Three Ways AI Can Supercharge Marketing for the CMO by Personalising Campaigns at Scale

The pitch for personalised marketing is compelling. Nearly 75% of consumers are more likely to purchase from brands that deliver bespoke experiences and businesses that excel at personalisation are 48% more likely to have exceeded their revenue goals than those with ‘low personalisation maturity’.

That’s why McKinsey & Company stated that it’s “not only a crucial capability; it’s one that punches above its weight” and Forbes described it as no longer a luxury but a necessity. 

But personalisation comes with significant challenges. Segmenting audiences, tailor-made content creation, smart activation, and data accuracy and privacy have all meant the barrier to entry has been high. In this article, we’ll explore how Artificial Intelligence (AI) is changing all that. Making it easier than ever for brands to personalise at scale. 

So, how is AI marketing democratising personalisation? Where can it have an impact? And how can you apply AI to improve the customer experience?  

How AI marketing can help you personalise at scale 

1. Identifying high-value customers   

Audience categorisation based on age targeting is only accurate between 4% and 44% of the time. 

Brands have traditionally categorised audiences based on demographic data — age, location, gender, and a little intuition about what certain customers might like. As data became more abundant, marketers were able to get more granular and personalised, targeting based on purchase history or contacting customers by name. AI has now raised the bar again, allowing brands to look at all touchpoints with individual customers, providing a holistic, omnichannel view of activity in real-time, and enabling segmentation marketing in a far more dynamic and effective way. 

Take Touring Club Suisse (TCS) as an example. TCS is the largest mobility club in Switzerland, protecting 1.5 million members on their travels: “Our members are at the centre of everything we do… Being customer-centric sets us apart from the competition,” says Bernhard Bieri, Director ‘Business Unit Club’, TCS.

To achieve this, TCS used an AI-powered centralised platform and predictive analytics “to implement segmentation marketing and follow up with offers that match their interests at different stages in the sales funnel,” Bieri explained. 

With these AI tools, you can focus resources on the most promising opportunities, make smarter decisions about customer needs, and connect them at the right time on the right channel. As Bieri continued, “We can pinpoint the best time to send communications, so they’ll have the biggest impact and highest engagement rates.” 

Key takeaways: 

1. Leverage real-time data: The quicker you react to customer buying signals, the more likely you are to convert. AI can help track, contextualise, and react to customers’ buying signals in real time.
2. Optimise resource allocation: Let AI guide you to the customer segments with the highest potential. You can then focus your efforts where they’ll have the biggest impact and see a better return on investment.
3. Improve timing and relevance: With AI, you can find the perfect time to reach out to customers. This ensures your messages hit home when consumers are most likely to engage.

2. Personalising content at scale   

73% of customers worldwide expect better personalisation as technology advances.

Personalising content requires a deep understanding of customer needs, challenges, and preferences. Where marketers previously had to sift through mountains of data to find the information needed to personalise engagement with target accounts, AI can surface these insights instantly. From tailored messages, emails, and content, AI allows brands to scale personalisation and segmentation marketing without compromising quality. 

This approach helped fintech company GoHenry double its customer base in two years. As Sonia Lele, Senior Director, Data Science, Salesforce, explains “Its AI-powered platform helps teams to identify high-value segments faster so [they’re] able to target them with relevant, personalised messaging.”   

Customers can connect with agents using their preferred channel — including email, phone, live chat, and social media — and AI-powered chatbots support customer queries by routing complex cases to the most relevant free agent. Adopting AI in this way enables you to improve personalisation and marketing metrics across all user journey stages. 

Key takeaways: 

1. Implement predictive analytics: AI-driven insights help you stay one step ahead. You can predict what your customers need next, allowing you to engage them proactively with personalised offers that hit the mark.
2. Leverage AI-powered support: The faster your customer service, the more effective it’ll be. AI-powered chatbots provide tailored information, reduce wait times, and boost satisfaction.
3. Scale personalisation: Delivering bespoke content at scale helps you to strengthen customer retention. With AI, you can adapt content, tone of voice, and visuals to customers’ specific preferences.

3. Integrating sales and marketing efforts 

Formula 1 boosts fan satisfaction to 88% and first-call resolution to 86% via AI-powered automated chatbots. 

One of the biggest benefits of AI is facilitating better alignment between marketing and sales via shared insights and data. Both teams can engage with prospects more effectively by collaborating on segmentation marketing, scoring and targeting based on account attributes and spending patterns.  

This is what helped Formula 1 — who interacts with thousands of fans — to turn its popularity surge into longer-term sustained growth and loyalty. 

Behind the scenes, data was out of sync and communication lapsed between teams. With an AI-powered data platform, “We’ve improved the processes, templates, speed of resolution, tooling, and how our teams navigate,” said Matthew Kemp, Formula 1’s Senior CRM and Customer Operations Manager. 

With data connected and shared on an AI-powered platform, it’s clear to all teams where prospects are in the sales lifecycle. This provides you with deeper insights to scale growth. 

Key takeaways:  

1. Align Marketing and Sales: Bringing Marketing and Sales together fosters better teamwork. With AI-powered insights, you can align your marketing and sales efforts with shared data and information.
2. Synchronise data: Using an AI-powered platform unifies your data, breaks down silos, and creates smoother, more consistent communication across your teams.
3. Gain visibility into lifecycle stages: With AI-powered platforms, you can gain clarity on where prospects are in the sales cycle. This helps you to better engage with potential customers.

AI marketing: a winning strategy  

AI-powered marketing has opened a new world of possibilities for CMOs. When brands adopt AI, it’s easier than ever to target high-value accounts and personalise customer engagement. And when teams are aligned and marketing efforts are integrated, you create a streamlined strategy that keeps you ahead of the curve.