Web Crawling and Text Mining for a Leading Home Appliance Manufacturer and Retailer
From changing customer preferences and regulatory changes to constant innovations and rising competition, businesses in the home appliance market space face constant challenges in terms of increasing sales revenue or increasing their market shares. Additionally, the need to stay updated on technological innovations and the need to cater to the requirements of the cost-effective customer base also increases the operational costs and significantly reduces the sales revenue. With various benefits including the ease of purchase and discounts, there is an increased customer preference towards e-commerce platforms. As a result, consumer goods manufacturers face the dire need to focus on benchmarking product prices based on the feedback from different consumer segments and third party retailers and competitor pricing.
The Business Challenge and Quantzig’s Approach
To identify potential growth opportunities, the client – one of the leading home appliance manufacturers and retailers in Europe – collaborated with Quantzig to conduct a web analytics engagement that would help them develop a solution to optimize price points, marketing strategies, and enhance product features and offers based on customer feedback. Due to the intense level of competition in the home appliance space, the client was facing significant issues in terms of improving sales revenue and market shares. As a result, an effective solution that would help them improve pricing and promotion scenarios across multiple categories of products based on price elasticity and demand.
The primary objective of this web crawling and text mining study was to optimize price points and benchmark competitors to streamline their focus on customer segments using targeted campaigns. Additionally, the business intelligence study analyzed the behavior of online retail users and sales and benchmark product prices.
To meet the specific requirements of the home appliance manufacturer, Quantzig’s team of web and social media analytics experts developed an effective solution based on sentiment analysis, supplier analysis, and sales forecasting. Moreover, to gain a clear understanding of the business, our analytics experts also developed various analysis models and collected information on various parameters including historical sales, product, online price and sale price, discounts, and product reviews.
An overview of the data used and models applied are given below
Business Benefits and Insights
With the objective of helping the leading home appliance manufacturer and retailer improve the pricing and promotion scenarios across multiple products categories, a dedicated digital analytics team with considerable experience in conducting similar web analytics and price benchmarking studies, offered an effective web crawling and text mining solution to optimize price points and enhance product performance. By analyzing information from user reviews and ratings, we also helped them deliver incremental value to shoppers in their shopping experience and create personalized experiences and custom offers. Furthermore, by identifying drivers and analyzing the level of customer engagement, this web crawling and text mining solution identified prospective customers and design targeted campaigns to increase cross-selling opportunities.
By tracking more than 5000 price points across the websites specified by the client, our web crawling and text mining solution offered highly scalable solution with 99% uptime and data accuracy and real-time insights on dashboards with customizable features. Additionally, we also analyzed brand performance based on the product volume in various sales rank buckets by geography, category, and product and helped the client benchmark the prices of their products against competitor offerings and third-party retailers. Other than designing an effective pricing strategy, our solution had an impact on discounts and sales and understand the performance trends for top products.
In a span of just eight weeks, this web crawling and text mining assessment helped the leading consumer goods manufacturer in Europe gain insights in identifying top selling retailers and how sales of their various products were affected by stock keeping strategies of third-party distributors. By analyzing customer sentiment at the brand and category level, we also helped the client in improving the approach of their sales representatives.
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