Живеем във времена на драматични промени и ритейл секторът не прави изключение. Тук не става дума само за неизбежната технологична трансформация на този тип бизнес, но и за промените в потребитеските нагласи заради COVID-19. Много ритейл бизнеси не успяват да отговорят на предизвикателствата. От 2015 г. досега, общо 128 крупни ритейл марки са обявили фалит само в САЩ по данни на CB Insights. Сред тях са вериги магазини за храни и напитки, дрехи, обувки, мебели, спортни стоки, стоки за свободното време и т.н. Ето защо поставяме фокус върху наистина важните ритейл KPI показатели и разказваме как изкуственият интелект и автоматизацията на бизнес процесите помагат те да бъдат оцветени в зелено.
The COVID-19 pandemic is unprecedented in the recent days cataclysm. Countries from all over the world found themselves in a wholly new and, in most cases, unexpected situations. It applies to not just governments and businesses but also consumers.
The retail sector has been shaken by the dramatic change that forced some retailers to close their outlets, others to shift to e-commerce, while other businesses are facing drastic demand surge. When consumer behavior is rapidly changing, the right retailers’ response is essential, and their future might be at stake.
A DIY retailer, for instance, has the potential to increase its sales revenue by 1 – 2% annually with price elasticity of demand application.
Meeting customers’ needs is essential for a retailer wellbeing. A retail business failing to do so will be simply pushed out of the market, soon or later. Some retailers rely on their gut feeling but as data analytics experts, we are perfectly familiar with Arthur Conan Doyle who once said, “It is a capital mistake to theorize before one has data”.
The worldwide known fast fashion retailer H&M is suffering from a problem with unsold stock worth $4.3 billion. The situation became clear when the Q1 report of the Swedish giant was released. It made analysts and commentators speculating with the company capability to stay competitive. Such statements are problematic, especially for a public company with significant free float.
This is a no brainer – weather definitely has its own impact on retail sales. The substantial question is to which extent. This blog post is based on our own analytical insights extracted out of a project we developed and implemented for a chain of pastry shops in Europe.
Our example is giving deep insights on how day-to-day weather change affect daily revenues for a particular retail location. Careful examination of a representative sample of pastry shops shows clearly that the revenues of such kind of retail business may change up to 40% on a day-to-day basis. No doubt, this is big!
Regardless of its size, any fashion or apparel manufacturer is confronted with challenges related to predicting the future.
Unlike the big brands that manage to create and impose trends, smaller players try to foresee what will be the forthcoming changes in consumer tastes. Trends might arise even from occasional events, take for instance Converse sneakers which became a big hit after rock bands like The Ramones wore them onstage on their gigs at the late 70s and early 80s.
Apparel manufacturers often can do nothing but to follow and adapt according to trends. Discussing fashion and apparel, such shifts affects everything – size, color, shape, fabric, price, etc. are a piece of the equation for success or fail.
Visits, visitors, events, conversions, orders, time on site, page views, subscribers, average order value, etc. are just a fraction of the e-commerce KPIs and metrics that every online retailer should keep an eye on. All these pieces of data are just the perfect fit for predictive analytics and sales forecasting.
Its huge amount of data which might be modeled in order to project future demand and overall e-commerce performance. This is leading to crucial benefits pushing online retailers further in terms of effectiveness, profitability, and performance.
Running retail business of any kind might be extremely tricky process full of unknown variables. Full scale analytics service provider is able to offer you a lot. But in depth analytics projects demand lot of recourses, hence money. Big retail businesses already benefit from analytics services because of their large scaling and that’s how they improve their profitability even more. This is raising following question:
Are small retailers able to benefit from data analytics?