White Paper | Author: Khanh P. Dang, Google APAC, IAB SEA+India Commerce Council subgroup
Even as restrictions and offline stores open up, people are still spending time online and deepening their usage especially with respect to how they shop. Specific to APAC, it was shared in a recent study across 14 markets and over 15,000 participants that APAC shoppers are young (62% 18 – 44 age), wealthy (83% claiming to be mid to high income), and careful (70% ‘careful’ ie, thrift-seeking or deliberate vs 30% ‘fun’ ie, shopping for entertainment). In addition, a McKinsey study found APAC seniors (individuals of age 60+) would be spending $5 trillion by 2023, but had a tendency to shop offline due to more trust in brick and mortar shops.
Against this backdrop, it would make sense for retailers in APAC to lean on AI-powered solutions to address the diverse shopping habits of shoppers in the region and build brand trust in a more privacy conscious manner.
Shoppers have a myriad of customer journeys, whether on retailer apps, streaming on connected TVs, or embracing both online and offline experiences. This complexity poses a challenge for retailers to reach them. However, AI-powered solutions and machine learning tools can allow retailers to assess signals in real time overlayed against preferences and intent. This not only gives the capability of being at relevant moments and connecting to high valued customers, but also simplifies management and optimisation especially within omnichannel shopping solutions.
AI-powered solutions have allowed retailers to capture value across their advertising inventory. For example, a beauty brand gained tremendous success during large shopping moments (ie, 11/11 Singles Day), and they also did so in an ‘always-on’ fashion.
AI-Powered Solutions Are Misunderstood; They Are The Key Towards Meeting Business Objectives
Misconceptions, unfortunately, are commonplace with regards to AI-powered solutions such as: “it’s a black box”, “it’s volatile”, and might not bring maximum business impact and profitability. However in truth, they can unlock speed, scale and success.
When evaluating solutions, it’s important to lean into technology that provides clear controls on goals, messaging, bidding, and the ability to ensure that algorithms are working for specific marketing objectives. Machine learning should continuously evaluate and account for a plethora of variables, such as device type, time of day etc, but it’s important to maintain the ability to adjust targets and learn from bidding strategies.
Volatility may happen, especially at the time of launch, however what is often forgotten is that more data and learning equate to better performance. AI-powered solutions can also evolve with exciting new shopping behaviours and formats recently announced by Google to fully capture intent. In contrast, manual bidding cannot take into consideration the innumerable signals unique to each user and optimise at scale.
AI-powered solutions also allow for maximum business impact and profitability. One should leverage the machine to capitalise on real time auctions across inventories for growth but also optimise beyond intermediary metrics (ie, CPCs or CPAs) and allow for driving real business outcomes such as revenue, profit, or even customer lifetime value.
Retailers leveraging value based bidding, moving from target CPA to a target return on ad spend, achieve 14% higher conversion value, with a similar return on ad spend. Business sustainability and profitability can be achieved by driving towards real business objectives.
AI-Powered Solutions Offer Relief and Unlocks Greater Strategic Value
78% of marketers say they feel relieved that giving a larger role to digital tools, frees up time to uncover insights, untapped audiences, improving website and app experiences, and consulting on digital transformation.
More sophisticated retailers and their marketing partners can spend time testing, learning, iterating their strategies and building expertise in using data. As mentioned by Bruce Williams, Head of Performance, Dentsu Media, “ We’ve had to remodel our mindset and our client’s mindset, because AI-powered solutions are often thought of as a replacement for something. It’s not. They actually enhance the work of our teams who operate holistically and navigate across channels.”
AI-powered solutions are not a replacement for individuals or entire tasks, but allow retailers to supercharge and enhance their capabilities.
Developing Engaging First Party Surfaces Builds Trust and Future Proofs Business
AI-powered soutions allow time for retailers to build great immersive and visual experiences on their own surfaces to show authenticity, differentiation, and engagement. Developing a solid customer relationship yields trust, a prerequisite to consented, rich, first-party data.
One example leverages Immersive Stream for XR in Southeast Asia, where Robert Pike, Marketing Communication Director, Ford International Markets Group mentioned, “Ford has developed and deployed highly engaging and personalised on-site experiences such as an immersive AR showroom that nurtures prospective buyers on their vehicle shopping journeys — creating a compelling value exchange for consented first-party data that helps us build even stronger and more durable customer relationships.”
The virtuous cycle of leaning into AI-powered solutions and building trust through more personalised experiences, measured both online and offline, can help retailers capture the full APAC opportunity. It also helps their business strengthen, scale, and grow for an uncertain future in a privacy-centric world.