Interview ODOSCOPE with Andre Morys - Founder and CEO of Konversionskraft

Interview with konversionsKRAFT founder André Morys

The topic of Customer Experience Optimization (CXO) is often characterized by a competition between decisions that are as fast as possible and as accurate as possible. When does real-time optimization make sense and when does a shop owner benefit more from the basis of larger data sets?
In the following interview excerpt, André Morys, the founder of
konversionsKRAFT, answers these and other questions about personalization processes. This interview was conducted as part of our research for our white paper “Customer Experience Optimization”, in which four prominent top experts from the fields of online marketing and digital analytics take a closer look at CXO.

→ For more insights, download our whitepaper on data-driven customer experience optimization.

ODOSCOPE: Hello, André. I am pleased that you are answering a few questions about Customer Experience and how to optimize it. Can you please introduce yourself at the beginning?

André Morys: Yes, of course. My name is André, I am founder of konversionsKRAFT. We’re now 85 consultants and colleagues who are focused on delivering better customer experience, more ROI and more revenue for our customers – more growth.

ODOSCOPE: Everybody wants more growth. How would you define customer experience and how do you measure a good or possibly bad customer experience?

André Morys: That’s the crux of it. Customer experience cannot be measured, because it runs deep somewhere in the brain of a customer. The customer himself is not aware of many aspects of the customer experience! You can’t ask customers “How do you find this hotel booking page?” and the customer answers “Oh yeah, I miss Scarcity here”. You know what I mean? So we also need expert knowledge. And what is sold is not necessarily what the customer thinks is great. There are also many questions of definition.

Measuring customer experience is difficult. Actually, we just want to achieve the turnover and therefore the question is: Which customer experience ultimately brings the company a contribution to turnover? I would therefore distinguish between researching and understanding the customer experience, i.e. qualitatively. You can measure the outcome of a good customer experience. But what you now call a good customer experience may be something the customer wouldn’t even say: “This is the perfect customer experience now.” You have to be aware of that.

ODOSCOPE: I see what you mean. Is it better to optimize in order to meet existing customer expectations, or do I design a specific customer experience that is then accepted by the customer? How do you go about it?

André Morys: As I said, customers are often not even aware of what they need. Only when they see it do they think it’s great. That’s why I always say, “It’s both! Of course, you have to meet A’s hygiene factors and needs from the customer’s point of view – a customer wants some problem solved and that is your minimum requirement of where you are going with the customer. But then, by cleverly adding elements that a customer may not be aware of, you can ultimately increase the outcome of your customer experience.

But you can only deliver the ‘more’ when you have already developed the base. So say, if your online shop or website is so bad that it doesn’t meet the basic requirements, then you don’t need to build anything. There are also these analogies to iPhone and Nokia mobile phones. Basically, you need both.

ODOSCOPE: If I then optimize, where and when does real-time optimization make sense? This means that you are faster, but may have less data available. And where does real-time optimization not make sense?

André Morys: Well, first of all the calculation here is quite simple. The faster I deliver a good customer experience, the more ROI I have. So why would I wait with that? From the, I say, “Conversion Optimizer view” we know that we want to influence the behavior of a customer. The earlier the customer perceives this stimulus, the earlier we can change his behaviour.

That on one side. On the other hand, of course, we also have requirements for a certain quality. If I show the customer nonsense because I have too little or bad data, it’s not good either. So somewhere I have to find the optimum under these conditions. But I would always say that good results need contrasting changes. That’s why I advocate, the sooner the better with real-time optimization.

ODOSCOPE: Very good. Especially in times when everything is immediately available, no one is patient any more and the attention spans are decreasing.

André Morys: Right. Much more important, in my opinion, is that we are aware that a customer also has the need to have a consistent customer experience. So I have to be careful with every personalization: If a customer sits at his desktop computer in the office during the day, surfs and gets any category page with results displayed, he might want to show them to his wife in the evening. He takes the iPad, then has a different user profile, different cookies and then says: “Look, I found this article” and it’s gone. A worst-case scenario from a customer experience perspective! In order to decide how much we change, how quickly and how well we change it, we must of course understand it well: How does the customer tick?

ODOSCOPE: Yes, exactly, we have already had many discussions about that. So this case: the list is different, then you can no longer find the products you actually wanted to show. There’s a trade-off. There is also another conflict of goals in the context of personalization, whether one should make rule-based or data-driven decisions. What do you prefer and how would you rate the two possibilities?

André Morys: Well, I don’t see any contradiction here. I might even build some kind of pyramid model out of it. Because maybe I can even fundamentally change the customer experience for all customers without calling it personalization – but just a good customer experience and I don’t need any fixed rules for that.

Then perhaps I am rule-based, because there are such basic, simple things that I can do with a simple rule. Then I should implement them. Then maybe I would add data-based real-time targeting to the top, as an extra layer. Certainly someone has already made such a model, but for me this is not a contradiction at all.

ODOSCOPE: I see what you mean. This means that such a combination can actually deliver even better results than focusing on just one approach.

André Morys: Exactly. From the conversion point of view we are always trimmed for ROI. When I optimize a customer experience for all of my customers, I naturally have a greater ROI because it is effective for all of them than if I did it specifically for one segment. So a rule-based personalization, which plays out some element that I’ve previously fixed, only pulls in a certain segment again. So I have to be careful not to make the ROI “homeopathic” because of my granularity. If I have a good personalization, then of course I have to make sure that I get it effective for as large a segment of my customers as possible.

ODOSCOPE: Is there perhaps a way to anticipate change? If you somehow notice that certain things have to be changed, because otherwise the customers jump off me and the conversion rate goes down?

André Morys: Definitely. This applies in principle to optimizations of the customer experience as well as to personalization. A good salesman also knows when you walk into the store or showroom. Suppose you go to your BMW dealer and buy the new M5 tomorrow. You’re going in there with such a cautious walk. Then the salesman knows even before you say the first word, “oh, maybe you could be such a traditional customer”. So he anticipates your preferences based on certain signals you send.

A good personalization does nothing other than that and looks when I have a certain referrer, for example from a price comparison portal: “A valid signal for the fact that I am a certain type of customer”. So why wait with the personalization? Our psychological background gives us a qualitative view of clusters. So you say cluster A versus cluster B is one view, the data view. But what does that plaid shirt mean now? What better way to sell you this BMW if you’re wearing a plaid shirt? The good salesman knows that.

ODOSCOPE: Yes, it is. Exciting points. I jump back to the question where you said it needs a good basis to optimize a customer experience. I suppose you’re referring to both technological and human, that is, procedural as well as organizational, aren’t you?

André Morys: Well. First of all, we have to put ourselves in the shoes of the customer and tell ourselves that he doesn’t make a difference. He goes to a website and says: “Phew, I’ve got something here, but I can’t find my way around”. And now it can be personalized the way it wants to be. If I feel like I’m wrong here or it’s too expensive, I’m going away again. This does not only happen in personalization. This also happens with technical changes to shops, which are now to become more responsive. Then everything has more white space, looks more expensive and customers no longer buy.

It’s nice that everything is now working seamlessly on all devices, but if my shop now looks expensive, but I sell items that are not expensive at all, I have a problem. That’s what I mean by hygiene factors. Because if something bothers you, the customer jumps off. Only when I have solved the hygiene factors can I optimize other factors. These are things that I basically have to optimize in the Customer Experience. And only when they are regulated can I get to grips with the so-called enthusiasm factors. This is an ancient model of a Japanese named Kano, which unfortunately is often forgotten, and that includes everything. No matter whether logistics, customer experience, assortment or personalization.

This interview was conducted by Sven Verborg, ODOSCOPE.