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Nous disposons de données sur 216 entreprises qui utilisent Basket Analysis. Notre liste de clients Basket Analysis est disponible en téléchargement et est enrichie de spécificités essentielles de l'entreprise, y compris la classification de l'industrie, la taille de l'organisation, la localisation géographique, les tours de financement et les chiffres d'affaires, entre autres.
Entreprise | Pays | Industrie | Employés | Chiffre d'affaires |
---|---|---|---|---|
Shell | Royaume-Uni | Oil And Gas | 137K | $361B |
PwC | Royaume-Uni | Professional Services | 328K | $50B |
UnitedHealthcare | États-Unis | Hospitals And Health Care | 13K | $250B |
EY | Royaume-Uni | Professional Services | 357K | $45B |
Fractal.ai | États-Unis | Professional Services | 4.4K | $136M |
Tractor Supply | États-Unis | Retail Furniture And Home Furnishings | 10K | $18M |
Red Bull North America | Autriche | Manufacturing | 20K | $6.8B |
Bain & Company | États-Unis | Business Consulting And Services | 22K | $6B |
Accenture | Irlande | Business Consulting And Services | 738K | $63B |
Cheney Brothers | États-Unis | Restaurants | 1.3K | $2B |
The Rehancement Group | États-Unis | 62 | $6M | |
Infosys | Inde | It Services And It Consulting | 315K | $17B |
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Statistiques d'Utilisation Technologique et Part de Marché
Vous pouvez personnaliser ces données selon vos besoins en filtrant par géographie, secteur d'activité, taille de l'entreprise, revenus, utilisation de la technologie, postes de travail et plus encore. Vous pouvez télécharger les données au format Excel ou CSV.
Vous pouvez recevoir des alertes pour ces données. Vous pouvez commencer par sélectionner la technologie qui vous intéresse, puis vous recevrez des alertes dans votre boîte de réception lorsque de nouvelles entreprises utiliseront cette technologie.
Vous pouvez exporter ses données vers un fichier Excel, qui peut être importé dans votre CRM. Vous pouvez également exporter les données vers une API.
Il y a -1 alternatives à Basket Analysis
Basket Analysis est utilisé dans 17 pays
Questions fréquemment posées
Nos données proviennent d'offres d'emploi collectées auprès de millions d'entreprises. Nous surveillons ces offres sur les sites web des entreprises, les plateformes d'emploi et d'autres plateformes de recrutement. L'analyse des offres d'emploi constitue une méthode fiable pour comprendre les technologies utilisées par les entreprises, y compris l'utilisation de leurs outils internes.
Nous actualisons nos données quotidiennement pour vous garantir un accès à l'information la plus récente disponible. Ce processus de mise à jour fréquente assure que nos insights et notre intelligence reflètent les derniers développements et tendances au sein de l'industrie.
Basket Analysis is a data mining technique that is widely used in the field of business intelligence and retail analytics. It involves analyzing the contents of a customer's shopping basket to identify patterns and relationships between different products that are frequently purchased together. This information is valuable for businesses as it allows them to understand consumer behavior, improve product recommendations, optimize pricing strategies, and enhance overall sales performance.
Basket Analysis falls under the category of "Association Rule Learning" in machine learning and data mining. It focuses on uncovering relationships between items in large data sets, often represented in the form of rules such as "If item A is purchased, then item B is also likely to be purchased." By understanding these associations, businesses can make informed decisions on product placement, cross-selling opportunities, and targeted marketing campaigns.
The concept of Basket Analysis dates back to the late 1980s when it was pioneered by researchers in the field of data mining and market basket analysis. One of the early contributors to this technology was Rakesh Agrawal, who developed the Apriori algorithm for finding frequent itemsets in transactional data. Agrawal's motivation was to enhance the efficiency of market basket data processing and extract meaningful insights from large volumes of sales data.
Basket Analysis currently holds a significant market share within the realm of retail analytics and business intelligence tools. With the rise of e-commerce and the increasing focus on personalized customer experiences, the demand for Basket Analysis solutions is expected to grow in the coming years. Companies are increasingly looking to leverage the power of association rules to drive sales, improve customer satisfaction, and gain a competitive edge in the market. As a result, the future outlook for Basket Analysis technology appears promising, with a forecasted trend of continued growth and adoption across various industries.
Basket Analysis is a crucial technique utilized by companies to gain valuable insights into customer behavior and preferences. By examining the contents of shoppers' baskets, companies can uncover patterns, correlations, and trends that can inform strategic decision-making and personalized marketing efforts.
Basket Analysis enables companies to identify which products are frequently purchased together, allowing for targeted cross-selling campaigns. Unlike traditional upselling approaches, Basket Analysis provides data-driven recommendations based on actual customer behavior, increasing the likelihood of conversion.
By understanding product affinities and seasonality trends through Basket Analysis, companies can optimize their inventory management processes. This leads to a reduction in stockouts, excess inventory, and ultimately, cost savings compared to relying solely on manual forecasting methods.
Basket Analysis empowers companies to deliver personalized recommendations and promotions tailored to individual customer preferences. This level of customization enhances customer satisfaction and loyalty, setting companies apart from competitors that offer generic marketing messages.
Unlike intuition-based strategies, Basket Analysis provides concrete data insights that guide strategic decision-making processes. Companies can rely on empirical evidence to shape their pricing strategies, product bundling tactics, and overall marketing initiatives for improved results and ROI.
Introduction:
Many well-known companies across various industries leverage Basket Analysis to gain insights into customer behavior, optimize product recommendations, and enhance their overall sales strategies. With the help of this technique, businesses can better understand the relationships between different products and transactions, leading to more informed decision-making processes.
Case Studies:
Amazon: Amazon, the e-commerce giant, uses Basket Analysis to enhance its product recommendation engine. By analyzing the items customers purchase together, Amazon can suggest relevant products to users, thereby increasing cross-selling opportunities. The company started utilizing Basket Analysis early on to personalize the shopping experience for its customers.
Walmart: Walmart, one of the largest retail companies globally, applies Basket Analysis to understand consumer purchasing patterns. By examining customers' shopping carts and identifying common product combinations, Walmart can optimize its inventory management and marketing strategies. The company integrated Basket Analysis into its operations to improve sales forecasting and promotional offers.
Netflix: Netflix, a leading streaming service provider, implements Basket Analysis to enhance content recommendations for its subscribers. By analyzing viewing patterns and preferences, Netflix can suggest personalized movie and TV show selections, enhancing user engagement and satisfaction. The company incorporated Basket Analysis into its algorithms to deliver a more tailored entertainment experience.
These case studies highlight how prominent companies leverage Basket Analysis to drive business growth and improve customer satisfaction by understanding purchasing behavior and providing personalized recommendations. By harnessing the power of this analytical technique, businesses can unlock valuable insights to optimize their operations and enhance customer experiences.
Vous pouvez accéder à une liste actualisée des entreprises utilisant Basket Analysis en visitant TheirStack.com. Notre plateforme fournit une base de données complète des entreprises utilisant diverses technologies et outils internes.
À ce jour, nous disposons de données sur 216 entreprises qui utilisent Basket Analysis.
Basket Analysis est utilisé par une large gamme d'organisations dans divers secteurs, y compris "Oil And Gas", "Professional Services", "Hospitals And Health Care", "Professional Services", "Professional Services", "Retail Furniture And Home Furnishings", "Manufacturing", "Business Consulting And Services", "Business Consulting And Services", "Restaurants". Pour une liste complète de tous les secteurs utilisant Basket Analysis, veuillez visiter TheirStack.com.
Certaines des entreprises qui utilisent Basket Analysis incluent Shell, PwC, UnitedHealthcare, EY, Fractal.ai, Tractor Supply, Red Bull North America, Bain & Company, Accenture, Cheney Brothers et bien d'autres encore. Vous pouvez trouver une liste complète des 216 entreprises qui utilisent Basket Analysis sur TheirStack.com.
Selon nos données, Basket Analysis est le plus populaire dans États-Unis (80 companies), Royaume-Uni (30 companies), Canada (13 companies), Inde (6 companies), Irlande (6 companies), France (5 companies), Suisse (5 companies), Australie (4 companies), Singapour (4 companies), Afrique du Sud (3 companies). Toutefois, il est utilisé par des entreprises du monde entier.
Vous pouvez trouver des entreprises utilisant Basket Analysis en le recherchant sur TheirStack.com. Nous suivons les offres d'emploi de millions d'entreprises et les utilisons pour découvrir quelles technologies et outils internes elles emploient.