Good retailers sell well, and best retailers offer their customers an unforgettable experience. The story of the 1800-Flowers.com online store is interesting because it traces the path that a Manhattan flower shop bought in the 1970s for $ 10,000 to a multimillion business that generated $ 1.2 bn. in sales just last year. The achievement goes through impressive AI innovation that has cemented its leadership position in the US online marketplace.
Not matter if a business is a production, retail or wholesale focused, the inventory is a crucial piece of its smooth running. It is a challenge that has to be faced properly. If not, efficiency wouldn’t be gained, resulting in not acceptable business performance. Inventory management executed as it should mean less cash locked in a stock, on time deliveries and at the end of the day – happy clients. As we all know, they do matter.
Predictive analytics is applicable as efficiency booster in many business processes and inventory management is no exclusion. Optimizing inventory is ensuring the right SKU is available in the right quantities, at the right time and at the right location. Such optimization is leading to stock levels reduction, hence transportation costs reduction and write-down cost reduction. Relying purely on data, predictive analytics is the perfect tool for addressing issues like this. Combine demand prediction with sales forecasting and you`ll know what, when and where.
Since AI has turned into a buzzword, many misperceptions created too many myths we`d like to share with you and bust together just like Adam Savage and Jamie Hyneman. Even though we are living right within the Secondary Information Age, the lack of understanding of what actually is AI and where it can bring the society we are all living in, it is a foundation of quite a few misconceptions. Some of them funny, other rather scary.
There was a time when the banks were the sole legitimate lending providers but the rapid increase of Internet coverage, smart devices penetration and credit scoring automation made possible to get a fast loan with just a few clicks on your phone. Welcome to the FinTech world built by much more than cryptocurrencies and ICOs. Credit scoring automation is the tool that enabled loan access to the underfinanced population. Matching credit scoring with machine learning, AI and automation, in general, made this process a viable business case.
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”.
Credit scoring is the process enabling lending businesses to determine how likely a lender will default its loan. This process is utilizing different data sources and less or more is designed around the business logic of the lending organization. In some markets like USA and UK, there are credit scoring bureaus assigning credit score derived from credit files and history of a particular person. In other markets, the credit scoring is up to the lending institutions, not matter banks or nonbank financial institutions like leasing companies, consumer finance companies, telecommunication companies, etc. Such businesses hold the credit risk and they need a solution like credit scoring. In this blog post, we explain why credit scoring as a service is the most viable option for lending businesses of different size and markets. Let us share with you the three main options in front of a company dealing with such kind of financial risk.
Have you ever heard about Moore`s law? In 1965, Gordon Moore, who would later become one of the founders of Intel, wrote a paper claiming that the number of electronic components, which could be placed into an integrated circuit, will double every year. This exponential became known as Moore`s law and turned out to be the foundation of the digital world.
Just think of it! Without credit and lending businesses, we would not be able to buy a house or appliances when we need them. Business would not be able to grow, expand and innovate at the desired pace. Credit is the fuel of any country` economy and this is not a secret. But what is fueling credit and lending businesses? How do they decide if you are eligible for a particular loan or not?
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.
We`re not sure if you already have heard about this and if not, keep in mind that those couple of minutes will be more than worthy.
The Spotify Fraud
Unknown scammer, allegedly from Bulgaria generated about $3m revenue out of creating and continuously playing a couple of playlists with tracks with an average length of 43 seconds. Spotify is paying artists about $0.004 per play and the fraudster has registered around 1200 premium Spotify accounts, continuously rolling the playlists.
It is believed that such ‘performance’ was achieved via bots automating the skip and play game regarding the Spotify policy to pay for a listened track only its 30 seconds or more. This way, the playlists called ‘Soulful Music’ and ‘Music From The Heart’ became played so many times they made it to number 84 globally and 22 in the US in the playlists charts.