Multimarket Search campaigns are the bread and butter of any global agency, but they bring with them some additional challenges compared to their single market cousins. Key considerations include the additional lead time and the administrative challenge of translating (or more importantly trans creating) content into local language. This process generates significant additional cost, allowing only limited refreshes and damaging RoI. Literal translations are frequently inappropriate and local cultural context is key (the Vauxhall ‘Nova’ lives on in infamy. Nova conveying bright light and space age technology in English does not have the same ring in Spanish.)
Local translators, who are (vital for transcreation,) may not have the best grasp of the nuances of Paid Search. How different elements are deployed and even the character limits. Each round of changes adds to the administrative burden and likelihood for errors, so maintaining a high level of consistency across multiple markets can be a tricky task at best.
Enter the AI
Large language models (LLM) offer a revolutionary leap forward in this area. Now it is possible to translate quickly, easily, cheaply and crucially accurately across a number of languages simultaneously at the touch of a button. At Merkle, we have created a proprietary AI-based tool called d.Scriptor, that can review the content of a landing page, be given the context of any particular translation, be it a headline, site link or description, fit a brand’s tone of voice and asked to remain under character limit(s) whilst providing the equivalent in local language nearly instantly.
A centralised PPC team need only provide a base version of all text assets whilst the LLM will fill in the ‘blanks’ in a wide variety of languages with series of calls to the LLM API. Although this could of course be achieved with a manual translation. The speed and efficiency of this is leagues ahead. The output of the system can then be in a convenient format firstly for review and correction by a native speaker and then for upload directly into the platform by your PPC team. This AI-based approach will help cut down on administrative back and forth and hence provide a big efficiency for teams and translation costs over time. We would however always recommend that a native speaker reviews all outputs prior to use, as although LLMs have been improving fast there is no substitute for a human in the loop.
As the landscape of copy and creative in search continues to evolve, the rise of conversational search and Performance Max means that we will require more frequent updates and changes to effectively optimize campaigns. This is crucial because agencies and advertisers have direct control over this lever of optimisation. As we move forwards the platforms will be increasingly pushing automated creation of assets, again necessitating faster turnarounds on localisation than is achievable via traditional methods.
What does this mean for how we should structure teams going forwards?
Increasingly this means that an experienced, centralised team supported by powerful AI tools and enterprise level management solutions is going to be best placed to support international brands efficiently and effectively. Maximising economies of scale and minimising the additional administrative costs of localised support from individual markets and siloed teams.
Centralisation is equally important between Paid and Organic search. Breaking down the silos between these teams will become increasingly important as the lines between the two approaches blur. Thanks to conversational search (the growth of searches with multiple interactions and inputs on the SERP) and the exponential growth of key-wordless campaigns outside of ecommerce (i.e. performance max), resulting in even more unique searches and a richer picture of the user. Logically we should view Search Engine Marketing (SEM) holistically, with SEO practitioners also in a key position to benefit from the increased speed and accuracy of translations via a LLM. At Merkel we have developed our Total Search team and proposition with this in mind.
4. Extend customer journeys into value-based experiences
A purchase should be viewed as an inflection point in a prolonged relationship with the customer, rather than the end goal. Depending on a brand’s business model – B2C or B2B or B2B2C – and value proposition, the relationship between the organization and the customer may encompass other constituents (e.g., purchasing, legal, approvers, etc.), third-party organizations (e.g., a parts supplier), a restricted VIP experience (e.g., a loyalty program with its own point-based currency), or a special retail event (e.g., a pop-up store campaign run with a dedicated POS platform). Personalization at scale entails extending the commerce experience to encompass portals, marketplaces, and loyalty programs, creating cross-pollination between these environments and the purchasing funnel. This ensures that as many of the customers’ needs – no matter how specific they are – as possible are met through experiences owned and operated by the organization.
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