Data Driven Design: How to Use it to Increase Ecommerce Conversions
How would you like reading the mind of your visitors? Or knowing precisely what your customers are thinking about your store? Not bad, huh?
And that is exactly what data analysis can do for your business.
Having a good database allows you to understand customers’ minds and buying patterns. This is important to improve conversion rates once it helps predicting consumers behavior.
But, how can you do it? In this article, we will walk you through:
- what is data-driven design;
- why your online store needs it;
- how to put in place a data-driven strategy in your website.
What is data-driven website design?
Data-analysis is no longer only tracking site visitors, bounce rate, exit behavior. Identifying your target audience and their sources is essential, but not knowing what’s turning away them from your site is almost a crime.
By using data to identify consumers behavior patterns, you can find pain points that need to be improved to sell more.
And here is where the data-driven design enters. It allows you to make changes based on real numbers, not blindfolded.
Data-driven design improve engagement, UX and lead generation based on real stats.
Data became so important, that it’s impossible to disassociate it from ecommerce growth. Knowing page performance, bounce rates, session duration, is essential to increase conversion rates.
Why should you start making data-based decisions in design
As we mentioned above, data-driven website design can improve the User Experience (UX) for optimal results for both users and merchants.
Let’s see how:
Data influences end-user Experience
Brands need to evolve continuously based on customer expectations. When it comes to website development, data analytics is the only source of solid information that directly contributes to the brand’s ROI.
Data influences UX by showing what users are expecting, or the specific factors that are turning them away from making a purchase at your shop.
Practical UX Design contribute to Ecommerce Conversions
An efficient UX design with well-placed site elements, artifacts and is essential to the success of any online store.
Imagine a customer visits your site trying to make a purchase but is constantly being distracted by irrelevant recommendations, or is frustrated with the multiple steps in the payment processing page. This can lead to your customer exiting your website without a purchase.
You certainly don’t want that, right?
One of the major issues for bounce and cart abandonment rates is an impractical site design. Lack of visual prominence for critical elements such as cart, checkout progress and other indicators are also a big no-no.
But, how can start using data to make website improvements?
How to implement data-driven design
Quality is more important than quantity
There are 2 kinds of data that can be collected from any website.
Quantitative Data: numbers focusing on site visitors, conversions and click among others.
Qualitative Data: is non-numerical and refers to the user behavior on your site.
While quantitative data is important, qualitative data is a mandate when it comes to better conversions. It can help you understand user behavior based on browsing patterns, emotional responses, engagement, etc.
Google Analytics Tools for Predictive Data Analysis
One of the most common, popular way to collect valuable qualitative data on your website is using Google Analytics. Of all the websites, ecommerce stores are the ones where Google Analytics finds its use on a much broader scale.
With so many customers browsing, purchasing and leaving the site, it can be difficult to analyze their purchasing patterns.
This is where Google Analytics Ecommerce Tracking finds its use. The tool conducts an extensive user research, collecting all quantifiable data. This helps you analyse shopping behavior, checkout behavior and merchandise performance.
Google’s advanced machine learning algorithms can also help identify, track and measure user engagement. Use this to predict their preferences and make personalized product recommendations.
The advanced metrics track the entire customer journey, from start to finish, whether it ends in a purchase or cart abandonment or returns.
It is integrated as a site plugin and is available for purchase for ecommerce websites hosted on any platform.
A/B Testing for personalized page design
We’ve seem A/B testing’s importance increasing in the last few years, as the need to deliver something unique to convert a visitor into a customer.
The big idea behind A/B testing on ecommerce UX is to determine the best way to optimize the site for better conversions.
By comparing two different sets of visual and content elements (A & B) you can identify which one has the strongest user experience and better CRO. These two sets are shown to two different user groups to track and compare conversion rates using advanced analytics tools.
Artificial Intelligence for informed decision-making
Artificial intelligence and machine learning capabilities can make a regular ecommerce website into a strategic and smart machine that can deliver data-driven results. It is an epic combination when ecommerce meets machine learning and here’s why.
- Data collection and Analysis are done in the blink of an eye – saves time and effort.
- Automates the entire system of data management – gets more work done in a less time.
- Advanced data algorithms and predictive analysis – curbs suppositions and make decisions based on solid facts.
- Smart machines can deliver the job at the fraction of a second – personalized search results and accurate product recommendations.
- Out of the box data analysis and reporting – studies product pricing trends and makes data-driven suggestions.
- Smart Sales Rep to narrow down cart abandonment rates through automated personalized email marketing.
Whether the ultimate goal of your website is engagement, experience or conversion, data plays a key role in influencing the decision-making patterns of your target audience when they visit your site. A deeper insight into website data can help influence purchase decisions, thereby expanding the scope to develop an evidence-based UX design for ecommerce sites.