Case Study
Adsmagnify Drives a 2640% Revenue Increase and 541% ATC Growth for Clothing Brand
Case Study
Adsmagnify Drives a 2640% Revenue Increase and 541% ATC Growth for Clothing Brand
AdsMagnify helped a clothing brand scale from ₹10,000-₹50,000 in monthly revenue to ₹13,72,369 through a strategic full-funnel marketing approach. By targeting audiences across the TOFU, MOFU, and BOFU stages, we tested key ecommerce segments like Add-to-Cart (ATC), Checkout audiences, and Lookalike audiences (1% and 2%). Through tailored ad campaigns, retargeting, and continuous optimization, we significantly increased conversions, resulting in 12,807 products added to cart, 10,566 checkouts, and 2,394 unique purchases.
Client Overview: A fast-growing clothing brand generating ₹10,000 to ₹50,000 in monthly revenue approached Adsmagnify, an AI-powered digital marketing agency, to scale their business and boost revenue. The brand aimed to expand its reach, increase sales, and optimize its advertising spend to unlock new growth opportunities.
Challenge: The primary challenge was scaling revenue beyond the existing range while optimizing ad spend across profitable marketing channels. The brand was seeking a structured and data-driven approach to marketing that would target potential customers at different stages of the purchase journey and maximize return on ad spend (ROAS).
Strategy: Adsmagnify implemented a comprehensive marketing funnel strategy using a multi-step approach, divided into the three stages of the funnel: TOFU (Top of the Funnel), MOFU (Middle of the Funnel), and BOFU (Bottom of the Funnel). The team also deployed a range of audience targeting techniques, including custom audiences and lookalike audiences, to refine the customer journey from awareness to conversion.
TOFU (Top of the Funnel) - Awareness Stage:
At the top of the funnel, Adsmagnify focused on generating brand awareness and reaching new audiences who were unfamiliar with the clothing brand. We tested a variety of cold audiences through paid social media campaigns, specifically on Facebook and Instagram. The goal here was to cast a wide net and attract potential customers by using engaging creatives such as videos, carousel ads, and lifestyle images of the products.
Audiences Tested:
Broad Audiences: Targeted without any specific interests or demographics to let the algorithm find potential customers.
Interest-Based Audiences: Targeting users interested in fashion, online shopping, streetwear, or similar brands.
Lookalike Audiences (1% and 2%): Created based on the brand’s existing customers who had completed a purchase. The lookalike audiences at 1% represent the top 1% of users who closely match the characteristics of existing customers, while the 2% audience was broader, giving us more room for scaling.
Behavioral Audiences: Users who show interest in high-engagement activities like online shopping or mobile app interactions.
MOFU (Middle of the Funnel) - Consideration Stage:
For the middle of the funnel, the focus was on engaging users who had interacted with the brand but hadn’t made a purchase yet. This phase was crucial for nurturing leads and driving further interest through educational and persuasive content that helped overcome buying objections.
Audiences Tested:
Engagement Audience: Users who interacted with the brand’s content on social media (likes, comments, shares).
Video View Audience: Users who watched 50% or more of the top-of-funnel video ads, indicating strong interest.
Website Visitors: Users who visited the website but didn’t perform any specific actions.
Add to Cart (ATC) Audience: Users who added products to their cart but didn’t complete the purchase.
Initiated Checkout Audience: Users who started the checkout process but didn’t finalize the order.
During this stage, we also continued testing Lookalike Audiences:
Lookalike (1%) based on people who added items to their cart.
Lookalike (2%) based on those who visited the product page but didn’t add to cart.
BOFU (Bottom of the Funnel) - Conversion Stage:
The final stage of the funnel focused on converting warm leads into paying customers. Here, we used direct and conversion-focused messaging, showcasing product benefits, limited-time offers, or free shipping to drive urgency and increase conversions.
Audiences Tested:
Checkout Audience: People who reached the checkout page but didn’t make a purchase.
ATC Retargeting Audience: Those who added products to the cart but didn’t complete the purchase.
Purchasers: Previous customers who could be targeted for upsell or cross-sell opportunities.
Dynamic Retargeting Ads: Personalized carousel ads showcasing products users had viewed or added to their cart.
At this stage, Lookalike Audiences were refined based on purchase data:
Lookalike (1%) of users who made purchases.
Lookalike (2%) of users who initiated checkout.
Results:
By methodically targeting each stage of the funnel, Adsmagnify achieved remarkable results for the clothing brand:
Revenue Growth: Monthly revenue skyrocketed to ₹13,72,369 within the campaign period.
Average Purchase Value: The average price per purchase increased to ₹563.
High Engagement: 12,807 products were added to cart, reflecting strong user interest.
Checkout Success: ₹10,566 in product checkouts, showing the effectiveness of the retargeting strategy.
Conversion Rate: 2,394 unique purchases were made during the campaign.
Conclusion:
The detailed and structured approach of Adsmagnify’s AI-powered marketing, which combined precise audience segmentation with a well-optimized marketing funnel, enabled the clothing brand to scale rapidly. By targeting the right audiences at the TOFU, MOFU, and BOFU stages, Adsmagnify maximized customer engagement and conversions while optimizing ROAS.
This case highlights the importance of audience testing and funnel optimization for e-commerce brands looking to drive growth and revenue. With continuous testing, retargeting, and personalized ads, Adsmagnify ensured that every rupee spent delivered a high return, showcasing the power of AI-driven digital marketing.
Client Overview: A fast-growing clothing brand generating ₹10,000 to ₹50,000 in monthly revenue approached Adsmagnify, an AI-powered digital marketing agency, to scale their business and boost revenue. The brand aimed to expand its reach, increase sales, and optimize its advertising spend to unlock new growth opportunities.
Challenge: The primary challenge was scaling revenue beyond the existing range while optimizing ad spend across profitable marketing channels. The brand was seeking a structured and data-driven approach to marketing that would target potential customers at different stages of the purchase journey and maximize return on ad spend (ROAS).
Strategy: Adsmagnify implemented a comprehensive marketing funnel strategy using a multi-step approach, divided into the three stages of the funnel: TOFU (Top of the Funnel), MOFU (Middle of the Funnel), and BOFU (Bottom of the Funnel). The team also deployed a range of audience targeting techniques, including custom audiences and lookalike audiences, to refine the customer journey from awareness to conversion.
TOFU (Top of the Funnel) - Awareness Stage:
At the top of the funnel, Adsmagnify focused on generating brand awareness and reaching new audiences who were unfamiliar with the clothing brand. We tested a variety of cold audiences through paid social media campaigns, specifically on Facebook and Instagram. The goal here was to cast a wide net and attract potential customers by using engaging creatives such as videos, carousel ads, and lifestyle images of the products.
Audiences Tested:
Broad Audiences: Targeted without any specific interests or demographics to let the algorithm find potential customers.
Interest-Based Audiences: Targeting users interested in fashion, online shopping, streetwear, or similar brands.
Lookalike Audiences (1% and 2%): Created based on the brand’s existing customers who had completed a purchase. The lookalike audiences at 1% represent the top 1% of users who closely match the characteristics of existing customers, while the 2% audience was broader, giving us more room for scaling.
Behavioral Audiences: Users who show interest in high-engagement activities like online shopping or mobile app interactions.
MOFU (Middle of the Funnel) - Consideration Stage:
For the middle of the funnel, the focus was on engaging users who had interacted with the brand but hadn’t made a purchase yet. This phase was crucial for nurturing leads and driving further interest through educational and persuasive content that helped overcome buying objections.
Audiences Tested:
Engagement Audience: Users who interacted with the brand’s content on social media (likes, comments, shares).
Video View Audience: Users who watched 50% or more of the top-of-funnel video ads, indicating strong interest.
Website Visitors: Users who visited the website but didn’t perform any specific actions.
Add to Cart (ATC) Audience: Users who added products to their cart but didn’t complete the purchase.
Initiated Checkout Audience: Users who started the checkout process but didn’t finalize the order.
During this stage, we also continued testing Lookalike Audiences:
Lookalike (1%) based on people who added items to their cart.
Lookalike (2%) based on those who visited the product page but didn’t add to cart.
BOFU (Bottom of the Funnel) - Conversion Stage:
The final stage of the funnel focused on converting warm leads into paying customers. Here, we used direct and conversion-focused messaging, showcasing product benefits, limited-time offers, or free shipping to drive urgency and increase conversions.
Audiences Tested:
Checkout Audience: People who reached the checkout page but didn’t make a purchase.
ATC Retargeting Audience: Those who added products to the cart but didn’t complete the purchase.
Purchasers: Previous customers who could be targeted for upsell or cross-sell opportunities.
Dynamic Retargeting Ads: Personalized carousel ads showcasing products users had viewed or added to their cart.
At this stage, Lookalike Audiences were refined based on purchase data:
Lookalike (1%) of users who made purchases.
Lookalike (2%) of users who initiated checkout.
Results:
By methodically targeting each stage of the funnel, Adsmagnify achieved remarkable results for the clothing brand:
Revenue Growth: Monthly revenue skyrocketed to ₹13,72,369 within the campaign period.
Average Purchase Value: The average price per purchase increased to ₹563.
High Engagement: 12,807 products were added to cart, reflecting strong user interest.
Checkout Success: ₹10,566 in product checkouts, showing the effectiveness of the retargeting strategy.
Conversion Rate: 2,394 unique purchases were made during the campaign.
Conclusion:
The detailed and structured approach of Adsmagnify’s AI-powered marketing, which combined precise audience segmentation with a well-optimized marketing funnel, enabled the clothing brand to scale rapidly. By targeting the right audiences at the TOFU, MOFU, and BOFU stages, Adsmagnify maximized customer engagement and conversions while optimizing ROAS.
This case highlights the importance of audience testing and funnel optimization for e-commerce brands looking to drive growth and revenue. With continuous testing, retargeting, and personalized ads, Adsmagnify ensured that every rupee spent delivered a high return, showcasing the power of AI-driven digital marketing.
AdsMagnify helped a clothing brand scale from ₹10,000-₹50,000 in monthly revenue to ₹13,72,369 through a strategic full-funnel marketing approach. By targeting audiences across the TOFU, MOFU, and BOFU stages, we tested key ecommerce segments like Add-to-Cart (ATC), Checkout audiences, and Lookalike audiences (1% and 2%). Through tailored ad campaigns, retargeting, and continuous optimization, we significantly increased conversions, resulting in 12,807 products added to cart, 10,566 checkouts, and 2,394 unique purchases.
Client Overview: A fast-growing clothing brand generating ₹10,000 to ₹50,000 in monthly revenue approached Adsmagnify, an AI-powered digital marketing agency, to scale their business and boost revenue. The brand aimed to expand its reach, increase sales, and optimize its advertising spend to unlock new growth opportunities.
Challenge: The primary challenge was scaling revenue beyond the existing range while optimizing ad spend across profitable marketing channels. The brand was seeking a structured and data-driven approach to marketing that would target potential customers at different stages of the purchase journey and maximize return on ad spend (ROAS).
Strategy: Adsmagnify implemented a comprehensive marketing funnel strategy using a multi-step approach, divided into the three stages of the funnel: TOFU (Top of the Funnel), MOFU (Middle of the Funnel), and BOFU (Bottom of the Funnel). The team also deployed a range of audience targeting techniques, including custom audiences and lookalike audiences, to refine the customer journey from awareness to conversion.
TOFU (Top of the Funnel) - Awareness Stage:
At the top of the funnel, Adsmagnify focused on generating brand awareness and reaching new audiences who were unfamiliar with the clothing brand. We tested a variety of cold audiences through paid social media campaigns, specifically on Facebook and Instagram. The goal here was to cast a wide net and attract potential customers by using engaging creatives such as videos, carousel ads, and lifestyle images of the products.
Audiences Tested:
Broad Audiences: Targeted without any specific interests or demographics to let the algorithm find potential customers.
Interest-Based Audiences: Targeting users interested in fashion, online shopping, streetwear, or similar brands.
Lookalike Audiences (1% and 2%): Created based on the brand’s existing customers who had completed a purchase. The lookalike audiences at 1% represent the top 1% of users who closely match the characteristics of existing customers, while the 2% audience was broader, giving us more room for scaling.
Behavioral Audiences: Users who show interest in high-engagement activities like online shopping or mobile app interactions.
MOFU (Middle of the Funnel) - Consideration Stage:
For the middle of the funnel, the focus was on engaging users who had interacted with the brand but hadn’t made a purchase yet. This phase was crucial for nurturing leads and driving further interest through educational and persuasive content that helped overcome buying objections.
Audiences Tested:
Engagement Audience: Users who interacted with the brand’s content on social media (likes, comments, shares).
Video View Audience: Users who watched 50% or more of the top-of-funnel video ads, indicating strong interest.
Website Visitors: Users who visited the website but didn’t perform any specific actions.
Add to Cart (ATC) Audience: Users who added products to their cart but didn’t complete the purchase.
Initiated Checkout Audience: Users who started the checkout process but didn’t finalize the order.
During this stage, we also continued testing Lookalike Audiences:
Lookalike (1%) based on people who added items to their cart.
Lookalike (2%) based on those who visited the product page but didn’t add to cart.
BOFU (Bottom of the Funnel) - Conversion Stage:
The final stage of the funnel focused on converting warm leads into paying customers. Here, we used direct and conversion-focused messaging, showcasing product benefits, limited-time offers, or free shipping to drive urgency and increase conversions.
Audiences Tested:
Checkout Audience: People who reached the checkout page but didn’t make a purchase.
ATC Retargeting Audience: Those who added products to the cart but didn’t complete the purchase.
Purchasers: Previous customers who could be targeted for upsell or cross-sell opportunities.
Dynamic Retargeting Ads: Personalized carousel ads showcasing products users had viewed or added to their cart.
At this stage, Lookalike Audiences were refined based on purchase data:
Lookalike (1%) of users who made purchases.
Lookalike (2%) of users who initiated checkout.
Results:
By methodically targeting each stage of the funnel, Adsmagnify achieved remarkable results for the clothing brand:
Revenue Growth: Monthly revenue skyrocketed to ₹13,72,369 within the campaign period.
Average Purchase Value: The average price per purchase increased to ₹563.
High Engagement: 12,807 products were added to cart, reflecting strong user interest.
Checkout Success: ₹10,566 in product checkouts, showing the effectiveness of the retargeting strategy.
Conversion Rate: 2,394 unique purchases were made during the campaign.
Conclusion:
The detailed and structured approach of Adsmagnify’s AI-powered marketing, which combined precise audience segmentation with a well-optimized marketing funnel, enabled the clothing brand to scale rapidly. By targeting the right audiences at the TOFU, MOFU, and BOFU stages, Adsmagnify maximized customer engagement and conversions while optimizing ROAS.
This case highlights the importance of audience testing and funnel optimization for e-commerce brands looking to drive growth and revenue. With continuous testing, retargeting, and personalized ads, Adsmagnify ensured that every rupee spent delivered a high return, showcasing the power of AI-driven digital marketing.
Other Projects
Other Case Studies
Check our other project case studies with detailed explanations
Other Projects
Other Case Studies
Check our other project case studies with detailed explanations
Other Projects
Other Case Studies
Check our other project case studies with detailed explanations