At Quantzig, we adopt a comprehensive approach to analyze your product categories and other offerings. A part of this approach involves leveraging machine learning and AI tools to examine category performance data through category analysis to help businesses gain insights into profitable product categories. By putting machine learning and natural language processing to good use, we not only help retailers gauge massive amounts of unstructured data sets but also help them better understand customer behavior for each category.
Businesses that emerge successfully from the shock waves hitting the retail industry will be those that redesign their store layout and supply chains to meet the ever-growing customers’ demands. With changes in business models and the shift of power to customers, it has become necessary to adopt a comprehensive approach to retail category analysis - one that focuses both on the customer and the categories required to meet the growing demands of the customers. Our retail category analysis solutions can help retailers tackle challenges arising due to such factors through advanced analytics-based solutions.
While analyzing product categories, businesses are inclined to determine the size of the category. While this may seem relatively straightforward, it can become somewhat more complicated. As such, the need to consider category size from potentially unusual perspectives has become crucial for retail companies. Our advanced category analysis solutions help you to do just that by offering in-depth insights on category size.
In today’s complex retail scenario, a fine-tuned approach to analyzing category growth has become essential for making the right choices about where to compete. To succeed in such a scenario, we believe that companies need to adopt advanced business models that have a significant impact on category growth and revenue.
Uncover the relationship among different product categories using category analysis and devise new strategies to better position your products. Our category association analysis solutions are designed to offer better insights into the correlations between different product categories, helping you manage your categories better.
By redesigning the store layout plan based on data clustering methods, businesses can optimize their product categories and drive measurable improvements in sales. Our category optimization solutions help businesses avoid the proliferation of underperforming SKU’s that leads to poor forecasts, out-of-stock scenarios, and dissatisfied customer base.
Quantzig’s product category analysis solutions help retailers to gauge product affinities to identify new cross- selling and up-selling opportunities across categories and customer segments and create eﬃcient product bundling strategies, along with optimized shelf planning and category management.
Our category analysis solutions offer proven methodologies that are rooted in machine learning and affinity mapping to help retailers conduct profit-loss analysis to analyze factors leading to a reduction in sales volume, sales revenue, and product market share.
Using a price planning and optimization solution can dramatically increase the speed of retail decision making. Our price sensitivity category analysis models help you create competitive prices while ensuring maximum profit margins.
An analytics-driven demand transference model helps retailers to calculate the transfer of demand in response to assortment changes.
A successful product launch involves preparing for its impact on your existing customer base and your organization as a whole. Our product launch impact analysis solutions offer in-depth insights to help you measure the success of your product launch based on key metrics.
With real-time footfall data being the key driving force behind increased engagement rates, dwell time and sales, it has become crucial to analyze footfall data to obtain a granular overview of in-store activities that help assess the impact, performance, and the overall success of your marketing initiatives.