Purchase Abandonment Predictor

From Computer Laboratory Group Design Projects
Revision as of 15:44, 14 October 2013 by afb21 (talk | contribs)
(diff) ← Older revision | Latest revision (diff) | Newer revision → (diff)
Jump to navigationJump to search

Client: Philip Wilson, The Hut Group <Philip.wilson@thehutgroup.com>

There are many online shopping sites where users become frustrated - they can't find what they want, get bored, or simply fail to complete a purchase. Retailers would be happy to help out such customers, if only they knew which ones were most likely to benefit. If you could predict which shoppers are about to abandon their shopping basket based on click stream analysis, then it would be possible to offer the customer incentives to stay on the site. Incentives could be discounts, pop-ups or contextual product recommendations.

If successful, the system may be trialled on a large popular e-commerce site such as MyProtein.com, LookFantastic.com or IWantOneOfThose.com.