Achievements
1000 + Fashion & Furniture Retail Accounts
Multi-stage, signal-driven ABM motion
5-6% CTR
60% pipeline through ABM
Plot Twist in 3 Moves
Rashmica switched to Recotap’s signal-driven ABM strategy: ICP defined wrt regions, sectors & Seniorities, Personalized Multi-Stage ABM Campaign
ABM grew to 60% of Vue.ai’s pipeline, boosted CTR to 6%, and helped close a $1M deal—powered by a one-person team using Recotap
Vue.ai, from Mad Street Den, powers AI-led retail automation for fashion and furniture brands offering tools like smart tagging, visual search, and 1:1 personalization.
Top of funnel prospects in both fashion and furniture retail weren’t moving across to the sales‑ready leads segment.
Thinning awareness pipeline on the top end and leaking ARR on the back end led to doubling of revenue shrink.
Rashmica knew that to reverse this, the team needed to go beyond broad outreach and adopt a buyer-centric, intent-driven methodology customized for each stage of the funnel.
To execute this vision, Rashmica’s team turned to Recotap’s Account-Based Marketing (ABM) platform.
ICP-Based Segmentation
The first step was to define Ideal Customer Profiles (ICPs) for each region and sector. This allowed Rashmica’s team to create audience segments tailored to local buying behaviors and industry priorities.
Accounts
Targeted Personas
Stage 1: Awareness Campaigns (1:Many)
Rashmica launched multi-stage awareness campaigns with clear, ICP-specific messaging. Each region ran 2–3 month campaigns featuring informative, solution-driven ad creatives across LinkedIn & programmatic channels. The goal was to introduce Vue.ai’s capabilities while building top-of-mind awareness.
Few campaigns also included a set of existing accounts to showcase what’s new & improved with the features and what can be a game changer. The creatives were designed accordingly to choose Vue.ai as a product again.
Stage 2: Engagement Campaigns (1:Few)
As engagement metrics rolled in, she and her team dynamically refreshed segments identifying high-intent accounts and moving them into the next wave of campaigns. These 1:Few campaigns lasted 1–2 months and focused on deeper messaging including product capabilities, use cases, and social proof.
Stage 3: Consideration Campaigns (1:1)
Accounts showing strong buying signals were then targeted with 1:1 personalized ads crafted at scale using Recotap. This final 4–5 week phase was all about relevance and conversion, with messaging tailored to the specific pain points and context of each account.
Thanks to a structured, multi-stage ABM approach and Recotap’s automation, Vue.ai:
“We asked closed accounts how they heard of us—most had seen us digitally. That’s when we knew ABM was working.”
Rashmica Rajendhran’s leadership in digital marketing and demand generation proved pivotal in turning Vue.ai’s TOFU challenges into a high-yield pipeline engine. This case underscores the power of targeted ABM, data-driven segmentation, and personalized messaging in modern B2B marketing.
Rashmica Rajendhran, Associate Director – Digital Marketing & GTM Strategy at Mad Street Den, led global demand gen for Vue.ai. She brings sharp campaign instincts and a flair for strategic pipeline acceleration.
Identify and prioritize high-intent accounts using integrated signals
Auto-segment accounts based on intent and behavior
Run targeted, full-funnel LinkedIn campaigns
Serve 1:1 personalized LinkedIn ads at scale
Deliver dynamic landing pages no code needed
Track engagement and campaign performance instantly
In Case-study
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