Using AI to Master the Branding Trio – Differentiation, Targeting & Loyalty

In this feature, Lavin Vaswani of Quantcast takes a look at how AI can help brands master their targeting, and stretch limited budgets.

Artificial Intelligence (AI) is one of 2024’s most talked about digital developments. Gartner placed generative AI on the Peak of Inflated Expectations on its 2023 Hype Cycle for emerging technologies. But just like the metaverse, NFTs, crypto, and other developments popularised in recent years, we are still some ways away from realising its full potential. 

That said, AI, in general, is poised to reach a transformational stage within two to five years, giving marketers a relatively short runway to incorporate the technology into their workflows and overall strategy.

Both traditional predictive AI models and generative models are quickly being fine-tuned to handle a variety of use cases. New applications adapting pre-trained models for productivity and content generation are becoming popular. These include applications such as chatbots, call center automation, AI assistants, and more. Such use cases help marketers stretch their limited budgets.

Defining priorities to deliver meaningful AI projects

Despite the technological shifts impacting how consumers behave, their needs, and content consumption habits, the core priorities for marketers remain the same: create differentiation, consistently and efficiently target the right customers along the purchase funnel, while cultivating brand loyalty. 

And while the ‘why’ and ‘what’ of modern marketing have become more complex, the ‘how’ hasn’t changed that much. Differentiation, targeting, and loyalty remain the building blocks of a solid brand strategy. However, marketers can reduce some of that complexity by using AI to focus on the measurable improvements that the technology can bring to these three core areas.

It’s no secret that most digitally-led organisations are racing to adopt AI in one way or another. However, deployments with clearly defined priorities, operational objectives, and measures of success will have a better chance of being viewed as an investment rather than just a cost to the bottom line. So how can your organisation create value with AI rather than just jump on a bandwagon?

Stacking the blocks with AI

AI can add value in different ways in all three core branding areas. 

• Differentiation is all about creating a distinctive and creative positioning and offer. The value of AI here lies in not just being able to analyze vast amounts of data and determine market gaps, but also in brainstorming and testing new differentiation strategies. Marketers can use AI and machine learning to predictively analyse consumer behavior and market trends to understand and anticipate demand.
• Targeting digital consumers is set to become even more challenging when third-party cookies eventually go away. Here AI plays a key role in helping marketers leverage first-party data to create more impactful campaigns. By optimising for thousands of variables in real-time, AI can help marketers improve conversions and achieve lower cost-per-acquisition. Machine learning and predictive analytics can also help brands achieve better customer segmentation through behavior analysis, contextual targeting, and look-alike audiences.
• Finally, AI also has a role to play in cultivating brand loyalty by helping marketers create immersive experiences that keep consumers engaged and coming back for more. Marketers can also use AI to understand brand perception and sentiment in real-time, which enables them to come up with strategies to personalise content and messaging for various touchpoints, driving more impact with tactics such as emails and digital ads.

Start small, but certainly start now

Brands need to define their objectives and AI goals clearly to be able to effectively block out irrelevant chatter around this topic. The quality of the output of AI models depends on the data being used to train the model over time, that’s why starting as soon as possible is paramount. 

Marketers also need to ensure the data being fed into algorithms or applications is clean enough to draw insights relevant to their objectives – a herculean task in itself. Small test-and-learns can help teams with smaller budgets figure out what applications are most useful and meaningful to adopt immediately before diving too deep with a full-blown AI strategy.

AI is not a silver bullet that can solve all marketing challenges. However, if used well, it can become an indispensable tool in the savvy marketer’s toolkit, helping them deliver both long-term and short-term gains for the brand, and future-proof their overall brand strategy. By starting small and scaling gradually, marketers can harness the power of AI to master the branding trio of differentiation, targeting, and loyalty, ensuring sustainable growth and competitive advantage in the evolving digital landscape.