Abbott created a data-collection program that gave retailers in Vietnam the power of first-party data analysis normally the province of large and sophisticated organizations.
Objective
In Vietnam, traditional trade is the primary commercial channel, which still embraces an obsolete and non-digitalized way of conducting business. This dynamic has led to continuous decline of traditional trade over the past years, especially after the pandemic, when digital adoption in Vietnam took a giant leap forward and the country saw the emergence of modern channels like e-commerce.
Abbott's business in Vietnam, however, significantly relies on traditional trade. Hence the key objective for this project was to holistically transform the traditional trade landscape in Vietnam, leveraging the power of data and digital technologies to help traditional trade compete with other emerging channels. With that objective, Abbott sought to enhance traditional trade retailers':
Context
This effort by Abbott was the first time such a disruptive initiative had been implemented in traditional trade in Vietnam. Historically, traditional trade there does not capitalize on first-party data. Hence, its activities can only target mass shoppers with no room for personalization.
Target Audience
Abbott's target audience was traditional trade shoppers who were primarily women, 30 years old and above. These shoppers were primary caregivers and decision-makers in their families, taking care of their children and their parents at the same time.
Creative and Media Strategy
Abbott started by overcoming the biggest hurdle of traditional trade in Vietnam: the lack of data. Historically, no personal data or transactional data were recorded in Vietnam's traditional trade. So, Abbott implemented a mass-scale data collection via unique QR codes on Abbott products. This data was then fed to Abbott's data warehouse where a personalized retention journey was crafted for each user based on his or her unique purchase behavior. Marketing materials were then automatically generated based on predefined templates as well as key objectives that Abbott wanted to pursue. To keep the humanized essence of traditional trade in each message, all of Abbott's messaging was crafted as daily human conversations and sent to users through promoters at each store where the user had been recruited.
Abbott began by accelerating the collection of first-party data in traditional trade. By incentivizing shoppers to scan unique QR codes on Abbott products, Abbott was able to collect not only personal data but also rich transactional data, as well as behavioral data. Over a short period of just one year, Abbott recorded over 300,000 new member signups and 1.5 million scans.
These data-points were subsequently fed into Abbott's data warehouse where users were segmented according to Abbott's key objectives, i.e., upselling, cross-selling, or recruiting lapsed users. From there, Abbott crafted a personalized retention journey for each shopper based on his or her unique purchase behavior.
Following this approach, over 800,000 personalized marketing creatives were automatically generated, with different content angles, targeting different phases of the customer journey, presenting personalized nutritional information, personalized loyalty content, and also personalized promotional offers.
These personalized marketing creatives were personally sent to each consumer by promoters at each traditional trade store through the most popular mobile social media messaging app in Vietnam, Zalo, thereby preserving a human touch.
The project required an investment of just under $100,000 to generate significant incremental sales.
Technology played a pivotal role in this project to transform traditional trade. Three distinct systems were integrated in this project, intricately linked through API to collect, map, and segment data collected from traditional trade stores and then automatically generate a personalized journey with corresponding marketing materials ready for Abbott's promoters at each store to send to consumers.
Abbott's own data hub served as a data repository to host all the data collected, then validated and segmented it, then mapped it to Abbott's corresponding promoter at the store where data was first collected.
A journey-builder system was employed to construct a personalized retention journey for each consumer based on specifically defined objectives. This approach enabled Abbott to automatically craft hundreds of thousands of personalized marketing creatives fitting with the key objectives.
Last but not least, Zalo was used as the front-end platform for consumer communication. An exclusive Zalo mini app designed specifically for Abbott within the Zalo ecosystem empowered automated one-on-one conversations between Abbott's promoter and each consumer. Beyond that, the Zalo mini app allowed Abbott's promoters as well as retailers to effectively manage their shopper base via Abbott's advanced taxonomy system.
Within just twelve months of launch, Abbott's initiative achieved significant milestones. The company attracted 300,000 new member sign-ups and over 1.5 million scans, each contributing to the enrichment of Abbott's dataset.
Abbott's efforts have also yielded substantial business results, specifically a 48 percent increase in the number of repeat shoppers coming back to its traditional trade retail outlets. Abbott also saw a 50 percent uplift in average basket size, reflecting the positive impact of Abbott's strategies on consumer spending patterns. In aggregate, these improvements have culminated in an impressive 47 percent boost in lifetime value, underscoring the enduring value of Abbott's customer-centric approach.
Additionally, Abbott observed a high consumer satisfaction rating of 4.8 out of 5, reflecting the effectiveness of the effort's personalized and humanized approach.
