“You never let a serious crisis go to waste” – I am sure most of us would have come across this line in the recent times (… a little too often if I may add). Many firms with aspirations of gaining the pole position in e-commerce are putting this quote to practice. They are revisiting a not-so-successful experiment from the recent past – market place led hyperlocal e-commerce in grocery. Their moves are driven by two phenomena:
- Increased adoption of grocery e-com due to social distancing and lack of off-line options
- Lowered customer expectations : “some order fulfilment” could easily delight the customer in the times of lockdown. In the business-as-usual scenario, “full-order-fulfilment in determinate time” determined the level of customer satisfaction and subsequently the success of the platform
Customer expectations will start increasing as we inch closer towards business-as-usual pre-COVID days. “Full-order-fulfilment in determinate time” will start regaining importance. In the past, many heavy-weights have moved away from a market place led approach to an inventory led approach as they couldn’t effectively address this customer need. If rumours were to be believed, an e-com goliath bought a significant stake in a professionally run national super market chain as they couldn’t accomplish this.
Success in meeting customer expectations will determine the answer to the titular question. Ability to estimate stock levels at partner stores without significantly changing partner’s operating practices will hold the key to meeting raising customer expectations. Our point of view is rooted in three experiences:
- Our own attempt at running a hyperlocal platform between 2013-15
- Our attempt at galvanizing a 500+ store strong association of super markets in starting an umbrella e-commerce market place for member stores and
- Our more recent experiences of enabling a hyperlocal e-com giant and a large multinational brick & mortar retailer start their grocery e-com operation
Hyperlocal grocery e-com is a tight rope walk between managing delivery costs and managing customer expectations. Typically, sophisticated algorithms are deployed to navigate this tight rope walk. Stock level at partner stores, proximity of partner store to customer and proximity of delivery executive to the partner stores are key inputs to such algorithms. In the Indian context, stock level information is largely unavailable and if available, unreliable. On digging deeper, issues start surfacing at three levels:
Layer 1: 90% of grocery business1 in India happens through the ubiquitous Kirana stores where digital logs are non-existent. Digitizing Kirana stores has many benefits to both the Kirana stores and the ecosystem. Tapping into hyper local e-commerce is one of them. Many start-ups (including us) and industry majors are trying to address this challenge. Most of the efforts in this area deploy a mobile / light weight billing system at the Kirana store. This approach is yet to accomplish scale. One of the pioneering organizations founded in 2013 has a digitized less than 10k stores from a universe of 6,000k+1,2. One may wonder why the scale-up is slow given the benefits to the retailer and the eco-system. This question would require another essay to do justice, but here is the headline – they require sizeable changes in the ways of working at the store.
Layer 2: We need to look at stores that contribute balance 10% of business to understand this layer. A super market is a quintessential example of this type of store. These stores have technology tools supporting their operations. Most of the stores that you see in Hyperlocal apps today belong to this category. While they help in establishing an MVP (minimum viable product) they don’t scale well due to intensive purchase operations. Purchase and Sales logging are needed to track stock levels. Almost all these stores log sales comprehensively but purchase logging is not as disciplined. 75% of the unbranded super markets3 (independent self-service stores, local chains) do not log their purchase. Many branded chains are disciplined in both sales & purchase logging but are affected by Layer 3
Layer 3: A hyperlocal ecosystem needs a common language for it to flourish – both in product standards and technology standards. Consider Lifebuoy total 10 125g bathing soap. We surveyed about 50 super markets in Bengaluru to see how they catalogue this product. We found 24 variations of the same name in the systems of these retailers (refer exhibit below).
Imagine the plight of an e-com platform in clustering these names together. One may be tempted to use the barcodes as a product identifier. While this is a better mechanism than raw product names, it is not robust – a simple googling of 8901030721793, 8901030762093, 8901030637216, 8901030590634, 8901030627361, 8901030645808 will give you the answer. All these barcodes map to “Lifebuoy total 10 125g bathing soap“. A strong AI backed methodology or a large workforce needs to be deployed by the platform to fill-in the gap created by the lack of a standard product language. On the technology standards front, high proliferation in the number of billing systems in the market poses a challenge. Over 80+ billing systems (largely unorganized) exist in Bengaluru market alone3.
These challenges are tough nuts to crack. However, technological innovations and changes in the environmental factors make us hopeful of it being “the next big thing”. Specifically, we are kicked because of these 6 trends:
- Increased competition in the hyperlocal e-commerce game4,5,6
- Incentivization by governmental organizations to digitize SME businesses7,8,9
- Evolution of computer vision in addressing digitization challenge at Kiranas10,11
- Increased focus on AI led solutioning by hyperlocal e-commerce platforms and billing system providers4
- Increased collaboration of upstream players with platforms12,13,14
- Increased awareness and adoption of e-commerce for grocery due to the COVID-19 lockdown
(all urls last visited on 18th May, 2020)