Assortment and Allocation of Short Lifecycle products [704KB]

Retailers of products with short life-cycles (Apparel, DVDs, CDs, electronics, books, and toys) face issues in deciding store assortment and allocation due to non-availability of 'comparable' historical product sales data and due to significant variation in demand patterns between stores. We highlight a five-step methodology to optimize store-level assortment and allocation for such products. Our approach involves segmentation of stores and products on historical sales data adjusted for stock-outs and mark-downs.

Next Best Product Models for cross-selling financial services [495KB]

'Next Best Product (NBP)' models predict the next product/service/offer that a customer is likely to buy/use, given the customer's previous purchase history in the same category. In this article, we present an NBP framework for financial services companies.

NBP models are particularly effective in cross-selling where data on past selling activity is not available (e.g., Relationship banking) or when there have been few co-ordinated cross-selling efforts. NBP models can also be used along with campaign response models.


KF celebrates 7th anniversary

15 June, 2015

Knowledge Foundry celebrates 7th anniversary.

KF named among the '10 Emerging Analytics companies in 2013'

29 June, 2013

Analytics India Magazine listed us among the top 10 Emerging Analytics companies to watch in 2013

KF's views on the Big Data hype

20 Oct, 2012

The meaning of Big Data has become more diffuse as it has grown in popularity. Read about our views on the topic on the Analytics India Magazine website.

Interview of our CEO, Raj Bhatt, featured in Analytics India Magazine

19 Oct, 2012

Knowledge Foundry CEO, Raj Bhatt, recently got interviewed by Analytics India Magazine. Read on to find more.

KF joins forces with Knolseed Technologies for SaaS BI and analytics solutions

01 Oct, 2012

Knolseed Technologies founders, Raghuram Sreenath and Mohan Varadarajan, join Knowledge Foundry as VP, Engineering and VP, Products respectively, to lead development of Personalized eCommerce Marketing (PEM) SaaS solution