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Why customer service data is a goldmine

Why customer service data is a goldmine

Technology in E-commerce, part 3

This is the third part in our series where we speak about how technology can be used to enhance customer experiences, save costs, and drive revenue for you and your website. 

Part 1: Three ways to decrease customer service costs using technology

Part 2: The secret behind customer service that's great for both customers and your business

Written by Tobias Riis Christensen

The best use case of AI

With the launch of Chat GPT-3 in late 2022, AI has been on the lips of almost everyone in e-commerce. How can we use AI? How can we scale with AI? How can we automate with AI? 

Now the hype has flattened out a bit, more scalable and sustainable use cases are proving themselves, and we are more realistic in the hopes and expectations we have for AI in e-commerce.

The use case we want to talk about today is using AI to analyse and categorise your customer service conversations. By doing this, you can get incredible insights into what your customers are talking about - insights that you can use to improve the customer journey! 


How AI can help improve the customer journey

Somestimes, customers reach out to say how happy they are about a product or service – that accounts for approximately 1% of your conversations (if you are lucky). 99% of the time a customer reaches out to customer service it is because they are having an issue or a question. Not only is this frustrating to the customer, it is also costly for you. 

How do we go from that to AI that improve customer journeys? What you do is look at your customer service conversations and identifying which issues customers experience are most common and then fix those. Is it discount codes not working? Is it questions about stock status? Is it customers asking for updates on their delivery? Is the product damaged? When the issue that is bothering customers is identified you then make changes to processes so the next customer will have a smoother experience.

AI comes into this as it can process immense amount of data quickly. With AI you are able to, in real time, identify exactly what each conversation that comes in is about. The result is then a list of subjects that customers are asking that you can treat as a to-do list. If there are 382 conversations about damaged products in the last month, those conversations can be investigated to figure out what is causing them to arrive damaged – maybe some extra cotton wool would do the trick, and then you don't receive those 382 conversations a month, and can spend those extra resources delivering additional value to customers.


Examples of customer journey improvements

I would like to share some specific examples of our clients that have managed to improve the customer journey by looking at customer service data. Hopefully that can inspire you to look at your customer service data in a similar way.

One of our clients identified that a lot of orders contained another product than what the customer had ordered. The client had their own warehouse, packed orders themselves but no one could explain why this would happen. The client looked through some of the conversations and identified that it was the same two products that were usually interchanged. Then, the reason became clear – the two products were right besides each other at the warehouse and the products' names on the labels were similar! They then moved the boxes further apart and the amount of customers receiving incorrect products fell dramatically.

Another webshop, this time one selling equipment for home DIY projects, had a lot of questions about delivery times – which seemed odd, since it was clearly stated on their site. It turned out customers were curious about express and pick-up options, as timing was very important to that group of customers, as they were often assembling teams of friends or professionals to help finish their DIY projects. An improved delivery flow, where customers could pick up themselves when it fit them, which decreased the amount of conversations, improved conversion, and drove revenue.

These are examples from the real world of e-commerce on how companies have dived into their customer service data to improve the customer journey of their customers. AI can make it really easy to boil it down to a list of initiatives you can take – you can read more about this on our Customer Insights page.



We have been discussing why customer service data is a goldmine when it comes to improving the customer journey. With AI you can immediately analyse all conversations, and figure out which issues happen the most - and then remove them by optimising your processes and the way you work!

This is the third article in our five-part series about technology in e-commerce. Make sure to catch the other parts for insights on how technology can be used to decrease costs, drive revenue, and improve customer experiences. Find them below:

Part 1: Three ways to decrease customer service costs using technology

Part 2: The secret behind customer service that's great for both customers and your business


Tobias Riis Christensen

Tobias is a Product Owner and Business Developer at MakesYouLocal. He helps companies leverage AI technology and automations within customer service to improve processes and drive revenue, and ensures that webshops fully benefit from available technologies in their expansion journey.


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