The Proof of the Pudding …

Everyone knows that the real value of something can only be judged from practical experience and results; not from appearance or theory. And that’s exactly how one should measure any AI implementation – from the outcome of its application.

This is essential to clearing the hype around AI and focusing on methodologies that drive pure value. We believe that AI is the way forward and to substantiate, we’ve put together a case study to showcase how AI can bring true value to your business processes.

The Client: A global retail chain which sells products, both online and offline.

The Implementation: A behavior scoring model to generate machine driven recommendations, in order to resell/upsell products and drive revenue.

The Test: After six months of implementation, we ran up a test to understand how the logic fared. We filtered out data of all machine based recommendations that were triggered by specific customers, and see if they purchased the same product as recommended within a timespan of 0-5 days.

The below chart shows the outcome of the recommender logic.

 

The Results:
A total of 184,712 users responded to the targeted recommendation
33,358 users purchased in less than 24 hours.
32,080 users purchased within 24-48 hrs of the recommendation being sent.

The machine had recommended about 2,000+ unique products to 20,000+ unique customers, based on their behavior. It generated revenues worth $14M in six months

This is proof that AI based Recommender Systems can make a big difference in the way businesses channelize their revenues and contextually engage their customers.

About Plumb5 Recommendations

Plumb5, which uses a context-based collaborative filtering technique, delivers highly effective recommendations with the high conversion rate to some of their retail and banking customers. The main contributor to the effectiveness of these recommendations is that Plumb5 works in real-time by ranking in run-time, a technique similar to the continuous-time Markov Decision process.

Click here to read more on how Plumb5 Recommendations work

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