Q-Commerce is the natural evolvement of E-Commerce, especially in the grocery segment. The always-on culture of smartphones made us more immediate including our purchasing habits. The Q-Commerce segment grew rapidly during the COVID-19 pandemics due to its convenience and fast delivery, up to 30, or even 15 minutes in some instances. It is like the corner shop but at your front door. How nice, isn’t it?
How Q-Commerce is possible?
Unlike brick and mortar retailers, Q-Commerce vendors have a limited assortment and a bit higher but still affordable pricing. They rely on so-called Dark Stores, a small warehouse full of groceries located throughout the city. As bikes, scooters, and bicycles are faster in congested urban traffic, customers can expect delivery within half an hour or less.
Black Friday is marking the beginning of the X-Mass shopping hysteria since 1952 when it was created as a retailer campaign aimed to clear stock on promotional prices. More than half century later, Black Friday and the entire weekend after Thanksgiving, including Cyber Monday transformed into a shopping spree, helping retailers to generate more sales and revenues. Since data is one of the key assets for any retailer, its analysis is helping to boost the efficiency and overall campaign performance. As Black Friday revenues are estimated at billions of dollars, it is worthy to get aware how to take a bigger piece of this retail pie. In this blog post, we are going to share 3 different analytics applications helping retailers to achieve more on Black Friday.
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!
We`ve broadly discussed sales forecasting in our data analytics blog. But there is something we didn’t cover up to date and this is demand forecasting. Are there any differences between them? And if yes, how they complement each other.
We`ve already discussed how data analytics & sales forecasting might help restaurant managers to improve their business performance so we are moving in a specific case like cake & pastry shops. Their case is pretty specific, hence interesting.
Predictive and big data analytics are extremely hot these days, since the belief that the data is the new oil is taking over business managers from all sectors and industries. Data analytics for restaurants is also available even though the revenue of a particular restaurant location is not that big. But there are opportunities which make the difference between good and best.
Web mining is the process within you are extracting insightful information from World Wide Web. It is possible at different scales and for different purposes. In general, web mining is the term used for data mining application within online collected information. Such technical achievement gives businesses pretty interesting opportunities for the e-commerce businesses and online entrepreneurs.
It is not a secret that there is a staggering amount of information located on the Internet. The annual internet traffic is rated as a 1 zettabyte per year. If you ever have wondered how much data is that, just imagine a cup of coffee on your desk is equal to 1 gigabyte. A zettabyte is the volume of the Great Wall of China.
Important trends rarely happens overnight and furniture industry is no exclusion. Overall the market is on the rise with constant growth, esp. on matured markets. The healthy market definitely is good news for furniture retailers and stores, who are a main branch in the selling cycle of the industry. But there are few crucial trends that decision makers should keep an eye on.
To have a crystal clear notion of upcoming restaurant sales is crucial for efficient business. Sales forecasting is addressing this very issue with some interesting approaches.
It is true that a restaurant owner knows his business better than anyone. But it is also true that there are some wastes, not matter how good you are into business planning which is also time consuming. This is what sales forecasting is doing for restaurants – it manages the tiny balance between the necessary stock products sufficient to meet the customers demand while keeping wastage levels to a minimum.
Running a restaurant is not an easy business. It requires a lot of effort which sometimes is so exhausting that you miss a bit or two. It is both pleasure and burden but at A4Everyone we believe that every business might perform better in terms of profitability. That’s why we listed 9 tips & hints that might act as profit boosters for any restaurant business.
