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Topic(s): Artificial Intelligence Customer Experience

How AI can help you deliver an 11-star customer experience

The 11-star experience

When you're a customer interacting with a brand and everything meets your expectations, you’re happy to give a 5-star review to that company in return. But what would happen if an organization aims higher than 5 stars? What would happen if an organization wants to offer a 10-or even an 11-star experience? Brian Chesky, CEO of Airbnb talked about this during an interview for Masters of Scale: ‘Do things that don’t scale’.

Delivering an 11-star experience would mean that an organization has unlimited resources to ensure that the customer has a crazy, over-the-top experience. Imagine yourself going on a vacation. You step out of the plane and there’s Elon Musk, waiting for you to give you a warm welcome. But then he says, ‘Let’s shoot you to the moon first, there’s a live private concert of your favorite band waiting for you to start. After, you can go to your all-in mansion where everything is perfectly arranged.’

Of course, offering this kind of experience is unfeasible. But what organizations can do is reverse engineer that 11-star experience. By thinking about what they want to achieve exactly with customer experience, they can take a step back and define what a 6- or 7-star experience would look like. Next, they need to figure out how they can do that with the available resources. Artificial Intelligence (AI) can help organizations answer that question

the 11 star frameworkSource: Jessica Pang, UXDesign.cc


Why you need AI: tomato soup with meatballs

There’s quite a famous analogy between AI and tomato soup with meatballs. Unless you have the entire pot of soup to yourself, when you're eating tomato soup with meatballs, you like to scoop up as many meatballs as possible. But if you can only get one spoonful, you need to figure out what’s the best way to position your spoon to get as many meatballs as possible in one go.

The same goes for AI. If you have unlimited resources to create an 11-star experience, then you don’t really need AI to help you move forward, as you can invest in as many projects as you want. But if resources are limited, which is the case in many organizations, you have to work within certain restrictions and you need to make smart investments. AI can help you to be as efficient as possible with the resources at hand and helps you to prioritize the right actions to level up your customer experience to that 6 or 7 star-experience and set you apart from competitors.  

It all starts with data: Data mesh principle

AI is more than just machine learning and algorithms. AI represents a complete flow that starts with the data, which gets put in the algorithm and eventually presented to the end-user.

DATA FLOWRepresentation of the data flow within Hello Customer

For data to be valuable it’s crucial that you can manage, store and use data in an efficient way. That’s where the concept of data mesh comes into play. Data meshing originated in software engineering. Software engineers used to build really big systems called monoliths. But over time they realized that these systems were way too big, too complex, and simply not maintainable. So they decided to look for a way to break these systems down into multiple smaller services, which smaller teams can work on. This way, every team can change what they want within their own, smaller system which is much easier to manage.

In 2018 we saw a similar evolution in the data space. Up until then, organizations often used big data warehouses to centralize all their data. The downside was that that data never fitted a specific use case: the finance department wants to see data in a different way than the product or marketing team. Instead of using huge data warehouses, the data mesh principle suggests providing every team with its own, smaller warehouse. This way, the data gets divided into different domains for different departments in an organization, which can manage and make use of the data in a way that is relevant to them.

Applying data mesh to customer experience

So, how can data mesh help you improve customer experience? If different departments have access to their own data, they can use it for internal purposes, but they can also connect that data with external tools like customer experience software. This way, your CX software becomes a data product in your data mesh setup. Hello Customer for example allows companies to easily connect any data you already own to the platform, allowing you to create and compare different customer or product segments for example.

The other way around, you can push the data you collected in the Hello Customer platform to your own systems via API or via our Snowflake connector. This way your CX team can use that data to present your results to the rest of the organization. This can help with building a business case on the ROI of your customer experience improvements, e.g. by linking received customer feedback to your revenue data so you can truly understand what impacts your revenue in a positive or negative way.

integrations HC

Integration model of Hello Customer


Creating an 11-star experience with Hello Customer

As previously mentioned, for data to be valuable it’s crucial that you can manage, store and use data in an efficient way. Similarly, when it comes to improving your CX, data is just data if you don’t know how to transform it into insights that are relevant to your business. At Hello Customer, we constantly innovate to improve these insights, both quantitative and qualitative, using AI.

AI-powered quantitative insights

When it comes to quantitative insights, our Key Driver Analysis (KDA) is a crucial tool to understand what you need to prioritize to improve a chosen KPI, based on statistical relevance. The KDA actually matches the 'tomato soup with meatballs' comparison very well: if you don’t have the scope, the budget, or the resources to fix everything all at once, the Key Driver Analysis shows you what to focus on first. Everything that finds itself in the ‘Fix This Now!’ quadrant has a big influence on the general happiness of your customers. This is where you should first put your resources on your mission to deliver that 6-or 7-star experience.


KDA potential gain

Hello Customer's Key Driver Analysis


AI-powered qualitative insights

For the past years at Hello Customer, we have worked hard on ISAAC, our in-house AI analysis. ISAAC specializes in transforming large volumes of customer feedback into tangible, qualitative insights. Our AI analyzes each item of customer feedback separately and breaks it down into multiple predictions so you know in detail what your customers are talking about. Next, it also applies sentiment to each detected topic so you quickly know what drives customer satisfaction and in consequence what you should keep in mind to create a 6- or 7-star experience.

ISAAC analysis ENGCustomer feedback analysis in Hello Customer


Taking it to the next level: generative AI

Technological evolutions in AI have been skyrocketing lately, largely thanks to OpenAI’s release of ChatGPT to the world. Although the total impact still remains to be seen, programs like ChatGPT are already changing and optimizing the way organizations have been working for years. ChatGPT and all of these other large language models are called ‘generative AI’, as they are very strong in generating text.

How does generative AI work? You can see ChatGPT as a black box which is actually a complicated mathematical function. This function gets a certain input like ‘We will, we will…’ (1). The black box then tries to predict what the next word could be. In the beginning, the black box doesn’t know anything and will fill in the parameters randomly to generate a random outcome (2).

Generative AI flow
However, as ChatGPT runs on data available on the internet, it could predict the correct answer: ‘ROCK YOU!’ (3). Because of this, the black box can adapt all the parameters so that when it gets the same input in the future, it will predict the right outcome. This requires millions of examples and it will iterate this process millions of times, changing the parameters a little bit each time. This is called the learning or training step. (4)

Generative AI flow 1

Our team has already developed solutions based on generative AI, like our automated summaries. Automated summaries give you an instant summary of the feedback you have collected about a specific topic, so you don’t need to comb through thousands of feedback items yourself. On top, it gives you the top 3 positive and top 3 negative mentioned topics, and it even gives you suggestions for improvements.

automated summariesAutomated summaries in the Hello Customer platform



Even though creating an 11-star experience is impossible for most companies, they can go all-in on a 6- or 7-star experience. To achieve that, AI can help organizations deliver exceptional customer experiences, within their available resources. By using AI to manage data, prioritize customer needs, and generate insights, organizations can provide a level of service that sets them apart from their competitors. 

Want to learn more about our AI-powered customer feedback platform and how it can help you deliver an 11-star experience to your customers? Check out our platform or request a demo, we’re happy to help.