Decoding the ‘Minimalist’ Way to Maximizing Revenue Growth

The ‘Mexico Crowd’ is how Aditya Mishra of Minimalist describes shoppers on Quick Commerce (QComms). What he means is that these are shoppers who value convenience over price, willing to pay a few extra rupees for the ease of a door-step delivery!

That also means that this crowd is not easily swayed by discounts. They need a good product and they need it delivered in 10 minutes. To achieve this, brands need an efficient supply chain system coupled with performance marketing that brings the right products before the right audience.

For Minimalist, these were the first valuable insights that emerged on partnering with GobbleCube in their journey to grow revenue and market share on QComms.

While the brand was able to see faster resolutions for problems related to availability, listing, discounting and competitor strategies, one of its biggest successes with GobbleCube has been in optimizing ad spends.

“Insights from GobbleCube gave us an opportunity to divert ad spends towards products that had low organic SOVs to improve our sales, defying traditional logic that tells you to increase ad spends on best-performing SKUs to do that,” says Aditya who is Growth Manager (Quick Commerce) at Minimalist.

The skin, hair and body care brand has created more hero-SKUs, improved listings, fixed availability, optimized ad spends, increased market share, among others, all within a span of three months of associating with GobbleCube.

Aditya sat down for a detailed chat with us to share his stories of Minimalist’s QComm success story and how GobbleCube was an integral part of this journey.

Highlights from the conversation:

With GobbleCube, the time-taken to identify a problem has become near zero at this point.

To begin with, there are three parts to getting a QComm problem fixed - identifying the problem at our end, communicating it to the platforms which involves presenting the data in a way that’s easily understandable and the platforms solving it at their end.

The time-consuming task has always been the identification of the problem which earlier required a lot of data work at our end. But with GobbleCube we can see the problem right in front of us, on the dashboard. Identification happens in real-time.

The time taken to communicate the problem to the platform has now come down by nearly 50% because we still need to present data to the platform.The last part can only be achieved with follow-ups and regular calls.

We’ve seen the quality of the solution improve significantly in less than half the time taken before.

Our OSA (On-shelf Availability) on one of the platforms had dropped to 30% but we could not identify this earlier because we only had warehouse SOH (Stock on Hand) data. We had no clue what was happening at the dark-store level or why our sales had dropped.

GobbleCube’s insights on availability was a game-changer for us. We were able to track availability at the city and SKU-level and also monitor listings. For instance, SOH data showed that we had 3000 products in stock and the DRR (daily run rate,i.e, no.of units sold daily) is 100, so the stock is available for 30 days. But GobbleCube data showed us that we were available in only 20 of the 100 dark stores. Now if we were available across 80 dark stores, our DRR would have been higher. So by communicating this to the platform ensuring the stock is circulated on dark store level, the OSA was improved to 70% as a result of which we saw a 2X jump in our September sales vs August, with zero marketing intervention.

In another example, an SKU of ours was delisted from one of the platforms because it had a DRR of 5 or 6. GobbleCube’s data showed us that historically this SKU was made live only in Delhi, and nowhere else which is why the DRR never picked up. Earlier preventing such a delisting would have been out of our hands. But now, we are listed in the right localities, maintain good DRRs, and can detect and prevent delistings faster.

QComm is a place where supply chain matters a lot and that is where you will need to do a lot of interventions. Now that my bandwidth from managing supply chains has been freed because of data from GobbleCube, I can focus on scaling up marketing efforts, tweak my campaigns more frequently and focus on other growth levers from a marketing PoV rather than just solving for availability all the time.

We were running ads on one of our best-selling SKUs. But when we saw GobbleCube’s organic and ad SOV data for it, we were surprised to learn that it was doing well organically and was already ranked No.1 in the category. Even if we had not run ads on this SKU, its sales would not have been affected by much

So the insight here was that our ad spends were not being optimized as earlier, ROAS was the only parameter by which we could judge the performance of the campaign. The SOV data gave us an opportunity to divert ad spends towards SKUs and keywords where we had low SOVs and improve our campaign strategies. Diverting also helped us identify and build other hero-SKUs.

Further, along with tracking competitor keywords, GobbleCube also helped us identify all the high volume keywords that were relevant but missing from our campaigns. This helped strengthen our existing campaigns and create more relevant ones.

Tweaking our campaigns based on these insights led to a massive improvement in our ROAS  too, which went to 1.4 from 1 in just two weeks.

Cross-platform SOV data, on the other hand, helped me understand which SKUs are under-indexed or over-indexed on a particular platform. If there is a stark difference in the SOVs for the same SKUs between platforms, then the problem is either POs not being raised of appropriate quantity or campaigns not being optimized.

After identifying the outlier platforms I could do a deep-dive RCA to bring up platform SOVs for the affected category by reviewing POs, campaigns, etc.

With GobbleCube, I can see what is happening, why it is happening and how I can resolve it.

One of the things we struggled with was lack of attribution data for the ads we were running on the platforms.

For instance, the CPM for one of our SKUs we ran ads on was 500. But two days later my product was not available on that keyword. Turns out the CPM had gone up at the platform’s end. We did not find out about it until much later when our sales had been affected by it.

This is where having GobbleCube on our side helped because we had visibility into our ad SOVs. We could monitor whether the ads are working or not and then we could dig deeper to find out why. And all of this in real-time. The result? Our sales on this platform have tripled in the last three months.

Discounting was tricky for us to keep a track of successfully. There were discrepancies across discounts that were being offered on our products by some platforms.The main problem here is that discounts can vary with locations, unlike the E commerce channels wherein this parameter is rather more stable. The only way to monitor this earlier was to manually check for random locations or when the price disparity was escalated to us by the competitor platforms. With data on average selling price, PPU, discounting across SKUs, platforms, locations and competitors, GobbleCube helped us gain better control over our discounting strategies.

Earlier, we were looking at absolute numbers - so a 50% month over month growth on a platform was a big deal for us. Now that we have access to category share data with GobbleCube, we are able to benchmark our performance better and get a real sense of how we are growing. Now a 0.2% growth in category share is more relevant than just growing sales by 40%.

Access to overall market share as well as category share also helps us optimize ad spends as we can now focus on SKUs with declining category share. More importantly, the data made it clear that a rise in DRR does not necessarily mean a rise in category share.

Competition mapping earlier involved us calling the platform to ask about our performance. Platforms can’t share brand numbers so there was no way to compare and benchmark our performance with others.

But now we can see those absolute numbers daily which gives us a better understanding of category performance. We are now able to benchmark our performance to the overall category growth with GobbleCube’s data.

So we track competitor SOVs, OSA%, and when I know that my competitor is gaining market share, there are certain metrics that I can track directly on the platform which gives me an idea of what they are doing and where I am going wrong. But this is more qualitative at this point; there are no hard and fast rules.