The data-driven eCommerce design process: 4 important steps

1. Planning and collecting customer data

To ensure the success of an eCommerce design project, it’s essential to start by finding out more about the customer, using documents provided by the customer. Then, it’s time to dive deeper into the company’s objectives during customer workshops, to fully understand their needs and expectations. The key performance indicators (KPIs) need to be determined to guide the process. Observing Analytics data helps to formulate initial hypotheses, which can then be cross-checked with Hotjar data for greater precision. To gain a better understanding of users’ expectations and perceptions, it is useful to look for evocative customer comments and reviews. Finally, analysis of direct competition and inspiration from elsewhere can be used to refine strategy and propose innovative solutions.

To help you deal with all your data, Novatize offers a few tips on how to understand it.

2. Surveying, interviewing and organizing content

To optimize the user experience, it’s useful to place surveys at key moments in the customer journey to gather valuable data. Talking directly to real users enables us to better understand their needs and expectations. With these exchanges, the eCommerce catalog and product placement can be revised based on their feedback. Content is then structured to highlight the customer’s specific strengths and differences. Finally, the tree structure and labels are tested with real users to ensure smooth, intuitive navigation.

To understand the difference between A/B testing and usability testing in eCommerce, watch this video [French only]. 

3. Create your first iterations and test them with real users

To start the eCommerce design process, searching for relevant articles and publications is highly recommended, including sites like Baymard Institute and NN Group for inspiration and domain or feature-specific information. Navigation is guided by prioritizing important elements and creating prototypes with varying levels of precision depending on the stage of the project. We recommend starting with fast prototypes (Low or Mid-Fidelity) to generate as many ideas as possible, then mapping the user journey using wireframes or wireflows (Mid-Fidelity). The most complex functionalities are conceptualized (Mid or High-Fidelity) with a functional prototype that meets the multiple requirements of the project. By involving the developers, efficient and alternative solutions can be found. Finally, it is advisable to place the prototype in the hands of real users, in order to analyze their feedback, put it into perspective and sort it in order of importance. This enables existing solutions to be improved and new projects to be planned.

Find out more about UX and UI best practices for B2B eCommerce. 

4. Continue to draw inspiration and improve existing UX-UI solutions

To ensure the effectiveness of your initiatives, it’s essential to actively monitor your KPIs using the various analysis tools, for example, directly in the Analytics section of Shopify or in Google Analytics. Make sure you stay on top of best practices by observing trends and innovations to keep up to date. After each initiative, carrying out a post-mortem helps to improve your methods and processes. It’s also essential to keep attentive of new insights and opportunities linked to the eCommerce site, so you can adapt your strategies accordingly. By improving the list of projects to be carried out, and reviewing the prioritization of those that have not yet been completed, eCommerce will continue to progress. 

Investing in research is essential to minimize risk and ensure the success of your project. Data is everywhere, and knowing how to exploit it effectively is crucial. By integrating artificial intelligence into your various tools, you can digest and analyze this immense quantity of information more efficiently. It’s important to systematize data collection and centralize it for optimal management. Involve users as often as possible to ensure that the solutions you develop meet their real needs. Finally, creating a recurring pattern of contact with super-users ensures you benefit from constant, high-quality feedback.

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