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M<br />
FOUNDATION<br />
Even as it may be difficult to crystallize the penetration of online grocery<br />
models in India, under a successful hybrid model, we believe the<br />
potential for online penetration could be even higher (as is the case<br />
in China and South Korea).<br />
Assuming India’s online grocery penetration moves to ~6%, this<br />
could represent opportunity of US$30bn. To put this in context,<br />
that's 1.7x the current cumulative eCommerce revenue pool in India.<br />
In addition, a hybrid model may also resolve the friction in online<br />
apparel retailing in terms of customers seeking to try on clothes/<br />
shoes to ensure that they fit well. We do envisage a situation where<br />
eCommerce companies deliver clothes to a predetermined brick and<br />
mortar retail store where consumers can use the infrastructure to<br />
check the fit, with on the spot returns for a seamless transaction with<br />
lower fulfillment costs.<br />
…and potential to establish a scalable (and profitable) business<br />
model... Imagine that a customer orders groceries worth Rs800 with<br />
20 SKUs on the mobile app of a eCommerce platform. Upon<br />
checkout, the app is able to offer precise delivery time (say, two<br />
hours) for 18 SKUs that are available in the affiliated brick and mortar<br />
store that is within a 5-10 km radius of the customer. The remaining<br />
two SKUs will be fulfilled within 48 hours from a central warehouse.<br />
This arrangement has re-created the convenience of traditional mom<br />
and pop retailers for the consumer. It is also likely that customers will<br />
tend to order SKUs that are available for express delivery and hence<br />
be willing to consider product substitutions that may be recommended<br />
by the app (based on the customer profile), maybe with a<br />
discount to further entice the customer.<br />
Exhibit 31:<br />
How the hybrid retail model could work<br />
Store dispatches 18<br />
products for a 3<br />
hour delivery<br />
12.10pm: Customer orders<br />
20 products via the app<br />
App suggest product<br />
substitutions<br />
for 2 products<br />
Brick and mortar store<br />
affliated with e-Commerce<br />
3.10pm: Customer receives<br />
18 products from the retail<br />
store<br />
Shopping list<br />
Based on consumtion<br />
patterns, retailer can use<br />
big data to offer curated<br />
promotions<br />
18 products available for<br />
express delivery<br />
2 products to be delivered<br />
in +2 days<br />
Customer accepts product<br />
suggestions/ All 20 products<br />
to be delivered via store<br />
Central warehouse<br />
3.10pm: Customer receives<br />
all 20 products from the<br />
retail store<br />
+2 days: Customer receives<br />
2 products from<br />
warehouse<br />
2 products to be<br />
delivered in 2<br />
days/48 hours<br />
Source: Morgan Stanley Research<br />
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