Demand forecasting -

Demand forecasting

Anticipate sufficiently in advance of the loads that the telecommunications network will have at certain times and in specific areas. This way, you can avoid problems of saturation and drop in quality of calls and the service offered, with the consequent poor user experience.

For retail sector, it guarantees to always have in your establishment the products that your clients demand, for their greater satisfaction. To do this, you will have accurate predictions of this demand at your fingertips, anticipating its peaks and valleys and making sure you have the right supply at all times.

General Description of this use case

For an overwhelming majority of companies, knowing in good time what the market situation will be in the near future is a competitive advantage that can make the difference between success and non-survival. Among the factors involved in this is the prediction of demand for products and services.

If we focus on the retail sector, knowing future demand will help to prevent stock-outs of certain products in scenarios of very high demand. On the other hand, it also helps to avoid having high stock levels, with the negative effects that this entails. In addition, this information is very practical in terms of managing the material and human assets of the business more intelligently.

Turning to telecommunications companies, demand forecasting focuses on network load levels. Therefore, demand forecasting helps to have the network prepared for times of high usage of voice and/or data services.

Regardless of the industry, accurate demand forecasting will crystallise in increased profits, reduced costs and therefore more efficient investments.

Learn how this apply to your business

Tell us the particularities and needs your project needs to be able to implement a plan specially designed for you.

What solutions do you need?

In order to enjoy this predictive capability reliably, it is necessary to have the benefits offered by artificial intelligence algorithmic processing of data with a geographic component.

What kind of information are we talking about? This will depend very much on the industry we are focusing on. For example, for retail this data will relate to sales figures distributed temporally in each store or area (by months, days, special events, etc.), as well as the socio-economic situations of the markets and other variables involved.

For Telco, it is key to analyse the times and places where the most calls are made or the most data is consumed, as well as to find possible causes for this. For example, on special dates, such as Christmas, there is likely to be a peak in calls and video calls to congratulate the festive season.

With these predictions, managers in many industries will be able to prepare for all kinds of scenarios without traumatic actions and undesirable outcomes.

Telco network optimization

It optimize the rollout of mobile telecommunications networks, improving the user experience so that they enjoy an optimal service in terms of signal quality for each of the telco use cases. In addition, it maximizes the profitability of the core and radio access network infrastructure. All this optimizes the network topology: by placing the right equipment in each of the locations.

OMNICHANNEL RETAIL NETWORK OPTIMIZATION

The retail sector is clearly marked by the influence of different sales channels, such as physical and online stores. Therefore, it is essential to know the geospatial data that explain the dynamics of these channels, as well as the cause-effect relationships between them. With Locatium, you will be able to choose the best locations for new stores, predict results in new locations, mitigate the influence of competitors considering cannibalization, and optimize the right online-Vs-offline mix in each location.

Do you want to see how
many industries this use case applies to?

Demand forecasting is a critical process for a number of industries. From Locatium would like to help you identify the main industries where we can lend a hand to prevent this from happening.

Retail

Geographic data is a high-value resource for analyzing the effects of the industry's own omnichannel and for customer segmentation. With them, the locations of the establishments and their particular characteristics can be set more accurately, avoiding cannibalization and the influence of competitors.

Telco

With such a wide offer, telecommunications companies are forced to offer excellent service to their customers to be truly competitive. To achieve this it is necessary to design an infrastructure capable of meeting the needs of the user, as well as doing it with the greatest efficiency. Geolocated information is key to your site selection and deployment.

fmcg

Geospatial technology greatly speeds up the supply of fast consumer goods, facilitating their access for all buyers through an adequate choice of the locations of the establishments, as well as the types of products that these really demand.

Restaurants

Choosing the most valuable location for hospitality businesses involves analyzing useful geospatial data to attract customers who come to the physical establishment and for those who request home delivery (OoH marketing). It is also important to know the degree of saturation of each market, in order to know the ideal number of restaurants for each one of them.

Healthcare

Geographical data to know precisely and without risk the best situation for the performance of clinics of various medical specialties. These greatly increase the planning capacity of the various brands in the sector in specific markets.

Banking

The banking sector faces a challenge when it has to design a network of branches that satisfy the demand of its clients, as well as optimize its portfolio of financial products based on the characteristics of its target audience, both current and potential.

Automotive

The geolocated information allows you to decide in a documented way where it will be most beneficial to locate dealers and workshops. For this, areas of influence, prediction of demand, levels of cannibalization, and those establishments that are more and less profitable are taken into account, among other variables.

Want to know more about this use case?

If we have caught your interest or if you have any questions, we will be happy to help you without any obligation so that you are really clear about how Locatium can contribute to the success of your project with our datasets and advanced solutions.