How VCs and Brand Rollups are using Data for faster Acquisitions

How VCs and Brand Rollups are using Data for faster Acquisitions

3rd Mar, 2022

Abhinav Gupta

By Abhinav Gupta

When it comes to brands – the biggest story of 2021 was the astronomical growth of Brand Roll-ups. For the uninitiated, Brand Roll-ups are companies that acquire multiple digital consumer brands and then scale these brands 100x by leveraging their own operational expertise across eCommerce platforms, Supply Chain, Warehousing, Marketing, and so on.

Thrasio is the poster boy for the Brand roll-ups and is valued at over 10 Bn USD.

Brand rollups have raised over $12 billion in 2021 and the trend only seems to be accelerating in 2022. Not only Brand Roll ups, but VCs too have been pouring money into digital brands. In India, 77+ brands have raised more than 2B USD in 2021. In the US this number is estimated to be north of $10 billion.

Cumulative capital raised by Amazon Aggregators
Cumulative capital raised by Amazon Aggregators

Scaling fast doesn’t come easy. It comes with its own set of challenges. So even with ample experience in running and scaling brands, Brand roll-ups are posed with unique challenges.

Challenge of Scouting the right brand

There are 1000s of online consumer brands and new ones are launching every day. Every Brand roll-up wants to be the first one to scout a brand – but this is not easy.

The challenge here is to identify & pick the right brands without having access to any sales or financial data. Every Brand Rollup has a wishlist with regards to the number of SKUs, price points, reviews, and ratings as well – but don’t have tools in place to scout brands with these criteria in mind. And across multiple platforms and categories, the problem gets more complicated.

This is an ongoing problem since a brand that was not selling well yesterday may start hitting higher sales numbers a week down the line – and that is why Brand scouting has to be a continuous process.

One way these aggregators have solved this challenge is by offering mouth-watering referral fees for referring a brand. But this is not a sustainable long-term solution.

Data Comes to the Rescue

What Brand Roll-ups need is a continuous and automated data first Brand Scouting solution to enable them to scout the right brands.

  • What are all the brands in a category of interest?
  • Which of these brands is within the filters of Number of SKUs, Price Range, etc.?
  • Which brands have shown an exceptional rise in search rankings?
  • Which brands have shown the most increase in the number of ratings and reviews?
  • Which brands have the highest gain in the customer ratings?
  • What are the estimated sales and market share of the brands?

DataWeave’s Brand Scouting solution solves exactly this.

DataWeave’s Brand Scouting Solution

DataWeave’s Brand Scouting Solution is a comprehensive solution to help Brand Rollups and VCs scout for the ideal brand that fits their acquisition profile. We leverage public data collected from multiple eCommerce platforms to get them the desired information on brands they’re looking for.

For all the focused categories (Typically 30-40) – we collect data of all the SKUs (Typically 15,000-20,000) and aggregate that at a Brand level:

  • Ranking – Usually Brand Rollups are not interested in the Brands which are on the first page. But, they are interested in the brands which might be b/w 500 to 10,000 ranks but are showing an exceptional gain in ranking week on week.
Brand Discoverability & Ranking on Amazon
Brand Discoverability & Ranking on Amazon
  • Ratings – It’s important to look at brands that are showing high improvement in ratings or have consistently shown high ratings. The proportion of 5 stars vs. 1 star is an important metric here.
  • Number of Reviews and Ratings We enable you to find brands that have both high ratings as well as a high number of reviews. This is a very good metric to find the brands in a category that are getting exceptional customer love.
Brand Popularity Tracker
Brand Popularity Tracker
  • Filters – We enable filtering in terms of – No. of SKUs, Price Range, Rating and Reviews and even can eliminate established brands so that you only see the brands which qualify your criteria. We also enable you to separately analyze brands that are buying sponsored ads in a category, so you have a clear distinction between organic and sponsored growth of these brands.
  • Trends – What is important is not just the static performance on the day of analysis – but a trend analysis over a period of time to find the brands which are growing exceptionally.
Brand Score Trend, Average Rating trend & No of Reviews Trend
Brand Score Trend, Average Rating trend & No of Reviews Trend

… but, wait there’s more.

We compliment Brand Scouting with three more solutions to provide the right context and further analysis needed to provide comprehensive insights into the category and platforms where you are scouting for brands:

Category Analytics: When you are looking at a category and the brands in that category, it is often important to understand how dynamic that category is. We can help analyze:

  • If the category is crowded with more brands per product.
  • Does it have space for new brands?
  • What is the number of new brands entering that category?
  • What is the number of new SKUs entering that category?
Category & Subcategory Evaluation
Category & Subcategory Evaluation

We can also help with benchmarking the category – to help understand how the brand that you are scouting is doing when compared to its category peers.

Rank Group versus Price, Rating & No of Reviews
Rank Group versus Price, Rating & No of Reviews

Sales & Share: We can also provide a good directional estimate of the sales and market share of all the SKUs in the category wherein you are scouting for brands. These are estimates powered by our proprietary machine learning algorithms and can help you solidify your hypothesis around a blog or a category.

Revenue by Price Points
Revenue by Price Points

Sentiment Analysis of Reviews: Customer reviews tell more about the qualitative aspects of the SKU and the brand itself. Our algorithms can help understand what features of a brand or a product do customers really care about. We can answer questions such as:

  • Which features are mentioned most commonly?
  • Which features are mentioned positively or negatively?
  • What adjective is used to describe that particular feature?
Customer Sentiment Analysis
Customer Sentiment Analysis

The suite of Brand Scouting and complementary solutions is evolving rapidly as the space is evolving rapidly. We are supporting several VCs and Brand Roll-ups globally to scout for brands.

The best aspect about DataWeave is our ability to scout brands across 2,000+ eCommerce platforms globally across geographies. We are super stoked to be playing an enabler in the Brand Rollup revolution.

Beyond Brand Scouting – Digital Shelf Analytics

The challenge for Brand roll-ups is not over by just scouting and acquiring a brand. The journey is just about starting – the next challenge that the Brand Rollup faces now is to scale up these brands.

The challenge the Brand Rollup face is unique and very different from a single brand operator or even traditional CPG conglomerates.

DataWeave’s flexible product philosophy enables Brand Roll-ups to diagnose and measure the performance of multiple brands across multiple platforms in one dashboard.

- Abhinav Gupta
Abhinav is Director of Strategic Initiatives at DataWeave. He is working closely with several QSR chains and Brand roll-up companies, helping them grow their business. Abhinav can be reached at, 3rd Mar, 2022

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