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Reserva, Brazil’s leading fashion brand sees 7X marketing ROI with Gupshup Conversation Cloud

A pioneer in conversational marketing, the lifestyle brand grows conversions and cross-sell opportunities and boosts customer engagement 4X.

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7X

ROI from product sales

4X

Engagement lift

81.8%

Higher open rates

"Investing in conversational marketing that gives us incremental revenues was one of our best decisions. With Gupshup Conversation Cloud, we're up and running quickly and with the help of the amazing customer success team, we've seen 7X ROI via online sales attributed to targeted WhatsApp marketing."
Vanessa Velloso
CRM - Reserva

About the brand

One of the largest fashion retailers in Brazil, Reserva started as a men’s lifestyle brand in 2004 and has 200 stores and 100 franchises, subsequently launching other brands targeting the women’s segment. Known as a company with a strong personality, Reserva deeply cares about its customers and provides seamless online and offline engagement.

Objectives

Reserva’s marketing leadership was looking for new ways to engage its customers and grow revenues through cross-selling, contextual nudges, and segment-based promotions. Seeing the success of rich business messaging, the brand also started the use of click-to-chat ads to acquire new shoppers and re-engage existing customers in their CRM via targeted WhatsApp marketing messages. Additionally, transactional/ utility messages came in handy to keep customers informed about their order status and deliveries.

The Solution

Targeted Marketing Messages on WhatsApp

Reserva uses WhatsApp to meet its marketing objectives in multiple ways – from nudging to re-engaging its customer base. The brand defines cohorts based on dimensions such as gender and preferred category, with campaigns ranging from promotional sales or offers to abandoned cart alerts, and nudges to drive conversions. These campaigns see an average CTR of 40% – a massive jump from the 2.2% and 10% CTR from email and SMS respectively. WhatsApp campaigns also enjoy an open rate of 60%, compared to only 33% for email campaigns, a lift of 81%.

Overall, the retailer saw 7X ROI through online sales as a result of targeted WhatsApp marketing. Gupshup has also equipped over 1/4th of Reserva’s in-store staff to directly send cohort-based marketing messages to customers on WhatsApp. These could be for discounts and promotions specific to their store or area code.

“These campaigns see an average CTR of 40% – a massive jump from the 2.2% and 10% CTR from email and SMS respectively. WhatsApp campaigns also enjoy an open rate of 60%, compared to only 33% for email campaigns, a lift of 81%.”

Improved New Customer Acquisition with Conversational Advertising

In addition, Reserva is making the most of Click-to-WhatsApp ads to increase qualified leads and has generated over 2K leads, 122 of which are qualified within one month of launch. With their catalog on WhatsApp, customers can easily browse products, add or edit their cart, and checkout by completing their payment on the website, allowing for a seamless consideration-to-purchase journey.

Solution

Conversational Marketing

Channel

WhatsApp

Industry

Retail and eCommerce

Simplifying Order Updates with Utility Messages

WhatsApp’s unique position as a frequently used channel makes it a great fit for brands to send post-purchase utility/ transactional messages. Reserva uses WhatsApp for order confirmation, shipping, and delivery messages.

Utility messages on WhatsApp are commonly used to enhance customer experience given the channel’s richness, and its ability to address customer queries in a self-serve manner. Best of all, utility messages provide one single convenient thread for all order updates from Reserva. The brand uses WhatsApp for 95% of its online order-related messages.

Gen AI as a Personal Sales Assistant

Reserva partnered with Gupshup to launch a Generative AI-powered virtual sales assistant on the occasion of Mother’s Day 2024 to create a personalized assisted selling experience. Compared to standard recommendation engines, the virtual assistant probes the shopper to understand their needs better, just like an expert salesperson would.

Based on specific inputs, it then recommends products, maintains the context, and navigates the conversation to drive upsell or recommend complementary products. For instance, if a user has expressed interest in a black blouse to begin with, the AI bot can ask the customer about the specifics like occasion, fabric, style, look and feel, etc.

It then also uses this information to recommend related products the customer may like such as skirts, bags, or accessories to complete the look. All this while holding the context of the initial customer requirement, which was to purchase a black blouse.

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