Business Intelligence for fashion. 6 ways to strengthen your fashion business through BI.

Predictive analyses and an understanding of what drives tendencies are essential in an industry driven by trends and fashion.

As the possibilities within BI and analytics increase, new ways are created in which fashion businesses can make better decisions regarding which styles to produce and sell. Forecast for sales as well as market reaction and demand for certain styles can lead to less waste and a larger turnover.

Here are six examples of how you can strengthen your fashion business through a data-driven understanding of historic data in combination with data on current trends.

1) Analyse and understand historical data

Maybe a trend died, before you thought it would. Maybe your sales projections for a new clothing line missed the mark completely.

By analysing your historic data, you can learn a great deal from the past – whether it be by identifying the mistakes that led to a specific failure, by calculating which marketing and sales techniques it would be best to replicate in the future or something else again.

This form of planning – objective and based on facts – makes it easier for your company to develop strategies for your products and brand image.

2) Get an overview of the volume of orders

Due to the short life span of collections, it is important to have an updated overview of the introduction sales in order to know where to concentrate your efforts.

Whether it be an analysis of your sales personnel, customer groups, country or something completely different, it is important to keep an eye on deviations – for example, compared to the budget or the volume of orders of the same collection last year.

A well-implemented BI solution will provide you with a full overview of the volume of orders, which will make it easier for you to optimise the introduction sales process.

Orderoverview - fashion

3) Optimise the production volume

Waste due to miscalculated production volumes is a major hindrance to profitability in the fashion industry.

If you end up producing too many articles in a certain style, you are left with a surplus in stock when the trend dies out. On the other hand, if you produce too little of a product, the consumers may become frustrated and you risk losing sales in what might have been a profitable trend.

The right data insight will help you foresee the demand more precisely and plan the production accordingly.

Manufacturing optimisation - fashion

4) Know your customers

Do you really know who buys what? Most companies collect a wide range of data regarding their customers from both physical and online stores – for example age, gender, location etc. But do you know how to analyse the data?

By accumulating and enriching the organised and unorganised data, you can generate insight into your customer groups – insight that otherwise would not be readily available.

Furthermore, you can analyse customer behaviour such as when during the day your customers prefer to shop, how they react to marketing etc. Based on these analyses, you can adjust your marketing and design it to match your customers’ behaviour.

Customer analyses - fashion
PWT Group

“We have had great success with simulations where we compare our actual purchase to our budget. This enables us to see all the deviations – be they at store, supplier or item group level”

Mark Jensen, Business Developer, PWT Group

5) Increase your cross sales

Cross selling is selling more items to your return customers. By using data from earlier sales, you can analyse your customers’ basket size and what they tend to buy together – thus gaining insight into which items can be expected to sell best as well as which items are most often bought together.

Using this data, you can organise your store efficiently (both online and offline) and use the most efficient marketing tools for your target group. This way, you create a basis for increasing your income through improved cross sales.

Krydssalg - fashion

6) Gather and use external Big Data

BI allows textile companies to collect and analyse data from several sources to a bigger degree – including external data.

Instead of solely using your own data, you can integrate external data to get a broader picture of what is going on across the fashion industry.

As solutions for data collection and analysis become more readily available, an increasing number of businesses use Big Data as a source of insight into, for example, fashion trends.

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