WISMO – where is my order – is an umbrella term that covers a lot of specific customer service use cases. Unlike a lot of questions that customers could ask, it has a huge range of possible answers.
Think about it, the first thing you need to do is work out where the order actually is. Has it been packaged? Has it been shipped? What stage is it at with the carrier? Should it be there by now? Or, in the case of complex or custom items such as furniture or bespoke bikes, has it even been made?
Compare that to an item that has arrived damaged, where there are really only a handful of answers. Yes it’s damaged, would you like a replacement or a refund?
At DigitalGenius, when our ecommerce customers are mapping out their WISMO flows, it’s essential to get as granular as possible to find exactly where the package is. The upshot of this is that you can then use analytics to highlight issues in your logistics process. Let’s walk through it.
The different types of WISMO response
WISMO makes up around 20% of a retailer's customer service queries – more so during peak periods. Imagine you get that simple question from a question “Where is my order?”, your first step is to find out where your systems are telling you the order is. So maybe you first check to see if it has a tracking number from a carrier. If not, then you start working your way backwards to establish where you think it is.
The next question is to work out where it should be. So you check the expected time frames and see if the order is in scope for that. You also need to check what shipping option the customer chose to ensure that you are meeting that agreement. For example if they paid for next day shipping and it’s been 5 days, then clearly you have a problem and you should refund their shipping costs.
If you find out that the order is marked as “delivered” then you have to assume that the customer has not received it. So either it’s a mistake, or they’ve missed it, but either way you need to investigate.
The point here is that there are a handful of different places an order could be. Then if you consider the timelines, and then the fact that the customer is asking you about it, you quickly build up a long list of possible WISMO responses.
Your agents need to be able to deal with all of these circumstances, and the same is true for any automation tools you want to use.
Bad examples of WISMO responses
We recently saw a chatbot flow that went like this:Where is my order?
Has it been more than 10 working days since you placed the order? Yes/No
No
Typically orders are shipped within 2-5 working days, and take 3-5 working days to arrive. Please wait 10 days for your order. If it has still not arrived, please get back in touch.
To list the ways that this is bad:
This was entirely generic
There was no attempt to personalise or consider the context
It didn’t answer the question at all
It didn’t even provide a tracking link (there was one available)
It didn’t look into what shipping option the customer picked
We see other examples where the default is just to provide a tracking link to the customer. In so many cases, the customer has the tracking link and is reaching out because something has gone wrong, but that hasn’t been considered by the chatbot.
That’s why for chatbots to be effective, they need deep integrations.
The importance of deep integrations
Having deep integrations to your various systems, such as warehouses, order management systems, carriers and so on, allows the chatbot to do what an agent would do. That is, look up where an item is claimed to be, and compare that to where it’s supposed to be.
Using APIs, and other forms of integration DigitalGenius can do this by pulling the relevant information in, and incorporating that into the order.
Deep integrations also allow your bot to reflect the context. There is a world of difference between a response that just assumes information about an order (like the above example) compared to one that says “I can see that your order has been in transit for X days”.
With these deep integrations, you can then apply your own business logic to different scenarios. So if an order has not moved for 3 days, you can provide a different response compared to if it is moving at the right pace. Using generative AI, you can then help shape the exact responses you give more quickly.
Finding issues in your logistics process through customer service
So, once you have your flows all mapped out, then you can start responding to customers. Soon you are going to be building up a corpus of data about each of these WISMO responses, firstly including the volume of certain responses given.
This gives you the insight to see what the most common times for customers to enquire about the status of their packages are. You can also see where there might be bottlenecks, or where things are taking too long. You can then set about trying to fix any of these issues, or change how you communicate.
For example, if you say that it takes 3 to 5 working days for an item to arrive, but actually you are getting a lot of queries after 5 working days, you can amend your SLAs, or set about finding out why.
Similarly if you get a sudden spike, you may be able to detect something that needs fixing or changing. The fact that you’ve been able to be so granular with exactly what type of WISMO query means you have valuable data to help you be as efficient as possible.
On top of that you can look into the CSAT scores associated with each flow. You can then see which flows need more work, and which are performing well. Perhaps you need to take a different approach in some cases to boost that customer satisfaction.
How do we approach WISMO questions?
To see for yourself how we handle WISMO questions, have a watch of our webinar where we take you through all things WISMO here.
WISMO, WISMO, wherefore art thou, WISMO?
If you can really nail the intricacies of all your WISMO flows, then you are well on the way to providing a great experience for your customers. They can get 24/7 resolutions to their queries, and your customer service agents aren’t dealing with a really common, repetitive query. It’s a win-win-win.
Talk to us today to find out more.
