Shoppers on the client’s e-commerce site regularly dropped out of the buying process despite intending to purchase not because they’d changed their mind, but because they couldn’t get answers to specific questions about product features, shipping times, or return policies. The site couldn’t replicate what a real store associate would answer on the spot.
Post purchase support had the same gap proactive information could only go so far before a customer’s specific question needed a specific answer.
∙ Revenue lost to customers abandoning purchases over unanswered questions
∙ No true 24/7 support to catch queries whenever they came up
∙ Low cross sell revenue, with no channel to guide customers toward relevant add Ons
∙ Inconsistent customer service depending on when and how a customer reached out
∙ High volume of repetitive queries, difficult to handle at scale
Aiwozo built a virtual assistant to support customers at both ends of the journey while they were deciding to buy, and after they’d placed an order.
Conversation agents, using NLP and sentiment analysis, understood and responded to customer queries in natural language, whether about product details, shipping, or returns.
Action agents, went beyond answering questions to actually execute tasks customers requested turning the assistant into something that could act, not just respond.
Support agents took on responsibilities that would otherwise fall to operations and marketing teams, handling routine post-order queries and freeing human teams for higher-value work.
Key business and operational challenges that limited performance, scalability, and governance before automation was introduced.
