Key metrics for FMCG brands during the time of the lockdown
With major big box retailers and e-commerce struggling to fulfil orders due to supply issues and lack of manpower, major FMCG brands are now looking to kirana stores to fulfil orders. With various SKUs still going out of stock frequently at kirana stores, the brand marketing/sales are having sleepless nights with regards to the impact of lockdown on their sales. These are the key burning questions that FMCG brands are and will look at for (at least!) next two months:
- How is the total sales of the Kirana stores getting impacted? (Broken down by food and non-food. Also, broken down into Before lockdown, During lockdown, After lockdown)
- How is their category sales impacted?
- What sizes/SKUs are being bought in these categories? Is there a change in trend on size being bought and price paid?
- How is their brand share doing in each of these categories?
- Is there any trends within Kirana in terms of Geography, Size of store?
- Has their brand share in each of the consumer’s basket increased or decreased?
- How much inventory to build around essential v/s non-essential items during the next three-six month?
- What is the dip/surge in the sale prices by SKUs/categories?
- How is our each shoppers segment behaving and how big is each segment (premium vs. popular brand buyers, large vs. small pack buyers)? Are there any skews towards particular brands in their baskets across the SKUs they buy?
Considering that traditional trade is still fragmented with nearly 12 million stores across India, it is going to be a big challenge for FMCG brands to gather real-time data intelligence with regards to what is being sold at the kirana stores and how the consumers are behaving right at the point of sale especially during the lockdown; thereby making it difficult to plan short-term and optimise the operations.
Our cloud-based PoS solution installed in various kirana stores across the top 7 cities has enabled us record data relating to shopper basket and we are now seeing interesting patterns/stories unfolding before us with respect to the category movements and basket-level transactions. For eg: Milk, which is usually present in a steady 5% of the baskets, made a sudden jump to 14%, reflecting either less than optimal milk delivery that day or possible advance purchase for future use.
We are currently monitoring the data with respect to various brands/categories in real-time and we can provide you with insights relating to your brand(s)/category for the lockdown period and beyond. The insights that we can provide includes (a) Share of stores (% of stores selling a brand v/s category presence) (b) Brand and category share % in shoppers’ baskets/ bills and (c) Brand’s share of GMV (spends) out of the category. Please write to us at email@example.com for more information.