Ecard

Feedback Loops

Collecting and making sense of stakeholder feedback is critical for businesses that wish to make improvements based on what their stakeholders (such as users) need.

VET: What stakeholder feedback is essential to your organization?

HEI: How could digital technologies support and incentivize stakeholders to be willing to share feedback?


User feedback loops, supported by digital technologies, play a crucial role in building and strengthening the relationship between users and the products and services provided by fashion companies. A user feedback loop refers to the continuous process of gathering feedback from users, analyzing it, and using the insights to improve products, services, and overall customer experiences.

Digital technologies offer numerous advantages in establishing effective user feedback loops in the fashion industry. They enable efficient and scalable data collection, analysis, and communication, allowing fashion brands to gather feedback from a wide range of users and make informed decisions based on the insights gained.

To build or strengthen a feedback loop between users and fashion companies, several methods and incentives can be utilized. Here are some approaches commonly used:

Online surveys

Fashion brands can use online surveys to gather structured feedback from users. These surveys can be designed to capture specific information, such as user preferences, satisfaction levels, or suggestions for improvement. By offering incentives like discounts, exclusive access, or loyalty rewards, companies can encourage users to participate in surveys and share their opinions.

Ratings and reviews

By providing a platform for users to leave ratings and reviews for products and services, fashion companies can collect valuable feedback. Users are often willing to share their experiences and provide ratings and reviews when they feel their input is valued. Brands can showcase their responsiveness by actively engaging with user reviews and addressing any concerns or issues raised.

Social media listening

Fashion brands can leverage social media platforms to monitor and analyze user conversations, mentions, and sentiments related to their products and services. This allows companies to gain real-time insights, identify trends, and address customer concerns promptly. Engaging with users on social media platforms also fosters a sense of community and encourages users to share their feedback openly.

User testing and beta programs

Fashion companies can involve users in the testing and development phases of new products or features. By inviting users to be part of beta programs or user testing sessions, companies can collect valuable feedback on usability, functionality, and overall user experience. This approach not only provides insightful feedback but also engages users in the product development process, making them feel valued and invested in the brand.

Personalized communication

Fashion companies can establish personalized communication channels, such as email newsletters or loyalty programs, to regularly engage with users and seek their feedback. By providing exclusive content, personalized offers, and early access to new collections or features, companies can incentivize users to provide feedback and actively participate in shaping the brand’s offerings.

Case studies

Stitch Fix – Client feedback–driven styling

Stitch Fix’s styling service is built around continuous feedback loops: after each shipment, clients rate individual items, provide free-text feedback, and answer style preference questions. This granular feedback is fed into both human stylist workflows and machine-learning models to iteratively refine future assortments and recommendations, explicitly positioning client feedback as a core data source for design, buying, and personalization decisions.
Project link

Rent the Runway – Fit reviews and data-informed sizing

Rent the Runway’s “Finding Your Fit” system invites renters to share detailed reviews with body measurements, event context, and perceived fit for each garment. The platform aggregates this user-generated feedback into fit guidance, size recommendations, and visual review galleries, enabling a tight loop between wearer experience, future renters’ decisions, and inventory selection and product development.
Project link

Nuuly – Fit Feedback + Size Guidance

Nuuly’s “Fit Feedback + Size Guidance” feature asks subscribers to rate how each rented garment fits and describe where it feels tight, loose, or true to size. These data points are used to generate size guidance for future renters and to inform assortment optimisation and pattern adjustments, embedding an explicit digital feedback loop into the rental model.
Project link

Zalando – Embedded customer insight for brands

Through its data and analytics offerings, Zalando combines transactional data and customer insight (including survey-based feedback) to provide brands with dashboards on performance, user behaviour, and product response. This infrastructure closes the loop between what local users actually buy and say, and how brands adjust assortments, pricing, and marketing strategies on the platform.
Project link

Nike – Nike Run Club as performance feedback ecosystem

Nike Run Club is a mobile app that records runs, surfaces post-run analytics, and connects training plans to an individual’s performance history. These continuous digital feedback loops support runners in adjusting behaviour over time, while also providing Nike with large-scale behavioural insight that can inform service design, campaign targeting, and the development of performance apparel and footwear ecosystems.
Project link

References

  • Bonilla-Quijada, M., Del Olmo, J. L., Andreu, D., & Ripoll-i-Alcón, J. (2023). Customer engagement on Instagram for luxury fashion brands: An empirical comparative analysis. Cogent Social Sciences, 9(1), 2235169. https://doi.org/10.1080/23311886.2023.2235169

  • Goti, A., Querejeta-Lomas, L., Almeida, A., de la Puerta, J. G., & López-de-Ipiña, D. (2023). Artificial intelligence in business-to-customer fashion retail: A literature review. Mathematics, 11(13), 2943. https://doi.org/10.3390/math11132943

  • Huang, Y., Yang, J., & Li, Z. (2024). Effects of online customer reviews on sustainable clothing purchase intentions: The mediating role of green perceived value and trust. Journal of Consumer Behaviour. Advance online publication. https://doi.org/10.1002/cb.2344

  • Tupikovskaja-Omovie, Z. (2022). Enhancing user experience in fashion m-retail: Mapping shopping user journey using Google Analytics, eye tracking technology and retrospective think-aloud interview. Fashion Practice, 14(3), 352–375. https://doi.org/10.1080/17569370.2022.2129466

  • Tupikovskaja-Omovie, Z., & Tyler, D. J. (2021). Eye tracking technology to audit Google Analytics: Analysing digital consumer shopping journey in fashion m-retail. International Journal of Information Management, 59, 102294. https://doi.org/10.1016/j.ijinfomgt.2020.102294