Two-Wheeler Brand Ofero:
AI Shopping Assistant Cuts In-Store Deal Costs by About 80%
Contact UsCase Overview
Ofero, an electric two-wheeler brand, serves Southeast Asia and Latin America. Singoo rebuilt its path from “social media leads, manual dispatch, in-store conversion” into “social media leads, an AI shopping assistant inviting buyers to stores 24/7, in-store staff closing the sale”. In the first phase, piloted in offline stores in Southeast Asia, the cost of converting opportunities into deals fell by about 80%.
- Customer
- A new-energy electric two-wheeler brand
- Industry
- Two-Wheelers / Electric Two-Wheelers
- Products
- Electric two-wheelers, electric motorcycles
- Target Markets
- Multiple countries in Southeast Asia, Latin America and beyond
- Client Type
- Brand
- Project Duration
- Phase one piloted in offline stores in Southeast Asia
Client Background
The company focuses on the R&D, manufacturing and global expansion of new-energy electric two- and three-wheelers, mainly targeting emerging markets such as Southeast Asia and Latin America, with an emphasis on local adaptation and smart mobility. Its original online marketing path was “social media leads → manual follow-up → manual assignment of qualified leads to stores → in-store conversion”.
Client Challenges
- Challenge 1
Consumer leads arrive around the clock, but manual responses are slow and many leads are lost; large volumes of leads need long-term nurturing that people cannot cover efficiently
- Challenge 2
Leads are dispatched to stores by hand, follow-up is hard to control and conversion losses are high
- Challenge 3
High marketing costs: the cost of turning opportunities into store visits is high and ROI needs to improve
Solutions
- Stage 1
Offline In-Store Conversion
The conversion path is upgraded to “social media leads → AI shopping assistant inviting buyers to stores 24/7 → in-store staff converting”, with a private customer database built in parallel so the AI assistant can nurture leads long term and invite them again and again
- Stage 2
Standardised Direct Stores + AI Upgrade
Prove out “paid online traffic + AI store-visit invitations + offline in-store conversion” and produce a replicable online-AI-plus-offline-store SOP that closes the loop from traffic to touchpoint to deal; upgrade AI capabilities: customer profiles feed back into ad targeting, smart funnel diagnostics pinpoint bottlenecks, and deep private-traffic segmentation enables differentiated marketing
- Stage 3
Replication
Build an AI marketing system and add AI agents for after-sales, marketing content and stores
Implementation
- Stage 1Offline store pilot in Southeast Asia, with the AI shopping assistant handling store-visit invitations
- Stage 2Standardised model proven in direct stores; AI upgraded with profile feedback and funnel diagnostics
- Stage 3Replicate across Southeast Asia and other markets; add after-sales, content and store agents
Business Results
Deal Cost
~80%Reduction
Cost of converting opportunities into deals cut by about 80%
Store Visitors
100+/ month
Online marketing brings 100+ customers to stores every month
Phase Two Target
Halved
Deal cost to be halved again from the phase one level
Data notes: the deal cost reduction is based on the client’s own statistics from the store pilot phase; phase two figures are targets.
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