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As the industry is turning towards a more digitized approach, retailers are implementing advanced analytics practices to address major business challenges and to maximize benefits. Predictive models enable businesses to determine the intent of their customers, which assists retailers in meeting market demand. Predictive analytics monitors historical product pricing, the interest of the customer, competitor’s pricing, and inventory to deliver best possible prices to gain maximum profits to organizations. For instance, in Amazon’s marketplace, sellers that are using algorithmic pricing are benefitted through better visibility, sales, and timely customer feedbacks. Furthermore, according to the retail intelligence company Upstream Commerce, an automated predictive and dynamic pricing tool delivers up to an additional 20% net profit gain.

Predictive analytics is a key solution that helps retails and eCommerce businesses in building smarter market strategy and also helps in faster decision making. It helps in making significant enhancements in the business operations which include improved customer engagements, identifying better targets prospects, price optimization, and predictive inventory management. Further, with the added ability to deliver more effective marketing higher profits and more controlled operations, predictive analytics have become a critical component to both eCommerce and retail businesses.

COMPETITIVE LEADERSHIP MAPPING TERMINOLOGY

The vendors for predictive analytics software in Retail and Ecommerce are placed into 4 categories based on their performance in each criterion: “visionary leaders,” “innovators,” “dynamic differentiators,” and “emerging companies.” The top 26 vendors evaluated in the data quality tools market include Opera Solutions, Domino Data Lab, Dataiku, Figure Eight Inc, Civis Analytics, Agilone, Alteryx, Inc, Fair Isaac Corporation (Fico), Information Builders, Inc., Qlik Technologies Inc, Microsoft Corporation, Teradata Corporation, Knime Ag, Kognitio, Microstrategy Incorporated, Exago, Inc., NTT Data Corporation, Rapidminer, Inc, Greenwave Systems, Inc, Tibco Software Inc, Sisense, 6sense, Lytics, Good Data, Radius Intelligence Inc. and Angoss Software Corporation.

Use Cases of Predictive Analytics Software in Retail

Social Media Analysis: With increasing digitalization, retailers are moving towards promoting their products through social media platform. As a result of that, retailers need to monitor online sentiment and respond in real time with relevant messages or offers. In addition, consumers are also using social media to exert tremendous influence over a retailer’s brand or a product’s success.

BEHAVIORAL ANALYTICS: Retailers are focusing towards improving customer conversion rates and personalizing marketing campaigns avoiding customer churn, and lowering customer acquisition costs to increase their revenue.

PERSONALIZE IN-STORE EXPERIENCE: With increasing ecommerce/ online sales, retailers are focusing towards providing personalized in store experience to establish and drive loyalty by giving offers to incentivize frequent consumers to make more purchases thereby achieving higher sales across all channels.

CUSTOMER JOURNEY ANALYTICS: with increasing competition and complex retail queries such as understanding activities on every step in the customer journey, understanding customer behavior  and best possible to reach them, companies are adoption predictive analytics solutions.

OPERATION AND SUPPLY CHAINS ANALYTICS:  Faster product life cycles and ever-complex operations tend drive the focus to retailers to use predictive analytics solutions to understand supply chains and product distribution to reduce costs and gain competitive advantage.

TRADE PROMOTIONS OPTIMIZATION: Many companies are losing over one-thirds of the money invested in trade promotions to provide awareness among customers. This is mainly due to inability of decision-makers to measure trade promotion effectiveness and return on investment to profitably optimize spend by leveraging data.

 

Case Studies of Predictive Analytics Software in Retail

Versium Analytics

Case Study: Verium helped Outerwall to determine location for new kiosks using large volumes of consumer and sales data

Versium Analytics helped US based retailer, Outerwall in predicting the best locations for 20,000 new retail kiosk using its platform, LifeData. The platform helps in delivering a significant volume of highly relevant and non-biased insights into Outerwall’s customers in 10% of the time than the other methodologies such as cluster survey.

Business Outcome:

  • 90% decrease in data analysis time
  • Delivered historical activity data of over 250,000 transactions representing approximately 100,000 customers from their existing kiosks

BRIGDGEi2i Analytics

Case Study: BRIDGEi2i helped India’s largest retailers to study customer’s buying pattern, create targeted promotions, and enhance sales value

India’s largest retailers are implementing numerous methods to understand customers’ intent, provide instant response to changing customer expectations, determine future customer behavior, and bridge the digital and physical shopping experiences, thereby boosting the overall sales. Retailers have increased their focus on digital transformation tools, such as customer intelligence and predictive analytics, to deliver an enhanced, personalized customer experience and meet in-store expectations.

BRIDGEi2i’s predictive analytics solutions helped these retailers derive actionable insights on changing customer behaviors and develop customer-centric approaches to maximize customer retention. The company offered the ExTrack proprietary platform to effectively track customer experience-related issues and correlate these issues to enhance business outcome.

Business Outcome:

  • ExTrack accelerated the customer experience in a quick timeframe
  • Provided 360° customer view
  • Discovered areas that needed instant attention
  • Built customer loyalty and personalized schemes

SAP SE

Case Study: SAP SE helped Grupo Merza to gain insights into market baskets across products, categories, and stores

 Grupo Merza, a retail and wholesale distributor headquartered in Michocan, Mexico, offers numerous products and services, such as food and beverage distribution, transportation and logistics, and financial services. The group employees a workforce of more than 4500 people who operate in 19 wholesale distribution centers and 152 retail chains across Mexico. The group desired to augment its analytical insights and enhance efficiency for inventory management, transportation, delivery, and crediting and invoicing.

The company deployed the SAP HANA platform, SAP Lumira software, SAP Sales Insights for Retail analytics application, and SAP Predictive Analysis software to gain a competitive edge by easily understanding customer needs, increasing sales, and improving customer engagement. The company took only 4 weeks to deploy the SAP Lumira software without involving any consulting services.

Business Outcome:

  • Improved the transactional data and reporting delivery
  • Ensured faster decisions with self-service data visualization
  • Provided insights into how product assortment and promotion contribute to market baskets
  • Facilitated in recognizing the defaulters who had not cleared their debts
  • Created scorecards which would be instrumental in predicting future lenders’ behaviors

 

Arjuna Solutions

Case Study: Arjuna Solutions helped First Book to analyze personalities and behavioral patterns of its customers  

 First Book, an international distributor of high-quality books to disadvantaged youth. The company offers platform teachers and school administrators to register for an account and purchase books at substantially reduced prices on behalf of students. With increasing number of account holders, First Book struggled to increase repeat sales and customer engagement. 

First Book, used Persanalytix to identify the common characteristics among its customers, predict their individual customers who are likely to engage in repeat sales.

Business Outcome:

  • 720% Increase in Purchases from Email Marketing
  • 331% Increase in Repeat Sales Success Rate
  • 11 Billion Data Points Cleansed, Integrated and Supplemented
  • 97% Accuracy Predicting Individual Customer Spend

SAS

Case Study: SAS helped 1-800-FLOWERS.COM to Analyze data in real time to help improve the customer experience

1-800-FLOWERS.COM, the US based floral and gourmet foods gift retailer and distribution Company is focusing on enhancing customer relationship, increases customer lifetime spending and encourages cross-brand shopping. To analyze data in real time to help improve the customer experience, the company is using SAS Business Analytics solution. 

Business Outcome:

  • Reduced customer complaints by 40% during the critical Mother's Day season and increased customer satisfaction
  • Increased in new customer order
  • Initiated the Perfect Order Every Time (POET) program

 

Tibco Software

Case Study: TIBCO helped Yakult to enhance its new product sales in the Netherland

Yakult, Japan based leading probiotic beverage Company. The company’s portfolio includes a range of consumer, cosmetic, and pharmaceutical products. The company was suffering from time-consuming analysis, mistakes, and spreadsheets. The company used TIBCO Spotfire which helps in distinguish sales drivers from non-drivers in a very dynamic environment. Yakult was able to identify the elements in its marketing mix that drove the sudden category growth. Applying this knowledge to future marketing budget decisions fueled additional growth

Business Outcome:

  • Sales Increased by 15 % to 20%

 

Teradata Software

Case Study: Teradata helped largest beverage producers to monetize, manage and Increase sales globally

One of the largest beverage producers needed help monitoring, managing and increasing sales globally. The company is focusing on increasing demand for rapid insight from enterprise data to boost sales.  Also the company is also focusing to reduce the total investment in data and analytics through more efficient infrastructure.

The company has used Bespoke data applications and tools (Spark, R and Hadoop) to enhance reporting through scorecard creation that provides advanced analytical insight.

Business Outcome:

  • Increased beverage sales.
  • Large-scale analyses of data sets that were previously too time intensive to acquire.
  • Seamless access to data for business and IT users alike.

Microsoft Corporation

Case Study: Microsoft helped Fast Shop to optimize multiple processes including pricing and customer engagement  

 

Fast Shop, a leading Brazilian retailers specialized in providing in high-end consumer electronics and appliances. The company was facing problem in price setting as earlier pricing was set manually, and with 5,000 products for sale. SO the managers was only focusing on the products with the highest sales volumes and leave the rest to the judgment of sales staff.

The company has adopted Anzure analytics services, Azure data factory, Azure Machine Learning, Cortana Intelligent suite, Power BI, Azure SQL Data Warehouse for the restructuring

Business Outcome:

  • Increase in sales
  • Build 90% solution without IT help

Dataiku

Case Study: Dataiku helped showroomprive.com to anticipate and reduce customer churn rates 

 

Showroomprive.com, a leading e-commerce player with over 20 million members in Europe. The ecommerce site has about 15 flash sales and over 2 million visitors per day. The company is focusing on reducing customer churn rates and improve customer loyalty based on individual purchase rates, detect clients with a high potential of no longer buying from the website.

 

The company used DSS to build a predictive analytics application that detects potential churners based on individual purchase rates. Also, the company use DSS solution to automate the integration and enrichment of a variety of data sources such as customer data, order and delivery data, web logs, etc.

Business Outcome:

  • 77% accuracy in detecting potential churners
  • Internalized data research and development
  • In-house churn prediction system

Microstrategy

Case Study: Microstrategy helped Fanatics to enhance the performance on-demand

Fanatics, a largest online retailer of licensed sports apparel and merchandise, has started using MicroStrategy enterprise analytics platform to enhance the performance of the company on-demand. The company operates over 300 online and offline stores and powers the e-commerce business for all major professional sport leagues: the NFL, MLB, NHL, NBA, NASCAR, and PGA. Also, the company deployed a Hadoop distribution to manage and process unstructured log data, which will be analyzed using MicroStrategy enterprise analytics platform.

Business Outcome:

  • Generated over 30 million orders a year
  • Increase web traffic and clickstream data covering over 250 million web visits each year

Predictive Analytics Software in Retail

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Popular Comparisons
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1.3 Online
Civis Analytics adopts science-first strategy to take care of business issues utilizing person-level data. This platform is cloud-based and is designed for data scientists and decision makers to help clients find loyal customers. This platform combines machine learning and statistical models to not just help clients help retain existing customers but also gain new ones. It also helps clients optimize the ratio of expenditure-return by preparing a budget for marketing campaigns.
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3.5
The USP of RapidMiner Inc in predictive analytics software lies in its ease of use. RapidMiner enables users to easily build predictive models with an intuitive drag-and-drop interface. It also provides powerful data preparation and visualization tools that empower users to quickly extract insights from existing datasets. Furthermore, RapidMiner also offers support for specialized use cases such as text mining and deep learning, making it an ideal choice for organizations seeking an all-in-one predictive analytics software.
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3.2
Angoss uses data and predictive modeling to present insights that help users make better decisions faster. It uses advanced statistical algorithms for the prediction of outcomes. These outcomes are generated across all stages of model cycles. It helps improving predictive analytics for organizations looking to monetize their data.
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Information Builders WebFocus RStat is a cost-effective, robust, intuitive, and accurate predictive analytics software. WebFocus can help organizations by extracting meaningful insights from data of any kind. It creates interactive dashboards to consolidate information which increases the chances of actionable insights to be used in the everyday conduct of data-driven businesses.
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2.9
FICO Decision Management Suite is an integrated environment for development that is compatible with web as well as mobile applications. It is a platform that handles real-time streaming of data including its visualization, indexing, search, and pre-processing, based on rules that are defined in advance. The company's USP is the ability to provide models based on precise customer requirement to reduce time and cost.
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2.8
Alteryx provides information science that can viably and productively tap into a code-free and code-accommodating easy-to-use application. The predictive analytics software requires no coding, however, it is coding friendly for those interested. It has a fantastic interface without code for both analytics modelling and advanced modelling with code. It enables easy deployment and management of analytic models, flexibility, agility, and high speed. It supports visualization tools and all data sources. Alteryx helps find, manage, and understand all sort of analytic information of an organization at a high speed, thereby making better decisions and increasing productivity.
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2.7
MicroStrategy’s features and algorithms provide enterprises with advanced predictive analytics capabilities. MicroStrategy is useful for deploying models with governed data. It integrates seamlessly with R and can be connected to any source with the use of APIs. Some of its important features include: Scalable integration with R, incorporation of statistics, ARIMA, etc. and minimal IT support required
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2.7
Rapid assembling of predictive data that changes crude information into a business affecting service. This product has advantages for all types of users: analytics leaders, data scientists, IT professionals, and business analysts. It helps analytics leaders in terms of managing productivity, collaboration, coordination, and measuring team growth. Data scientists benefit in terms of automation, modelling, flexibility, and reproducibility. IT professionals gain advantages pertaining to scalability, code & integration, operationalization, and data governance; while business analysts obtain data access, preparation, exploration, and automated ML benefits.
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2.6
GoodData is a cloud-based platform with high SLA availability and maintenance. It allows for easy incorporation of already existing data warehouses. It allows the platform to be integrated into web or mobile applications. It is one of the most dominant cloud data warehouse that meets most versatile analytics platform requirements.
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2.5
Extensive set of cloud services that enables associations to address business problems, construct, oversee, and convey applications on a massive, worldwide system utilizing various tools and frameworks. Microsoft Azure ML Studio can be used to prepare and manage the data they need for machine learning. It can improve productivity through its powerful capabilities that can integrate the current model cycle with that of the app lifecycle.
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2.5
Natural language search and AI-powered bits of knowledge discovery make creating bits of knowledge a characteristic, instinctive, and intuitive experience. Spotfire has strong built-in predictive analytical methods that are smart, yet easy to use. Its intelligent data wrangling helps you clean and modify data, and auto-records it so you can edit it later as well. It is flexible and can scale secured documents as well.
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2.5
AXON Predict permits OEMs and enterprises to catch, screen, and break down information. AXON Predict is a product suitable for OEMs as well as large enterprises since it collates, scrutinizes, and analyzes data across networks and provide valuable visual analytical insights to users. This gives users real-time analytics to work with in order to enhance innovation and reduce costs.
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2.4
NTT Data offers effective solutions that supplement the decision-making process in an organization. This is possible across multiple business platforms and across different development and deployment capabilities. With the help of a comprehensive analytics and business insight methodology, NTT Analytics Solutions can change a client organization into an information-driven pioneer.
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2.4
Teradata predictive analytics software provides “Flip the Switch” analytics which allows on-the-fly switching of best campaign users from reverse modeling to forward prediction. Teradata Analytics for Enterprise Applications eradicates the complexity of enterprise application integration, delivers real-time access to integrated data from ERP and other enterprise applications, as well as provides transparency and visibility into business and customer insights.
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2.3
Qlik helps enterprises around the globe move quicker, work smarter, and provide a start-to-finish answer to get an incentive out of information. QlikView helps users compare different sets of data from multiple sources and locations to deliver the most value. Its main features include, interactive participation in session-sharing is possible across different groups which enables users to share their insights formally or informally. It is also possible to access and load data from different locations and from different deployment modes – cloud, on-premise, or big data sources.
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2.2
KNIME is an open source software and it helps create data science applications and services. Being open, intuitive, and able to integrate new developments, this platform makes reusable components accessible to all the users and helps understand data science workflows. The software provides actual data analysis as well as a number of processes and has productivity funtions to help operations.
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Sisense makes the analytics process easy for users right from the preparation of data to the creation of insights. Sisense is an intelligence software known for its agility and easy implementation. It can be used by varied companies. This platform offers a range of business analytics features. It is designed to make complex data preparation and visualizations simple to make better business decisions and intelligent strategies.
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1.9
Domino delivers predictive models using ML and AI techniques capturing all the dependencies of experiments. It is perfect for models across cloud databases as well as distributed systems. Powering model-driven organizations to rapidly create and convey models that drive business impact.
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1.8
Cloud-based Predictive Intelligence is used to generate insights into the behavior of customers and provides recommendations based on these insights to enhance revenue generation. Delivers reliable and customized experiences over each interaction point through a flexible, adaptable, and versatile stage that addresses enterprise needs.
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1.8
Lytics enables organizations to customize commitment with clients through its advanced Customer Data Platform (CDP) and enables organizations to arrange more relevant showcasing. This platform is easy to use and learn for it allows easy integration with various database and tools. It provides services to all the customers and helps companies arrange relevant marketing through Customer Data Platform. It also helps clients understand the audience behaviour with its website.
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1.2
Cutting edge projects delivered within deadlines. This software is majorly used by marketing and sales teams. It combines machine learning and artificial intelligence and empowering both, sellers and buyers. It is used to create and implement marketing campaigns and is compatible with most platforms. This software also helps users discover new sources of income.
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1.2
The platform is designed for B2B enterprise revenue teams, built specifically for the needs of marketing and sales teams. It is built for for revenue-driven marketers. It offers self-service AI, real-time business graph solutions, and over 50 billion dynamic signals, this platform can help you resolve a number of marketing and business intelligence concerns.
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Harnessing advanced artificial intelligence/machine learning to deliver better experiences and enhance business execution at scale. Opera Solutions offers AI solutions is supported by a team of data scientists that are scalable, practical, and transformative. This solution serves various industries such as financial, hospitality, healthcare, travel, retail, and telecommunications. In addition, problems related with scaling Big Data analytics gets solved by the AI/ML platform provided by the company.
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Figure Eight is a platform that uses both machine and human intelligence to transform data available in varied forms into a customized one for a number of use cases such as intelligent chatbots, autonomous vehicles, natural language processing, consumer product identification, and others.USP of this platform is Human-in-the-Loop Machine Learning stage changes unstructured content, picture, sound, and video information into customized high-quality data.
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2.2
Kognitio empowers data analysts and business clients to run a large number of complex questions simultaneously, providing a competitive edge to large-volume business data activities. Kognitio is an immensely flexible platform that has the strong feature of viewing images and executing complex manipulations on images using standard SQL queries. It can be deployed on both, an existing framework clusters or on a complete standalone one, on-premises or on cloud.
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