From faster lead follow-up to better self-service: this is how AI can help

The biggest pitfall with generative AI for content is trading quality for quantity. But AI can do much more than mass-produce content. It can also help you plan, organise, enrich, analyse and personalise your content at scale. This calls for a fresh approach: what can you do with content now that wasn’t possible before? Which markets, campaigns or channels are suddenly within reach? It also requires a streamlined content supply chain: one centralised workflow where creation, distribution and analysis work together seamlessly. 

Reorganising your content to reach new goals means more than just translating faster or publishing more blogposts. The focus must remain on quality. There was already plenty of content out there, and AI just added a load of mediocre content. That’s why relevance is more important than ever. It's not just about content, but about smarter, more creative content that really stands out.  

The way consumers search online is changing drastically. Search is being supplemented with AI. This leads to new customer journeys with new opportunities for brands to be seen. Just try it out with your most important keyword: Google shows different results than ChatGPT. So the question is: how does your brand get included in the datasets that LLMs like ChatGPT use? 

The answer is Generative Engine Optimisation (GEO). The key here is brand authority, not just on your own channels, but also through external sources that AI considers trustworthy, such as Wikipedia, Reddit, Emerce.nl and relevant news sources. Visibility is shifting from findability to recognition. Brands that adapt now will have a much better chance of becoming a structural part of the customer journey. 

Chatbots have been around much longer than ChatGPT, but users often preferred other channels. That was mainly due to the quality of these self-service systems: they didn’t understand emotions or context quite well, and only a small percentage of questions were answered correctly. Now, AI interfaces finally understand what customers really mean. Thanks to natural language processing, they can accurately interpret language, language level, jargon, and spelling mistakes. This means users can now ask questions in their own language and get relevant answers. 

An essential part of this is that users can switch to a human if necessary. That’s exactly why Klarna is hiring people again. Not because AI is failing, but because the combination with a human works best. But for those who want to find answers quickly on their own, generative AI makes self-service much better. An interesting bonus is that it gives you insights into the kinds of questions people ask ChatGPT, which in turn helps you with your GEO efforts. 

Customers get frustrated with complicated websites that leave them to figure everything out on their own, and they tend to give up quickly. This is where AI opens possibilities to personalise the customer experience based on user behaviour and preferences. While users are browsing, AI keeps track of what they do: what they click on, what they search for, how long they look at something. Based on these signals, AI understands visitors’ intentions. The website then adapts to guide them through the journey more smoothly: key information appears on top, they see different products, they get more or fewer options. Instead of static pages, visitors get dynamic experiences. 

For example, think of a website with lots of product reviews that shows automated summaries, tailored to your target audience and review score. Or a booking website where a chatbot asks you who you’re traveling with and what you’re looking for, then immediately shows you the most relevant options. The result is an interface that better fits the customer, without them having to filter or scroll. 

You receive a promising lead, but by the time you get to call or email them, their interest has already faded. How can AI help you reach out to leads faster and better? 

AI goes far beyond traditional marketing automation. With AI, you can automatically tailor lead follow-up to the specific enquiry and context. This means AI can answer a product question with specific information, by giving it access to your product database. AI can also classify a lead’s intention and act on it, for example by sending a message to the sales manager saying, “this organisation has requested a demo”. 

Whereas companies often only managed to follow up on about 30% of leads, with the rest disappearing into segmentation lists, sales teams can now respond to 80% or more of all leads in a meaningful way. This creates a much better experience for the lead too, far from the chatbot interactions of the past.

In the end, it’s all about the experience your brand delivers to your customers. Are you offering them what they need? Do you really understand what they want? Do they associate your brand with something positive? If the answer is yes, they are far more likely to make a purchase, stay loyal and become an ambassador for your brand. So focus on using AI to improve your customer experience, because everything else will follow from there. 

These five topics are what we’re seeing most in the market right now. The best application will vary from industry to industry. The challenge is to figure out what works best for your organisation, and the best way to do that is simply to get started. Don’t overcomplicate things. Pick a business problem or a goal that you haven’t been able to achieve just yet and see how AI can help you.

It’s not the speed of your AI adoption that determines your success; it's how customers feel about their experience with your brand. It shouldn’t just be efficient, it should feel good too.