Head of Product Marketing at Gan.ai, a visionary in digital marketing. From her beginnings at DDB with McDonald’s to navigating the transformative landscape of granular personalisation, Anna’s journey unfolds as a testament to the evolution of marketing strategies. Now at the forefront of hyper-personalisation with generative AI at Gan.ai, she shares her expertise on the future of marketing and applied sales. Join us as London Economic explores this industry leader’s dynamic career and perspectives.
How did you get to this point? What was your journey into this world?
Back when I started my marketing career in an ad agency DDB with McDonald’s as my first client, there were not as many ways to personalise the customer experience: marketing relied on user cohorts, promotional, seasonal events and brand partnerships with the focus on the location-based marketing of point of sales. Then in the 2010s, the development of AI and big data enabled marketers to get more granular with tailored content across channels: allowing me as a marketer to experiment with custom messaging, delivered via emails and dynamic ads as I promoted an augmented reality company WayRay and a mobile app Picsart.
Personalisation in email marketing, recommendations based on location data, browsing history, and purchase patterns have become the norm for marketers around the world. With the new wave of generative AI emerging in 2022, it was clear to me that the future of marketing is in hyper-personalising the customer experience, and I joined Gan.ai, a video personalisation company applying generative AI to the field of marketing and applied sales.
For our audience who may not be familiar, could you provide a brief definition of hyper-personalisation in the context of digital marketing and the landscape of the market?
It is a practice of tailoring every customer interaction with relevant text messaging, visual content, and offers based on their individual preferences, context and real-time intent via leveraging data, AI, and integrated platforms. The ultimate goal is to emulate a human salesperson or customer success associate who deeply understands each client, which results in user delight and higher sales conversion and retention. Great examples of personalisation in digital marketing include Spotify’s End-of-year Wrapped Report with personalised listening history or Amazon’s buying recommendation algorithm based on search and purchase history. The biggest advantage of the generative AI revolution for marketers is the availability of hyper-personalisation and content creation even to smaller companies.
In digital marketing it will experience rapid growth, expecting to reach $19.8B by 2025 (MarketsandMarkets), as over 80% of customers prefer to buy from companies offering a personalised experience (Epsilon). With the advances of platforms like YouTube and TikTok, video is becoming a key media, making up over 90% of the internet traffic (Cisco). Retail, media, and e-commerce are leading the adoption, with software, healthcare, and real estate to adopt next. Driving factors in this are consumer demand for relevant experiences, shifting privacy attitudes, and maturing approaches in data analytics.
In your experience, how have you seen hyper-personalisation impact different industries, and are there specific sectors where it has been particularly transformative?
One of the biggest challenges in brand marketing is scaling influencer campaigns for consumer brands and entertainment, as they are pricey and time-restrictive. AI personalisation solves this by turning influencers into true brand ambassadors: imagine your favourite celebrity addressing you by name and sending you a tailored offer. For example, in our campaign to launch Samsung’s newest Z4 Fold smartphone, its brand ambassador Alia Bhatt tells the viewer of the ad the name of a nearest mobile store, based on the location sharing, which resulted in higher smartphone sales in the advertised region.
It is not only for celebrities and influencers, it works in more traditional industries, such as real estate and healthcare, tackling the brand battle of trust building and conversion funnel. An eye clinic in the US had a quite high no-show rate of 20%. We developed a personalised campaign with reminders to patients, in which the doctor addresses the patient by name and reminds them about the visit. This reduced no-shows from 20% to almost zero, as efforts like this help build trust between the service and the patient, even before the treatment journey starts.
Another challenging industry is real estate: the home-buying process could be long and painful, especially given the current market conditions. For real estate clients and overall service business, it’s important to be the first one to connect with prospects, greet them and offer options: the one who makes the first move often wins the deal, so personalisation can improve lead engagement two or threefold for D2C e-commerce and service industries, such as beauty, financial and home services.
There’s a way to apply personalisation in almost any industry as long as it complies with necessary regulations, especially in higher-regulated B2B industries, such as financial, gaming, gambling, and more. Generative AI can help business owners scale their efforts, making them meet and greet every new customer who signs up on the website and humanise the business, making the business more customer-oriented and approachable.
While hyper-personalisation offers numerous advantages, are there challenges or common pitfalls that marketers should be mindful of when implementing such strategies?
One of the challenges is authenticity – making sure the voice and video look real and do not sound robotic. Try to build personalisation marketing with a real face and natural voice, such as the founder or spokesperson of the business, and not with AI avatars. Those look great and could help you save costs and time on content creation, but for marketing use human face, as we as people are more drawn to authenticity – content with real people as the way of building trust with consumers. While doing so, make sure you use good training data and algorithms, so both videos and voice sound and look natural and realistic.
While hyper-personalisation is relatively new, take advantage of it before it becomes ubiquitous: the earliest adopter will get the highest increase in metrics. Battle for customer’s attention is ongoing – make sure you win in it by implementing modern techniques. In addition, more regulators will come up with stricter guidelines on AI-generated content, requiring companies to mark all the content produced with AI as such, which could jeopardise the trust in brand building.
How does does it contribute to enhancing the overall customer experience, and what are the key elements that entrepreneurs should focus on to create a seamless and personalised journey for their customers?
It transforms the one-size-fits-all customer experience into feeling like a valued shopper or client. The result is greater perceived value, convenience, and emotional connection with the brand, which turns into higher conversion and retention. This could be done for different audiences, including potential clients, current customers, suppliers, employees, and more. For example, to celebrate the 10th anniversary of Uber on the market, we developed a personalised campaign, thanking each driver by name and the number of rides they gave during their work at Uber. This resulted in higher loyalty on the very important supplier side, which in turn resulted in a higher user delight for end customers.
Three key elements for entrepreneurs to focus on: first, relevance – tailor messaging and offers to individuals and user cohorts based on their interests, past purchases, and settings. Second, responsiveness – hyper-personalised recommendations that evolve based on real-time behaviour signals demonstrate genuine responsiveness to shifting customer needs and mindsets. For example, video stitching is a great technology to support this – based on the preferences, the users see a video tailored to their preferences, not the same one-fits-all content. Finally, the element of user delight – surprise customers by anticipating needs or progressing journeys based on their habits to improve brand affinity via positive emotions. My advice here is to use the major trait of humans currently not available to the most advanced AI – creativity and looking at the whole process, not just parts of it.
What do you see as the future trends in hyper-personalisation, and how should entrepreneurs prepare for the next wave of advancements?
As we live in an era where customers expect us to understand their wants and needs, a video spokesperson or virtual brand ambassador of the company appearing as content creator will be key for many brands – if you don’t have one, now may be a great time to start. This trend will result in further proliferation of content creators and digital avatars. Forward-looking entrepreneurs will explore video personalisation across owned channels while preparing their marketing tech stack and customer development platforms. Respecting viewer preferences via transparent opt-in policies will build trust.
Entrepreneurs should focus now on building a hyper-personalised marketing strategy, implementing their data, customer insights, and technology stack. Developing trust and transparency will be critical, and the most visionary companies will optimise around customer lifetime value using personalisation to drive loyalty and maximise revenue per user. Overall, generative AI unlocks content generation, video marketing, better search engines, and employee productivity, to produce the most value for users today.
For entrepreneurs looking to integrate hyper-personalisation into their marketing strategies, what advice would you offer? Where should they start, and what key considerations should they consider? What tools should they start using?
Start small, personalising one micro-segment of users or part of the user journey to measure the immediate impact in the engagement lift and revenue metrics. Refine the model, then scale. Then expand integrations gradually, as the customer insights solidify.
Identify use cases with the highest impact – where personalisation can move the engagement or revenue needle: for example, win-back campaigns for churn-prone segments, unique cross-sell offers, and tailored content for micro-verticals. Good starters are dynamic content, next-best recommendations, personalised search and routing, custom incentives and tailored lifecycle campaigns.
Audit journeys to locate touchpoints with the highest customisation upside. Then begin structuring an actionable customer data stack – profiles, dashboards, and customer journey analytics. Tools that can help you: customer development platforms like Salesforce CDP and mParticle, real-time testing Optimisely and Evergage, marketing clouds like Adobe and Salesforce, video personalisation platforms like Gan.ai and Rephrase. Test and iterate quickly: with a phased, data-centric approach balanced by respect for individuals, entrepreneurs can unleash personalisation as a growth accelerator and competitive differentiator.
Are there any metrics that are often overlooked but are crucial for evaluating the impact of hyper-personalisation? How can entrepreneurs effectively measure success?
The immediate impact of personalisation is visible on the engagement rate: users watch the videos longer, personalised web pages have a higher click-through rate, and other metrics depend on the industry. For example, in B2B sales, it could be the increase in conversion rate from meetings booked and deals closed. In D2C and e-commerce, there are fewer abandoned carts and more repeated purchases. For example, in a challenging campaign for Air India, we developed a special video invitation to the rebranding event from the CEO and doubled the CTR of the invitation, as consumers want to hear more personalised offers and are often willing to share their data to get the best offers.
As we wrap up, is there any final piece of advice or insight that you would like to share with our audience of entrepreneurs regarding hyper-personalisation?
View personalisation as an opportunity to demonstrate how you genuinely understand and serve each customer, not as a mechanism to drive sales through invasive targeting and automation. Build trust and transparent consent first. Lead with relevance and compassion, not just reach and frequency.
Personalisation allows visionary companies to transform addressable market metrics on slide decks into actual humans to serve. By combating hype with heart, entrepreneurs can form loyal bonds with the customers they profess to understand so intimately. Prioritise listening over assumptive shouting. This balanced mentality around personalisation will surely pay dividends in the coming era of AI augmentation.
