To state the obvious: Kirana stores are here to stay. These small, frugal mom-and-pop stores have successfully withstood headwinds from modern retail, e-retail, and the aftermath of GST and demonetization. The last two regulatory whammies had kiranas experiencing a 20-40% drop in sales temporarily, but they quickly bounced back and continue to be the fastest growing channel for FMCG with roughly 90% market share.
So we decided to do some research on what’s working for brands in the kirana market. Here are some insights.
In our last post we talked about how differential pricing can help premium brands get a piece of the pie. We decided to take a deeper look at how brands are winning in kiranas through smaller pack sizes and lower prices.
As is clearly visible the highest-selling SKUs in kiranas tend to be the cheapest ones in many cases. Exceptions are mineral water bottles, atta, oil etc. where the larger pack was sold in higher volumes
After GST revisions, moving many household goods from the 28% tax bracket to the 5-15% bracket, FMCG companies like HUL, Dabur, Amul, GSK, Procter & Gamble and Nestle are already cutting prices in order to pass on the benefits of the rate reduction to consumers. This should help FMCG brands produce smaller & cheaper variants of their products to win sales from the price-conscious clientele in kiranas. Maa, a popular mango drink released a Rs8 version of their drink which is flying off the shelves. Dark Fantasy a premium biscuit also recently released a miniature version priced at Rs 10 targeted for kiranas.
When Coca-Cola India and Southwest Asia president T Krishnakumar announced that 2/3rd of Coca-Cola’s beverage portfolio in the coming years is going to comprise localised drinks, many felt it was a decision long overdue. With regional brands, accounting for well over 15% share of the estimated ₹22,000-crore soft drink category, it is high time that bigger brands started tapping into this segment.
Apart from food & beverages, local brands tend to dominate in India and this is true across categories barring just a few.
Arasan, a popular South Indian brand, sold 3.5 times more than the national brand Rin in Mysore in 2017 in kiranas. This pattern is true for other geographies too — in Kolhapur, local brand Tip Top detergent was ahead of Rin by 26%. If you take oil as a category, Gemini dominates in Kolhapur, Naturalle in Telangana, and Sunpure in Karnataka — all local brands (Gemini was largely a local MH brand before Cargill acquired them).
In snacks, you have Balaji overtaking Lays in Mumbai and Maiyas doing better than Haldiram’s in Bangalore. The thing is, local brands have a sense of what the customers in their area want. They are then able to build a product that suits local tastes and markets more effectively.
To truly win the local markets, bigger brands need to emulate local players and concentrate on understanding local tastes, and preferences and accordingly evolve their product and market strategy – Paperboat’s success with flavours like Jal Jeera, Aam Panna, Bru launching a Karnataka-specific coffee based on local tastes are some of the examples and most major brands would need to understand these trends and product products suited to local tastes. Simple tactics like custom packaging to include the local script has seen improvement in sales too.
Just a couple of days back when I walked down to a corner shop to grab a couple of packets of my nephew’s favourite packet of Lay’s, I found myself in a very familiar situation. The shop had run out of stock of that particular flavour of Lays. I did what I always do in such situations: bought his second favourite thing; an ice cream cone and headed home.
Brands typically lose between 8-30% of sales due to out-of-stock (OOS), an FMCG problem as old as time.
A retailer is typically serviced weekly or fortnightly depending on the geography. As a result, he buys enough stock to last him until the next cycle. With the problem of limited capital and real estate, a retailer ends up stocking only 650 to 1000 SKUs whereas HUL with a 30% share of the shelf alone has about 3000+ SKUs which can be sold at a retailer.
However, in the absence of any tool to predict variable consumer demand or in case of a delay in the delivery of fresh stock, he can find himself in a stock-out situation. As we saw, consumers in such situations either look elsewhere or settle for a similar product from a different brand. Frequent occurrences of such situations make customer retention even harder for the retailer.
What can brands do to overcome this situation?
The only way to overcome this situation is to increase the frequency of orders a retailer can place so he can order more frequently and in proportionally lesser quantities.
If the 10-day procurement cycle is reduced to 3 days he can stock up to 3 times more SKUs with the same capital and employ his shelf space better. With the faster rotation of his capital, he is able to stock better and increase his return on capital employed.
Brands like Britannia & ITC are already working to further increase the efficiency to a “zero-day” inventory distribution model by directly servicing retail outlets every day. Britannia claims that they have seen up to 3 times increase in sales in outlets they service directly. Taking a leaf out of their books, brands must rethink their distribution strategies and work on creating the leanest possible distribution network
(In the next story we’ll also talk about a successful, profitable Just-in-Time distribution POC we conducted in Mysore and Kolhapur.)
In today’s age of real-time data made possible through mobile applications, data plans and the cloud, FMCG companies use decision analytics at every step in their operations to correctly predict what to market, how to market, and how much to push into their supply chains are clearly winning.
In tier-2 towns brands are heavily reliant on distributors for their local knowledge and reach. But by capturing hygienic data at every point of their supply chain brands can assess product performance independently: analyse geography-wise product acceptance and outlet-wise offtake.
With various parameters like seasonality, offtake, pricing, outlet category, order patterns, ATL/BTL, trade promotions and schemes a strong demand forecasting model can “suggest orders” with high accuracy which can reduce OOS situations by a considerable percentage. A predictive sales & supply model has improved retail availability and fulfilment by 23-42% in the brands that we researched.