if through a delay as the user waits for the information to pass into the frontend. The removal of the frontend allows for more creativity within the website design while also streamlining the design process. Shredding the bulk of the frontend also helps boost load speed and connectivity, which is essential in preventing Web users from backing out of the website due to a slow load time.

With the implementation of a decoupled CMS, an enterprise will likely see an increase in its generated profits and bottomline off of the website, all thanks to the faster responding website and the improvement on the user’s experience. All of these are issues a traditional CMS is not able to correct (Hackernoon, 2017). 

Future proofing a content management system has the ability to cut expenses, improve productivity and make locating stored data faster and more effective. With the shift to headless CMS, all of this is possible. While a traditional content management still provides viable assistance in the right setting, growing companies with expansive networks should consider making the switch to a headless CMS. While it may take some careful planning and transitioning into the new management system, it will pay dividends for years to come. Please connect with us if our team can answer any questions about going headless.

14th of August — 2017

The Difference Between Machine Learning and Artificial Intelligence

Chris Risner

W hen performing an Internet search on artificial intelligence or machine learning, the two terms are often used interchangeably. However, while the two are similar in nature and cross paths more than just a few times, there are major differences between machine learning and A.I.

As the industry continues to progress and both are utilized more and more, understanding the difference becomes necessary, both for the average consumer and for corporations looking to implement the technology within the business itself. 

In the Early Days

The best way to dive into the difference between machine learning and artificial intelligence is to dive back into the early days of AI. Now, the concept of artificial intelligence and machine learning has been around for hundreds of years. References to AI can be seen in literature dating back beyond the even earliest conception of a computer. However, the implemented idea of artificial intelligence didn’t truly begin to take shape until the 1950s. 

In 1956, the Dartmouth Conference brought computer scientists from around the world together. Computers remained in the earliest of infancy, yet the idea and drive to create artificial intelligence proved to be a major topic of interest throughout the conference. Of course, the technology necessary to create artificial intelligence lacked significantly and, up until recently, very little in way of AI had occurred. Real change didn’t truly take place in the industry until around 2012 (Nvidia, 2016).

The Divergence of Artificial Intelligence

Before diving into the differences of A.I. and computer learning, it is necessary to understand the divergence of artificial intelligence. In the early days of conceptualized A.I., computerized devices could take on the exact same characteristics and intelligence of a human. They might have a primary function or skill, but in general, the computer would act human. The best example of this in modern pop culture is the droid C-3PO from the Star Wars series. While the droid had a primary function (of being fluent in over six millions forms of communication), it could still perform many, if not most of the same tasks as a human. This form of artificial intelligence is known as “General A.I.”

Of course, while this form of artificial intelligence continues to develop, it isn’t the most commonly utilized form of A.I. The form of artificial intelligence primarily used in both the consumer and commercial levels is known as “Narrow A.I” (in some circles, this is also referred to as weak artificial intelligence while the other is known as strong artificial intelligence). This kind of technology is used for a specific reason or task. Typically, when the narrow A.I. is utilized, it is because it can perform the given task faster, or more accurately, than a human (Forbes, 2016). 

Narrow artificial intelligence is any kind of technology used to perform a specific task. One of the most used forms of narrow A.I. is the spam filter for any email account. It is used to identify undesirable emails and separate it from the rest of incoming messages. Other forms of narrow A.I. includes the newsfeed on user’s Facebook account, self-driving cars using GPS, navigational technology and sensors to drive safety, and, among other technological forms, machine learning (Tech Target, 2016). 

Machine Learning: An Offshoot of Artificial Intelligence

Machine learning does in fact fall under a category of narrow A.I. However, simply suggesting machine learning is a form of artificial intelligence is a narrow sided and inaccurate assessment. Machine learning does technically fall under the category of narrow A.I., but in reality it is so much more than a spam folder or Facebook newsfeed. With these other forms of narrow A.I., an algorithm is input, allowing the computer system to analyze information in order to perform a very specific task. In the form of machine learning though, the system uses the input algorithms to learn from the data it receives, in order to make a possible prediction or educated assumption on the interactive world around it. 

For example, with a spam folder (at least the standard spam folder used in most email services), the narrow A.I. is used to identify potential spam. From time to time it may miss a spam message, or flag a certain sender as spam. If a user identifies a file as spam, the spam folder will add this to the list of accounts to block (or, on the reverse side, remove the email from the spam list if the content is not spam). Although a user can add or remove information from the spam folder, it does not learn from the addition or subjection. It does not analyze the information included within the message, sender email address and title and use it to improve its spam filter ability. If it did, it would use computer learning (Forbes, 2016).

Examples of Computer Learning

There are many examples of computer learning, both large and small. One of the most popular currently is the digital assistant (Amazon’s Alexa/Echo, and Google Home are the two most advanced and widely used). These devices not only provide information, but learn on the fly in order to offer more specific results to each user.

The Blending of Machine Learning and AI

It is possible many confuse the term of artificial intelligence and machine learning because, in many cases, artificial intelligence used in technology has transitioned into machine learning. A prime example of this rests in a search engine’s performance. Google’s search results early on relied on keyword input. A user would input keywords and the search engine would utilize its specially crafted algorithm to provide results. However, if one user in Michigan and another in Nevada typed in the same basic keywords, they would receive the results. The search would use artificial intelligence to crawl through millions of data points to provide results, but it would not take into account the individual making the search request. 

Eventually, search engines such as Google began to implement machine learning into search. This way, the search engine could not only provide desirable results based on the input algorithm, but it could learn from user interaction and adapt to these requests. In a way, Google Search is the poster child of narrow A.I.’s evolution into machine learning (Wired, 2016).

The Push for General AI

The quest for general A.I., such as the Star Wars droids, continues to be a major goal in artificial intelligence research. However, to reach these goals, computer learning will play a major role, as the computerized device must be able to learn and adapt to its environment. In this way, artificial intelligence will lead to the development of computerized learning, which leads to the continued development of A.I. So, while computer learning does stem from narrow A.I., it is in itself an evolved, elevated version of it. 

While often subtle, the differences between machine learning and artificial intelligence can prove vast. Understanding this difference is necessary for an enterprise considering the implementation of such technology in current or future product releases or within the corporate network itself. As the industry progresses, the two technologies will continue to develop new traits, differentiating the two even further. However, for earlier adopters of the technology, in-depth knowledge of the two is a must. 

If our team can help you harness the benefits of AI and Machine learning, please connect with us.

11th of August — 2017

How Big Data is Influencing the World All Around Us

Chris Risner

D ata is everywhere and the rate of growth is spectacular. Most estimates show that the data in the digital universe doubles every 2 years. Part of that digital universe includes human and machine created data, such as the data generated from Internet of Things (IoT).

The growth of human and machine created data is growing 10x faster than traditional business data. It can be found around every corner, within every Internet search and, in reality, on every street corner. Consumers take advantage of data to buy anything from their next vehicle to the “healthiest” fast-food burger. Small businesses take advantage of website analytics to customize local marketing approaches and identify key demographics, while a corporate enterprise implements big data into computer learning applications and identifying future products to manufacturer. In essence, data makes the world go round. Having the latest and most in-depth information has changed the tides of military conflicts throughout world civilization and allowed for space travel. Of course, with the advancement of computer technology, more data can be analyzed, identified, sourced and streamed in a shorter period of time. Big data is influencing in every corner of the globe. Here are just a handful of ways the utilization of big data continues to improve lives and drive business into the future. 

Financial Trading

The understanding and analyzing of financial information has long driven the world of financial trading. All it takes is one look at a mutual fund to understand the importance of big data. While it still takes skilled financial advisors to read and identify shifts in the market and emerging trends, applications designed to crawl through financial information with a fine tooth (digital) comb makes all of this easier. In fact, more and more equity firms are implementing high-end data algorithms in order to stay ahead of the curve and identify upcoming trends further in advance. It is advantageous for investment firms to locate these monetary possibilities early on in order to maximize return on investment. This may be a more specialized field for those with the means of future investing, but big not only influences the world of finances, it is starting to drive it. 

Traffic Optimization

The utilization of technology within major cities and traffic routes is nothing new. The use of analytical data to identify busy times and most used stations has been used to improve public transportation for decades. However, this information is now used to bolster the flow of automotive traffic as well. The ability to analyze traffic in real time and adjust stop lights, the length of a light and sync both public and private transportation together has grown into a major business. However, this real time big data analyst is just the beginning. 

In the United States, Pittsburgh currently used traffic signals with artificial intelligence, designed to not only improve the flow of traffic but cut down on idling and braking (which in turn reduces the amount of released greenhouse gases into the atmosphere). Since the implementation of these A.I. traffic signals within Pittsburgh, idling is down over 40 percent, with automotive breaking down by around 30 percent (Paste Magazine, 2017). 

In the future, technological designers are looking at allowing vehicles to share input rout information with the computerized learning traffic lights, allowing the lights to process information and adjust when lights change in order to improve traffic flow and predict when and where traffic congestion may take place (and reduce it accordingly). 

Automotive Performance

Automobiles have contained computers, in some shape or form, for decades. These computerized systems have gone from controlling basic performance features within a vehicle to monitoring the entire car, providing mechanics (and anyone with the capability of reading displayed codes) with insights into issues within the vehicle and what needs work. In recent years, cars have seen the installation of self-parking, lane detection and merging features, all of which are designed to inform a driver as to if other vehicles are present and to help avoid accidents. Some current vehicles, technology developers and automakers have taken this several steps further. 

Google Maps is the most used GPS system within the United States. Through the company’s continual effort to map out every roadway in the U.S. (while doing the same for much of the world), the application has the ability to provide not only directions, but update drivers on accidents on route and help divert the driver along an alternative path in real time. Google has continued with this research into self-driving cars, capable of not only using the GPS mapped system, but to communicate with other nearby vehicles, in order to reduce human error and boost driving safety. As of September, 2016, Google’s fleet of self-driving cars had covered over two million miles, and the handful of accidents the vehicles had been a part of were all human error on the part of another driver. While these vehicles are not yet able to completely account for the human element, with the help of computerized learning and A.I., these accidents are likely to become less frequent in the future, even when human drivers are involved in other, non-computerized driving vehicles (The Guardian, 2016).

Sports Performance

For non-athletes, what actually goes into training for the sporting event remains a bit of a mystery. Outside of some snippets and behind the scenes coverage at half-time or between innings, the average sports fan likely does not know the kind of technology and big data analytics that goes into modern training. It is now possible for trainers to monitor how an athlete lifts weight, and based on data points, identify weaker muscles used during the lift and how to better train the weaker muscles in order to improve performance and boost muscle growth. Other tests allow athletes to go against teams through virtual reality, which is directly taken from analyzing each player on a team in order to help determine how the other team is most likely to respond to specific plays or actions. Beyond this, many top teams also track everything from sleep and nutrition in order to identify ways to improve nutritional absorption, boost oxygen flow throughout the body and convert nutrients within the blood flow to energy (Recode, 2017). 

Improving Healthcare

Much in the same way technology is used to monitor pro athletes in order to boost performance, technology is used to monitor patients in order to identify better ways to administer treatment. By analyzing dozens of data points given off by a patient (ranging anywhere from brain ways to heart beat and the kinds of nutrients consumed during a day) a medical staff can take the data analysis and use this information to shift treatments and provide a tailor made way of administering the necessary healthcare to a patient. On top of this, healthcare professionals are using big data in order to predict and prevent possible disease outbreaks and epidemics. This technology is used not only in major metropolitan areas but also third world countries. Researchers even monitor social media to see postings regarding sickness and identify problem areas within a community (Science Daily, 2017). 

As the ability to analyze big data continues to improve, informational sourcing will become more and more a tentpole in just about everything in the developed world. From companies using big data to optimize the marketing process to improving healthcare and device performance, the age of big data is here for good. These are just a handful of the ways analytical data can and will continue to influence the world in nearly every corner of technological society. If our BlueBolt team can help your team harness your data and make sense of it, please connect with us.

7th of August — 2017

Why A/B Testing is Critical for Website Optimization

Chris Risner

W hen the multiple versions are compared, random, and statistical analysis is used to decide which version is more effective at achieving the conversion goals that are specified by the business.

As every business strives towards achieving increased conversion rates, various testing methods that are both objective and data driven typically are implemented in order to attain this goal. A/B testing is one of the methods used by businesses to test different versions of a website in order to determine which version performs better. It is a side-by-side comparison between 2 different webpages so as to draw insights that are provided by each version of the webpage.

How A/B Testing Works

A typical A/B test involves taking a webpage or app screen and modifying it to create a second version of the original page. The change that is carried out can involve either changing a headline or button or completely redesigning the page. Typically, marketers like to make small changes with each test to make sure that they understand what is causing the difference in behavior and can be confident in their decisions moving forward. If too many changes are made at the same time, it will confuse the results and it will be difficult to know what changes influenced the visitor. After the adequate modification is carried out, a portion (maybe as much as half, or more) of the website traffic is directed towards the original version of the page (this is the control page), and another percentage of the traffic is directed towards the new version of the page (the variant/variation).

Customer interactions with each version of the page are carefully tracked and the results are collected and analyzed using analytical tools. Many different performance indicators can be tracked, such as incoming traffic, click-through rates, time spent on specific webpages, among others. The data collected is then analyzed via statistical engines and other appropriate tools, after which results can be interpreted. The business can determine if the different experience had a net positive or negative effect.

Measuring Conversion Rates

The key performance indicator that is normally used for A/B testing is the conversion rate. The goal of any business is to get its prospects to engage more with its products and services. They aspire to gain more from their visitors than just visits and a few clicks here and there. Therefore, the rate at which website visitors can be converted from simply being visitors to something else is called the “conversion rate”. The webpage version that yields higher conversion rates is essentially the one that the business will choose to implement.

Your business will have different criteria for measuring conversion rates, depending on the nature of your business. eCommerce sites can use product sales as a means of measuring conversion rates, SaaS sites can use trial or subscription rates to their applications, and news and media sites can use click rates in ads or the number of paid subscriptions as a result of the website change.

Steps Involved in A/B Testing

Before a business dives into an A/B testing framework, it should clearly define its goals and develop a detailed and strategic plan that will make the testing process proceed objectively. A successful A/B testing process typically involves the following steps:

Problem Identification

Every business should have a reason for wanting to test a new version of a specific webpage. It could be that the current webpage design is unattractive, certain links are not being clicked on enough, or the redirect pages as a result of those clicks are not relevant to incoming traffic.

The business should specifically identify the problem that they want to address even before they begin to contemplate on possible solutions. 

Research and Brainstorming

The next step involves conducting research into the problem that is being experienced and brainstorming possible solutions. For example, if a certain webpage layout is not yielding the desired outcome, the business can carry out research into different designs that they can incorporate, and the likely results that these new designs are likely to yield.

Therefore, rather than a random process of trying out solutions, research allows the company to try out specific solutions that have been proven to work for other similar situations.

A Clearly Defined Hypothesis

A hypothesis is a possible explanation for why something occurs the way it does. In the case of A/B testing, a possible hypothesis statement can be “a webpage with more detailed product pictures yields higher purchase rates.” Another possible hypothesis could be “a contact us button on the top right corner leads to higher subscription rates by customers”. The hypothesis should be specific, clearly defined and easy to understand/measure.

Testing

Now it is time to launch the two different versions of the webpage. The version that incoming traffic experience can be varied based on time, customer behavior, or through the use of different URLs. As long as the testing process is truly randomized, accurate results can be collected.

Data Analysis and Reporting of Results

Once the desired threshold of data has been collected, it can be analyzed through statistical tools that are relevant and objective to the data. Tools that generate visual data such as graphs, pie charts and other distributions are the best to use so that decision makers can get a clear glance of the trends that are signified by the data.

Importance of A/B Testing for Website Optimization

Continuous Improvement

Continuous improvement is an important component of website optimization. In order for a company’s website to be effective at driving traffic and converting leads, it needs to slowly adapt to visitor behavior and the trends of the industry surrounding the business.

As small changes (driven by objective data) are implemented to specific components of webpages, the final product is a summation of all the individual changes that yields an improved and optimized website. This in turn leads to increased conversion rates for the business because the new webpage will attract more traffic.

Increased Conversion Rates

A/B testing is critical for website optimization because it leads to increased conversion rates. One of the main objectives of carrying out an A/B test is to determine which webpage version is more effective at converting traffic.

Therefore, the comparisons end up yielding results that show which particular webpage version drives more traffic than the other. The business can implement this more effective version and reap the fruits of increased conversion rates.

Better Understanding of Your Target Audience

A/B testing is a great way of gaining a better understanding of your target audience. As a business takes the time to identify the problems that it is currently facing with its website, as well as brainstorming possible solutions, the company ends up gaining a deeper knowledge of the needs that its customers desire.

In addition, by researching possible solutions to current website challenges, testing those solutions and obtaining objective results; the business can optimize its webpages by implementing changes that are backed by data and are guaranteed to yield results. This is a much more efficient process of solving problems that are facing the business.

Test Multiple Components of a Webpage

A/B testing allows a business to sequentially test all the components that are included on their webpages in order to determine the most effective option for each component. For example, a business can begin by testing headlines, text, links and images, after which it can proceed to test CTAs, testimonials and even text within the webpages.

Such a thorough and comprehensive testing model allows the business to optimize its webpages in a manner that attracts and converts traffic. Each component will have been tested in order to determine the most appropriate and effective design for the business.

If you need help increasing your conversions, please connect with us.

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