The role of data analytics in fashion
Data analytics is the key process for taking better business decisions.
"Data-driven business" is a term you might have heard around in the last few years. But what does it mean? Simply put, it means that businesses in any industry are using data analytics to make better decisions. Indeed, having access to the right data at the right moment can improve every aspect of a business, from production to marketing.
Let's find out more!
What are data analytics?
In a nutshell, data analytics is the process of turning large and small data sets into actionable business insights. This can be done through a number of methods, including:
Using data to understand what has happened in the past. For example, analyzing past sales to see which products were most popular.
Using past data to predict what will happen in the future. For example, analyzing customer behavior to identify which customers are most likely to buy a certain product.
Using data to prescribe a course of action. For example, using predictive analytics to identify which products are most likely to be popular in the future, and then plan a marketing campaign to promote those products.
What is Big Data?
Big data refers to the large and growing volume of data sets that businesses are now able to collect, that are too large or complex to be dealt with by traditional data-processing application software. It includes everything from customer information (such as age, gender, location, etc.) to data on production processes, sales, website traffic, competitors, and more.
However, Big Data isn't just about volume, it's also about:
- velocity: the speed at which data is generated,
- variety: the different types of available data,
- veracity: the accuracy of the data.
Why are data important for fashion brands?
What does big data have to do with fashion? Everything.
The modern fashion industry is driven by data analytics. Data are fundamental throughout the supply chain, from the creativity of the designers and the environmental impact of production, to the speed of adaptation to the market, without counting logistics, customer experience, and after-sales services.
Without data, brands would be flying blind about production processes, consumer behaviors, and competitors. On the contrary, data allows them to identify what works and what doesn't, make predictions and better decisions.
Fast fashion brands are particularly good at data analysis. For example, some of them are able to intercept successful VIP Instagram posts, replicate those expensive looks, and place their version on their e-commerce in a matter of days.
How can fashion brands collect data?
There are different technologies that brands can use to collect and analyze data.They include:
Customer Relationship Management (CRM) systems
CRM systems help brands track customer behavior and interactions. This data can then be useful to improve customer service, target marketing campaigns, and more.
Social media listening tools
These tools help brands track what is being said about them on social media. The data are useful to improve customer service, for product development, and more.
Web analytics and app analytics
They help brands track how customers interact with their website or apps. The data gives insights on how to improve website/app design, to target marketing campaigns, and more.
In-store devices and smart labels
Touch screens, interactive columns, and smart labels are physical means that allow brands to easily and quickly collect data about the shopping experience right when it happens.
Smart connected products
All products that can interact with the consumer collect data. Some examples are connected garments with digital product passports, smart clothing that collects biometric data and IoT accessories such as a smartwatch.
Smartphones can be tracked through free wi-fi in shopping malls. This allows retailers to understand customers' movements and to identify any patterns when shopping. Although this kind of data analytics may seem more useful to stores, fashion brands can also draw useful insights from this information.
Which are the benefits of data analytics?
Here are just a few of the many benefits fashion companies can have from data analytics:
Data analytics can help brands better understand customer demand, so that they can produce the right products in the right quantities. This can reduce the inventory levels and improve production efficiency.
Data can help brands better understand customer behavior, so that they can target marketing campaigns more effectively. This can increase sales and improve customer retention.
Better customer service
Brands can understand customer needs and expectations, thus providing tailored customer service. This can lead to increased customer satisfaction and loyalty.
Faster (and better) decision making
Companies can have a deeper vision on processes and markets, and decide about production, marketing, and more in less time and with better results.
Better decisions translate into more profits.
Data analytics can help brands identify new opportunities and uncover hidden trends. For example, new markets to enter or new products to develop.
Data can help brands to automate tasks and processes. For example, data analytics can help brands automatically segment customers based on their behavior, so that they can target them with the right marketing messages.
Brands can identify areas of waste and inefficiency.
This is the result of all the above benefits.
Data analytics about consumers: an advantage only for companies?
As you can see, data analytics is a powerful tool that can help brands in several ways.
However, collecting big data may seem like an activity that only benefits companies. Actually, when used correctly, data can provide consumers with a more enjoyable customer journey, and more targeted products and offers. But a good customer experience includes respect for privacy. Indeed, the best use of data is that which takes place under the consent of the consumer. Therefore, fashion companies must be committed to making consumers feel safe while collecting their data, both online or offline. Transparency is the key to success.