🔍 How Blinkit built their Search Ads Engine
Discover how Blinkit developed their search ads product and explore the nuances of the Q-commerce industry by watching the latest episode of Scale by Airtribe. 🚀
Every marketplace, once it reaches a certain scale and distribution, begins to monetize by developing an advertising platform. Blinkit was no exception to this trend. This edition is based on a firsthand account from a Product Manager at Blinkit, who spearheaded the creation of their Search Ad Engine during the pandemic. We dive into the deliberate choices they had to make, the adjustments implemented, and the results they secured.
First, let's begin by examining some key data points that influenced Blinkit's decision to prioritize Search Ads over other options.
55% of e-commerce users shop via Search
Search provides the best conversion tracking data for product purchase
Many advertisers on Blinkit also advertise on search ads on platforms like Amazon and Google, and they deeply trust search ads.
Pushing for Cost per impression over cost per click
Blinkit chose CPI over the conventional CPC model. This decision allowed advertisers to pay based on the number of impressions, not just clicks, betting on potential consumer engagement without a predefined return. This model was seen as a gamble but promised higher rewards if the advertised products resonated well with consumers.
Let’s say a brand pays ₹20 for a click for a product of ₹100. The ROI is 5. It will always be 5.
Let’s say a brand pays ₹1 per impression and gets 20 impressions. The brand pays ₹20. But in those 20 impressions, the brand could sell two products for instance and get an ROI of 10. But it could also get an ROI of 0 by selling nothing.
Unique Bidding Approach
Blinkit chose an unique approach to bidding by allowing the highest bidder to pay their full bid amount, diverging from the more conventional normalized bidding process. Typically, in a standard auction:
If Brand A bids 5 and Brand B bids 3, Brand A wins but only pays 3.01.
However, at Blinkit:
If Brand A bids 5 and Brand B bids 3, Brand A still pays the full amount of 5.
To balance this approach, Blinkit permits brands to modify their bids up until the final moment of the auction. This flexibility can deter larger players from excessively high bids, thereby leveling the playing field and fostering opportunities for smaller or challenger brands. This strategic choice not only enhances competition but also encourages a more dynamic and engaging bidding environment.
Despite taking an unique approach to search ads, they faced a period of slow growth. The team started to talk to their customers and uncovered several critical areas for improvement:
Pricing Strategy Adjustment: In response to feedback, Blinkit opted to reduce prices and focus on optimizing engagement over immediate revenue gains. The initial choice of a Cost Per Impression (CPI) model proved to be a double-edged sword, as brands were not achieving sufficient sales from the impressions they paid for, leading to a decline in Return on Investment (ROI). Consequently, it became necessary to lower prices temporarily to better align with brand expectations and outcomes.
Enhanced Ad Serving Rate: The effectiveness of search ads was hindered by product availability issues, particularly exacerbated during the first wave of the COVID-19 pandemic when inventory reliability was compromised. To address this, Blinkit developed a feature allowing brands to specify multiple products for a single ad space. This ensured that if one product was out of stock, other products could still be advertised, thereby maintaining ad visibility and effectiveness.
User Experience Improvements: Recognizing the need for a more intuitive and user-friendly platform, Blinkit implemented several UX enhancements. These improvements were designed to facilitate easier navigation and interaction, ultimately aiming to enhance the overall usability of the platform for brands and advertisers.
The team later improved search ads by introducing city-level targeting to support smaller brands, significantly enhancing the quality, quantity, and frequency of information for better decision-making, overhauling the platform aesthetics for improved usability, and rapidly expanding the ad offerings to include Sponsored Display Banners and Sponsored Brand assets alongside the existing Sponsored Product.
The Results
The outcomes for our partners were notably positive, with Return on Investment escalating from below 1 to over 10, surpassing the industry standard of 5, creating a win-win scenario for all involved.
The platform experienced a tenfold increase in revenue contribution, solidifying these impressive gains as a tangible reality.
Additionally, the number of participating manufacturers expanded dramatically from fewer than 5 to over 100, and the volume of bids surged by 80 times.
Scale by Airtribe
Watch our video to learn why we think Blinkit is the King of Indian Q-commerce startups.
That’s all for today, folks! Hope you enjoyed this week’s newsletter. We’ll see you in the next edition. 🤗
Until then, keep learning and growing! 👋