Background and challenge
A multinational technology leader from Taiwan has launched many flagship products in computing and communications and, to give consumers a better experience, keeps developing product lines for different uses and audiences. With high prices, long consideration cycles and intense competition, the marketing challenge was to find the right mix for every campaign, lift overall sales and reach many potential customers to grow brand penetration.
A solid advertising foundation: three principles
Under the privacy policies of major ad platforms, audience categories are less distinct than before, marketing mixes tire quickly, and with so many sources of information, shopping journeys and roles have become blurred. Advertising strategy cannot look only at the moment of delivery; it has to plan audiences and creative for the long term. Combining these ideas with past results and AI-powered campaigns, CloudAD summarised three principles.
Principle 1: put members to work with owned audience data
With privacy rules and browser changes, the data platforms can capture is limited, and keeping data measurable and usable has become a central concern. CloudAD recommends using owned lists and website behaviour as a compass to find likely orders.
- Owned lists: import first-party lists into ad tools so the brand’s large member base strengthens learning signals.
- Website behaviour: the brand has a complete GA4 setup, so user interactions are captured fully. CloudAD packaged this data securely by behaviour, such as page views, purchases and carts, to guide learning at each stage of the funnel.
Principle 2: segmented messaging tailored to each use case
Many advertisers worry that promoting discounts will cheapen the brand, or that campaigns will need to switch between waves. CloudAD split creative by two goals, brand image and promotions, making results easier to judge and ads more relevant.
- Brand image: promoting the brand’s signature warranty service builds image when people need a related product and supports the long learning period ad systems need, lowering costs and turning brand audiences into a starting point for conversion.
- Promotions: the brand segments products by use, such as business, gaming and creators, so CloudAD recommended blending product and context in promotional creative, making ads personal as well as price-led and raising click intent.
Principle 3: smart learning with AI-powered ads
With complete first-party audiences and tailored creative behind them, ads can reach users at every stage of the journey. Many advertisers invest in Google’s Performance Max. As shoppers compare prices and reviews across more platforms, CloudAD also recommended Meta’s Advantage+ Shopping Campaigns (ASC), using Meta’s machine learning to extend reach and increase contact between products and customers.
- Google Performance Max: uses machine learning to follow customers across Google placements (YouTube, Gmail, search results and the Display Network) for maximum exposure. Campaigns can take in signals, such as first-party member data or YouTube channel audiences, so every advertising dollar builds on the last.
- Meta Advantage+ Shopping Campaigns: unlike traditional dynamic product ads with manually set audiences, ASC also runs in collection formats but uses automation to show products people are interested in, together with images and campaign information. Above all, AI learning helped the brand reach more potential customers and improve traffic quality and sales.
Results
- Conversions +200%
- Session engagement time +35%
If your marketing strategy or digital advertising has hit a wall, get in touch and let CloudAD help you find the next step.
