How Can Fashion Retailers Develop Scientific Discount Schemes?

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For example, in order to clear inventory, the common promotion decision that retailers may take is "all half price". This plan is indeed convenient and fast, and can rapidly increase sales volume. On the other hand, the "half price" promotion strategy will result in a sharp decline in profit margins and a weakening of profitability.

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Therefore, a good sales promotion plan not only needs to increase sales volume, but also helps retailers achieve profit targets as far as possible. So how can we make sales promotions to benefit consumers and retailers? The answer is to introduce Advanced Analytics, which is advanced analysis technology, such as big data, pricing algorithm and machine learning.

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Over the past 18 months, the Boston consulting company (BCG) has worked with fashion retailers to launch more than 20 quarter and quarter sales promotion projects using advanced analysis technology. According to the final result, the sales promotion scheme optimized by advanced analysis technology can raise the gross profit margin of retailers by 10-20 percentage points.

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The first stage of the promotion plan for advanced analytical technology

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This stage consists of three steps: Commodity matching, demand quantification, and creation and selection. At the end of the first stage, retailers can get a precise sales discount list according to the classification of goods and stores.

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1) merchandise pairing: this step is especially important at the end of the season, and it can predict the future sales performance of new products based on the historical sales performance of the old products. Commodity pairing refers to the collection and collection of old goods SKU collections with the same or similar sales patterns from the aspect of SKU (stock holding units, the unique identifier for each product and service).

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2) demand quantification: demand forecasting models can help retail teams grasp the relationship between sales volume and price at any time point, and also grasp the factors such as seasonality, promotion level, passenger flow and shortage. For a SKU or series of zero price elasticity, a big discount will not lead to sales increase, but will weaken profit margins. For SKU or series with high price elasticity, a slight discount can greatly increase sales and control profit margins. The demand forecasting model is based on the SKU sales data of previous quarters to quantify the needs of the new season and to develop better pricing strategies.

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3) create and choose the plan: the last step is the application of the demand forecasting model, which can predict the sales volume of each SKU in the unit sales cycle under different discount rates, and use this data to create a variety of promotional programs. The retail team can choose the most suitable solution according to its sales target.

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The following chart shows:

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The left side is the four common sales target of retailers, including sales volume, sales volume, gross profit and cash flow.

The middle is the optimal strategy of the retailer.

The right side is the corresponding sales environment.

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For example, if a fashion series sells poorly and has a large inventory in the quarter, retailers need to clear inventory and make room for the new season series. The strategy is to maximize sales through optimizing discount mix.

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In order to complete the first stage, fashion retailers need to compile and collate daily transaction data such as stores, SKU and invoices over the past two years, thus helping to observe customer behavior before and during sales promotion. In addition, retailers can add data such as available stock, merchandise size, style, color and so on.

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Under the requirements of advanced analytical technology, retailers also need to develop various promotional parameters, including promotions and end dates, choose promotion or off-season promotions, promotions and promotions (such as discount, full reduction, etc.).

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As shown in Figure two, retailers must set clear sales promotion rules. For example, retailers can choose a percentage discount for a certain product to prevent unsmooth communication and avoid misunderstanding.

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The second stage of advanced analytical technology promotion scheme

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The second stage is actually the promotion scheme entering the practical application stage. With the increasing number of store and SKU sales data, machine learning and algorithm are further improved, thus providing more complex and accurate suggestions. Through advanced analysis technology, retailers can check the initial discount form given in the first phase during the actual sales promotion process, and adjust it at any time.

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As shown in Figure three, the most leftside types are retailers, such as multi brand high-end retailers, luxury retailers, jewelry retailers and so on. For example, when the average discount of international multi brand high-end retailers decreased by 2.5 percentage points, corresponding sales increased by 5%, and gross margins increased by 13%.

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In addition, BCG also found that because physical stores are more constrained by external environment, e-commerce providers can more flexible implementation of adjustment and promotion strategies than physical retailers. At the same time, for all fashion retailers, the most important thing is still "people". For example, stores need special leadership and staff training when doing promotional activities, so as to ensure the smooth implementation of the plan.

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Advantages of advanced analysis technology

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1) optimization can be achieved throughout the entire product lifecycle: advanced analysis technology can be perfected in the process of practice and application, which means that fashion retailers can optimize them in the whole life cycle of a commodity or a series, not just a promotion stage. Fashion retailers are also able to obtain strategic planning proposals through advanced analysis techniques and purchase decisions after the end of the promotional period.

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2) people are still the core: in contrast, technology is still a supplement to human beings. The specific promotion rules are still worked out by the retail team, and only with the cooperation of the store staff can the sales promotion plan be carried out smoothly. In addition, the advanced analytical technology promotion scheme still needs real-time monitoring to ensure that it does not deviate from the initial goal.

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3) develop new skills: using advanced analysis technology, fashion retailers can also expand to other areas, such as overall pricing management, distribution, replenishment management and so on. For retailers seeking or embarking on digital transformation, advanced analytical technology will help them further explore the potential of analytical tools.

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The "big sale" has been in the retail industry for a long time, and retailers know that sales means greater traffic and sales. Nowadays, with the introduction of advanced analysis technology, retailers can not only get better sales performance, but also predict ahead of time, grasp the timing and intensity of promotion, and achieve their profit targets.