How AI Enables Marketers To Target Digital-Savvy Gen Z Customers

Forbes

18 hours ago

Wolfgang Sixl, VP Strategy, Analytics & Client Solutions, MCE Systems - Bridging Technology and Commercialization.
How can we understand the mindset of Gen Z consumers?
We can ask Freddie Mercury. He seemed to anticipate their desire for immediate gratification when he wrote the song 'I Want It All.'
Then, he nailed their longing for personalization with the song 'I Want To Break Free.'
Obviously, the members of Queen were not thinking about the brand experiences of young digital consumers when they were penning lyrics 40 years ago. Nevertheless, these titles are uncannily relevant.
Today's digital-savvy consumers are seeking not only customization, but also expediency. The data confirms it. According to a Salesforce consumer trend report, 81% of customers expect faster service as technology advances, and 73% expect better personalization.
In response, companies are jockeying for a better position. They are exploring new technologies that grab attention and improve loyalty—and help them meet customers' demands.
AI Makes It Personal
This isn't a new trend. Marketers already use tools like programmatic digital ads to deliver custom promos, targeting users based on past brand interactions or shopping behavior.
Now, AI tools are pushing this further. But mass customization marketing has had limited success, falling short of the true hyper-personalization consumers expect.
Two years ago, it looked promising. ChatGPT dazzled with its capabilities, and 98% of companies felt a newfound urgency to adopt AI.
Yet success remains elusive. While generating blogs, emails and ad copy is easy, creating personalized user journeys that drive real business results is another challenge entirely
How can they change this? I think there are three key barriers to overcome:
• Data Relevancy And Accuracy: In the marketing context, we want to prompt the customer to take an action. Here, AI engines can help. They can craft relevant offers calibrated to a user's specific tastes—but only if they are fed relevant and accurate enterprise-specific data. So, organizations must make sure the AI model has enough context to deliver the appropriate output.
• Data Timeliness: Relevant data is only half the story. Data must be up to date too. Real-time user and market information is vital for personalization. Without it, we can imagine a scenario where an AI model advertises outdated offers or—worse—sends irrelevant promotions to customers who have already converted.
• Execution: AI tools are new and unfamiliar to many organizations. It's very easy to implement a dysfunctional AI program. Common challenges in this space include aligning the tech to business objectives, overcoming staff resistance to change and ensuring the right people are leading the AI project.
A Program To Prepare For Change
To overcome the above challenges, stakeholders within a business must align. They must build guardrails that overcome model limitations, leverage enterprise-specific customer data and build an AI-native culture.
Large enterprises should start by collecting enterprise data (which includes real-time and metadata) from their digital customer points of interaction. They can couple this with a basic LLM model to create a 'sandboxed' enterprise-grade AI application. The output of the resulting AI application will combine the customer's preference with live market data.
Second, businesses must make sure their AI application is safe and focused—and avoids undesired outputs. They should prevent any exposure to malicious actors and make sure they follow all regulatory compliance to avoid violations and legal risks.
Lastly, enterprises must unite all staff behind the new processes. This starts with senior leaders establishing a cohesive business-technology plan, and assembling the right team to manage the changes.
The last point is vital. Workers across all industries are understandably anxious about AI. Nearly 60% of business leaders said in a survey this alarm was driven by a lack of knowledge. So organizations must foster a culture of openness to defuse employee concerns.
A Success Story: Mobile Device Care For Mobile Carriers
Even at this formative stage for AI, thousands of large enterprises are already seeing results. Javier Meza, Coca Cola's Europe CMO, shared last year how his company is using first-party data and AI to shift from a broad targeting style to a more consumer-centric approach.
Mobile carriers are well-placed to follow this example. These businesses possess huge amounts of relevant real-time first-party data. Clearly, the raw materials are there to deliver personalized services that can drive loyalty, prevent churn and grow ARPU.
Some carriers are already experimenting. Take the market for device care and upgrades, for example.
Industry data that we see at my company shows that customers want intelligent, personalized offers when they encounter an issue with their device—such as a value added service (VAS) or a trade-in. But for years, this has been a clunky, manual process that has not served customers well.
At MCE, we saw an opportunity to make device care digital and self-serve. First, we built a GenAI solution for chatbots in a mobile operator app. Then we connected it to an enterprise-grade application that sources live device data such as diagnostics, device configuration information and user conversational inputs.
The final part was tapping into a carrier's existing marketing database, so we partnered with a third party to build out a chatbot for them. With this real-world application, we were able to reduce mobile app utility inertia, increase marketing promo actioning and drive more retail visit intent.
When we applied GenAI to this solution, we noticed quite an uptick in engagement afterward—quadruple engagement with our pilot's custom journey, triple marketing promo engagement and nearly double the retail store locator opens.
Conclusion
AI is game-changing technology. It gives marketers the chance to deliver on the dream of genuine mass personalization.
The examples are already out there. So, now is the time to get ahead of the game, embrace the tech, build a unified internal culture and give customers the products and services they deserve.
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