Anindya Ghose, Stern Business School on driving performance with analytics

Use Case

Sometime back while travelling in Beijing, I took this picture:

The picture is a perfect tool to visualise the experiment that Anindya Ghose, who is the Heinz Riehl Chair Professor of Business at NYU’s Stern School of Business and the Director of its Masters of Business Analytics Program, and his team conducted across various cities in China.

In the field experiment, they sent out ~14k mobile coupons across to ~10k users. They then tested if commuters were more likely to respond to those coupons when in the subway. The results showed that peak commuting hours were actually the best time to send a marketing coupon (and I imagine then, also a push notification for your app). It also led to some other very unique insights. Here’s a quote from the paper.

The key findings indicate that commuters are about three times as likely to redeem their first mobile coupon compared to non-commuters.

…suggest that enhanced receptiveness to mobile coupons is more perceivable when users obtain multiple coupons.

Moreover, coupons with short expiration dates more successfully improve the response rates of commuters than do coupons with long expiration dates.

-From Seizing the Commuting Moment: Contextual Targeting based on Mobile Transportation Apps

This is but one example of many which the man himself, Prof Ghose talks to us about on this episode of the Use Case podcast. On the show, we dive deep into PRACTICAL ways using which data and analytics can be used to improve business performance.

You could listen to the full episode on the audio file above or in your favourite podcast app and for more such content, subscribers to the Turnaround Newsletter - to stay abreast with the latest from the world of tech and startups in India.

If you’d like to read instead, here are a few papers by Prof Ghose which I mention in the episode:

* Deriving the Pricing Power of Product Features by Mining Consumer Reviews

* Trade-offs in Online Advertising: Advertising Effectiveness and Annoyance Dynamics Across the Purchase Funnel

Let’s push our performance graph upwards!

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