Standortanalyse


Retail Site Selection can have a huge impact on business success

The site selection problem is one of the most fundamental problems for growing businesses and new entries. Opening up a new business location can either be a game changer if hitting the right spot, or your new business site could be doomed to fail if the location is not attracting enough customers. Hence, there is a high risk of making wrong investment decisions. There are many factors that influence this essential decision that it becomes one of the most challenging topic for every business.

The Problem of traditional location decisions

Besides geo-based factors like transportation accessibility, real estate prices and availability of qualified workers, also socio-demographic factors play a vital role in decision making. The latter group of factors determine the size and distribution of the potential customer base. With data on population, purchasing power and consumption habits demand forecasts can be generated.

Having so many variables that influence the revenue of a specific location, the traditional approach of evaluating a site by manual survey of the land and building a competition landscape becomes costly, time consuming and ultimately too complex.

Gaining the best return on your investment

Luckily, with the rise of Big Data Analytics there is no burden of incorporating a bunch of different factors at a time anymore. By leveraging available geo-based and socio-demographic data from the internet and integrating business data from existing stores, retail site selection becomes a lot more efficient and less risky.

Simulations can model predicted market shares in different isochrones given existing competitors, substitution products and pricing. Moreover, the cannibalization effects of the new store on existing facilities can be calculated by measuring the effects of overlapping catchment areas.

When incorporating Big Data and publicly available geo-spartial information, risk associated with the investment into a new store location can be minimized and new growth potential can be taped. This is especially valuable for retailers, delivery services and insurances.

What we do

As a leading data science company in retail, we excel on our experience with the largest food retailers in Germany and localization projects in other industries. In our analysis, we combine new technologies like Big Data and Machine Learning with GIS and risk models. Of course also individual preferences and corporate regulations are communicated beforehand and considered in the optimization.

As a result, we deliver a sales forecast for potential sites and visualize the findings in a map with colored isochrones to provide managerial insights for decision makers.

Check out our success stories below or talk to one of our Data Science experts.

The assortment must be individually adapted to the location too

To get the maximum out of your investment, we are also happy to consult you with category management analytics. We help you to set up the ideal assortment given the consumer class in the new store’s catchment area.

AI and data solutions for e-commerce.

During the last decade, Data has become one of the most precious resources that every business possesses, but when it comes to e-commerce businesses, data science makes the difference between failure and success. Because of the highly competitive market and the continuous rapid change of needs and trends in e-commerce, there is no space for errors in prediction and decision making.

There are various fields where Data Science can help businesses in e-commerce, some of which we will mention below.

Data collection in e-commerce

In general, it is difficult to track shopper’s buying journey in stores, since obviously, no one can read their customer’s mind. However, this changes with online shopping. Now more than 2,05 billion people purchase goods online which makes it easier to track the journey of customers before buying a product, which products they buy more often, and the ones that they have seen but have not purchased. Accordingly, companies collect information to give discounts to the right products, optimize the stocks to corresponds with the demand in different seasons and for the standard product line.

Personalize the shopping experience

In e-commerce, companies that are capable to offer personalized experiences to their customers are always one step ahead of their competitors. According to some research studies, 87% of the shoppers say that they are willing to buy more when online stores personalize their shopping experience.

The best successful example is Amazon. Their customers are frequently attracted by recommendation lists such as “customers who viewed this item also viewed” etc. As a result, the company boosts the sale of additional products and the revenue as well.

The benefits of Data Science

Furthermore, data science helps companies to improve buyers’ sentiment analysis. This is very important in order to figure out what customers like about a product and what they don’t like. The positive reviews are extremely important as they built trust about the product and the company, while in the case of negative reviews the impact is twofold. On the one hand, the negative reviews are good in order to understand what the customers don’t like about the product and what needs to be improved, and on the other hand, they can lead to trust loss about the product if not acted fast and in the right way.

Thereby successful companies give enormous attention to the collection of data and use data science to appropriately analyze them. However, since Data Science is very complex, in order to reach best results, it is essential for companies to ask for help from experienced Consulting Companies. Data itself has no value if it is not properly used.

Conclusion

Based on the arguments given above, one can conclude that the importance of data science for every company is enormous, but when it comes to e-commerce, it is vital. Thanks to the fast development of technology, innovation is done at a very high speed which leads to an extremely connected world.

As a result, companies need to react quickly and adjust their strategies in order to adapt to innovation, otherwise, failure is guaranteed.

The generation of data

We are living in the age of the fourth industrial revolution where data is the new electricity.

Each day, around 2.5 exabytes of data is created and the need for data has risen tremendously over the last decade. Data analytics is increasingly adopted across industries, starting from Retail, E-commerce, Logistic, Medicine and up to Manufacturing and Education.

Studies show that data-driven organizations can make better strategic decisions, maintain high operational efficiency, increase revenue and customer satisfaction.

Perks of data-driven organizations

In order for a business to exist and grow continually, it is vital to make the right strategic decisions. When data analytics is used properly, it plays a very important role.

On the one hand it helps to specify what currently exists, so you can forecast the impact of any decision on your business.

On the other hand, data is logical and concrete in a way that intuition is not. By including objective elements for your business decisions you instill confidence, which allows you to commit fully to a particular vision or strategy without being worried that the decision you made is right. As a result, you can identify business opportunities before your competition does, or detect threats before they grow seriously.

Benefits in numbers

The main objective of any company is to minimize the expenses and to maximize the profit. Data analytics plays a vital role when it comes to increasing profit and reducing costs, and it is substantial in order to achieve a balanced Business Strategy.

According to a report on “Big Data Use Cases 2015 — Getting Real On Data Monetization“, 40% of the companies leveraging data are enjoying diverse benefits like a better understanding of consumer behavior (52%), better strategic decisions (69%), and cost reductions (47%).

Moreover, the organizations have reported an average of 10% reduction in costs and an 8% increase in revenues from analyzing data. As we can see from the results, you obtain significant positive impact when you know how to read and apply the data reports correctly.

How Data Drives Customer Satisfaction

Furthermore, most successful companies in the world are focused on consumer satisfaction as well.

Customers want to have a smooth experience and communication with companies in order to avoid inconveniences and frustrations. According to research, the probability to sell to existing customers is between 60% and 70%, while selling to a new customer is 5-20%. 

To control this situation, companies use different data analytics strategies to collect information from different channels in order to better understand and identify customers’ needs and history, so they can adjust the sales and marketing strategies appropriately.

Beware of the right data interpretation

However, one should be aware that, just because decisions are based on data it does not mean that it will always be correct. If the data interpretation or the collection is incorrect, then the decisions based on the data would be inaccurate.

That’s why it is very important to seek professional help in order to avoid these inconvenient situation for a business to occur.


Find out about our success stories in the reference below or talk to one of our Data Science experts

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First of all, we look for extraordinary personalities who have already proven success in their academic career. We appreciate people with international experience and global thinking as our clients are international and globally connected. You should bring international experience to the table e.g., a semester or an internship abroad, Bachelor, Master or PhD done in different countries etc. Multiple spoken languages are a plus.  

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