Goal:

To identify scalable customer acquisition and revenue-growth levers for HouseEazy’s full-stack PropTech model in the secondary real estate market, with a focus on ₹80L+ 2 & 3 BHK buyers while improving customer acquisition costs and increasing overall transaction value.

Tools & Technologies Used: Customer acquisition and referral strategy, Real estate unit economics analysis, CAC and commission analysis, Customer segmentation, Upselling and cross-selling strategy, AOV and margin analysis

What I Did:

Analyzed the acquisition challenge faced by full-stack PropTech platforms that buy, refurbish, and sell pre-owned homes, particularly the pressure that 1–2% channel-partner commissions create on unit economics when scaling across thousands of partners.

Identified ₹80L+ 2 & 3 BHK buyers as a key segment for developing alternative acquisition and revenue-growth levers.

Proposed a “Past Buyer” referral channel by turning existing homeowners into an acquisition engine, leveraging the natural word-of-mouth and social networks associated with home purchases as a major life and prestige event.

At a midpoint AOV of ₹85L, calculated that a standard 1–2% broker commission represents approximately ₹85,000–₹1.7L per transaction.

Proposed offering existing customers a ₹25K–₹50K referral incentive, equivalent to approximately 0.3%–0.6% of the ₹85L AOV, to create a lower-cost acquisition channel.

Identified the potential to significantly reduce acquisition costs compared with relying entirely on broker commissions, particularly across a network of 4,000+ channel partners where acquisition expenses can scale substantially.

Proposed an Upsell + AOV expansion strategy by bundling interior/furnishing services with the property transaction.

Identified that customers purchasing ₹80–90L+ 2 & 3 BHK homes are likely to have additional furnishing requirements, creating an opportunity to capture an additional ₹5–8L of customer spending.

Leveraged HouseEazy’s full-stack model—owning the property and refurbishment value chain—to propose an integrated interior package that pure-play interior competitors may not be able to offer with the same transaction context.

Proposed offering a 3–5% discount on a ₹5L–₹8L furnishing package, representing approximately ₹15K–₹40K in customer savings.

The discount represents only approximately 0.2%–0.4% of the core ₹85L property transaction, creating potential room to absorb the discount within the broader refurbishment economics.

Designed the offering as a seamless single-window property + furnishing checkout experience, reducing the need for customers to separately search for and coordinate with interior providers.

Challenges and Learning:

Challenge: Reducing dependence on expensive broker-led acquisition while simultaneously increasing transaction value without negatively impacting overall unit economics.

Learning: Developed a deeper understanding of PropTech acquisition economics, referral-led growth, CAC optimization, AOV expansion, cross-selling, margin structures, and how owning multiple parts of the value chain can create additional growth levers.

Result:

Created a customer-led acquisition framework that uses past buyers as a potential scalable referral channel, with referral incentives substantially below traditional broker commission rates.

Developed a potential acquisition model where a ₹25K–₹50K referral incentive could replace a ₹85K–₹1.7L broker commission on an ₹85L transaction, subject to actual referral conversion and attribution.

Created an AOV expansion strategy by combining property transactions with ₹5–8L furnishing packages.

Established a potential discount framework of ₹15K–₹40K on furnishing packages while keeping the discount relatively small compared with the underlying ₹85L property transaction.

Designed a single-window property + furnishing experience aimed at increasing customer convenience, transaction value, and overall platform monetization.

Website: houseeazy (dot) com