Skincare brand Sebamed, marketed in India by USV Pvt Ltd, has become one of the first Indian advertisers to test advertising inside ChatGPT, working with WPP Media on the activation.
The idea is simple but significant: instead of buying conventional digital placements around consumers, Sebamed wants to show up inside the conversations where people are already asking about oily skin, cleansing routines, dryness and general skin health.
What the activation involves
The campaign centres on the Sebamed Gentle Facial Cleanser for oily and combination skin, and leans on the brand’s long-standing pH 5.5 platform — cleansing without stripping the skin’s protective barrier.
Rather than a broadcast message, the activation is built to surface when a user is in active consideration mode: asking a question, weighing options, looking for a recommendation. WPP Media describes this as a context-led approach, where brands appear within topics people are actively researching, creating a route from discovery to consideration to action.
Pranay Rao, Vice President – Marketing, USV Pvt Ltd, said the brand sees ChatGPT as an opportunity to bring its skin-friendly cleansing message “into relevant conversations” as consumers increasingly turn to AI-led platforms for answers.
Vishal Shah, Senior Vice President, Client Solutions, India, WPP Media, framed the shift more broadly, noting that AI is reshaping how consumers discover information, evaluate options and make decisions — and that the agency’s job is to turn that shift into practical media opportunities.
Why this matters
For years, the search-to-purchase journey in categories like skincare has run through a familiar loop: a Google query, a few blog results, some YouTube reviews, then a marketplace. Conversational AI compresses that loop. The assistant summarises, compares and recommends — often without the user clicking through to any brand-owned property.
That creates two problems for marketers. First, a visibility problem: if the answer engine doesn’t know your product, you don’t exist in the consideration set. Second, a measurement problem: traffic and attribution models built for click-based media don’t map neatly onto conversational surfaces.
Early experiments like Sebamed’s matter less for immediate ROI and more for the learning curve. Brands that start understanding query patterns, prompt intent and creative formats in AI environments now will have a head start when these inventories scale.
A simple way to think about AI-era discovery
For teams trying to build a plan, it helps to separate three distinct layers:
- Paid presence: emerging ad formats inside assistants like ChatGPT — the layer Sebamed is testing here.
- Earned presence: whether AI models cite your brand organically, which depends on structured product information, reviews, expert content and third-party mentions.
- Owned readiness: whether your site, product pages and FAQs are machine-readable enough for an assistant to extract accurate claims — pH levels, ingredients, skin types.
Most brands over-index on the first and neglect the other two. An ad can win a moment; a well-structured information footprint wins the default answer.
What marketers should do next
Start by auditing how AI assistants currently describe your category and your brand. Run the questions your customers actually ask — “best face wash for oily skin”, “is pH 5.5 better for skin” — and note which brands get named and why. That gap analysis is cheap and immediately actionable.
Then set expectations internally. Conversational ad inventory is new, reach is limited, and benchmarks barely exist. Treat it as a test-and-learn line item, agree on what a successful learning looks like before launch, and resist judging it purely on last-click performance.
Finally, watch the agency side. WPP Media positioning itself as a translator of emerging AI behaviour into media plans signals where holding companies see their next value pool — not just buying inventory, but helping brands become discoverable inside machines that answer questions.
Source: MediaNews4U
