Customer Experience at ZEISS: How data creates customer centricity
Since the founder of the ZEISS Group, Carl Zeiss, developed his first microscope in 1857, we’ve always had an inherent appreciation for the way that data and analysis can lead to deep insights. Today, we are still known as a technology leader in the optic and optoelectronic industry: from high-quality microscopes, precision eyeglass lenses, medical solutions to semiconductor manufacturing enabling the next generation of microchips. But next to our hardware, we also develop digital solutions and of course use data as the foundation for our digital future.
For me, data has always been more than just numbers. It offers insights into real life. As Global Head of ZEISS Digital Partners within the ZEISS Group, I see digital tools as a logical and modern continuation of our long history with measurement. But the cleanest and nicest data does not bring value itself: insights based on data help us to understand our customers and especially how to communicate and interact with them in a more targeted way.
https://video.tv.adobe.com/v/3440716
In this short video I explain further details how we at ZEISS Group use data to create customer centricity.
Data excellence: How we fulfill customer needs in real time
I think data is necessary to understand what our customers desire, it enables us to offer what they need at any given moment. To be able to respond to and fulfil these needs, we use data from all of our customer touchpoints, including for example our website, online store, and sales transactions.
In my view, there are three things necessary to respond to your customers’ needs in real time:
- A scalable content management system (CMS) to create and deliver content that customers want.
- A company-wide data infrastructure that removes silos and integrates customer data across all processes to gain a 360-degree view of customer needs.
- And a system that enables us to monitor the impact of our content so that we can distribute the right personalized content for a target group.
How are we addressing these factors at ZEISS? After a successful start with Adobe Marketo Engage, we expanded our Adobe portfolio with Adobe Experience Manager Sites as our foundation. In a second step we introduced an intermediate customer data layer with Adobe Real-Time Customer Data Platform (CDP). This provides a solid base for data excellence that helped us gain an accurate picture of our current customers and identifying future prospects. And thirdly, in my opinion, equally important is monitoring the effectiveness of the content, otherwise you run the risk to deploying messages and content which are not really personalized and suited to the expectations of the target group. I really want to point out that an effective data infrastructure is truly the core and at the heart of every successful personalization effort. Why? Because it's necessary to mitigate the risks that you have from having isolated data silos, not only across business units, but also resulting from different channels.
More customer engagement and trust with Generative AI
Generative AI (GenAI) takes this a step further and has a huge potential also for us at ZEISS being active in the B2B area. It allows us to create a true omnichannel experience for our customers by automatically adapting messages within the right channel for every customer in real time. We already can see the impact on our customers, who are more active and engaged. In one recent campaign using generative AI, the click-through rate rose from around 30% to up to 55%. We started implementing use cases regarding content creation and used it to localize messages, for example, for translation purposes. It helps us effectively and quickly scale the messages across the globe. And secondly, also in the context of deploying messages to different channels to create an omnichannel experience. We of course plan to use Generative AI in the context of personalization and content creation in more use cases in the future.
Set your basics right and manage change successfully
If you are currently in the midst of a transformation process and looking for ways to get started, I would like to pinpoint two aspects. First and foremost is fixing the basics, get the basics right! And in our experience, there is no real shortcut. If you do not have global data governance in place, if you do not master data management, it's very difficult to benefit from the value promises of new tools which support personalization or where GenAI could be brought into the equation. And secondly, a successful implementation of a personalization experience, at least in our experience, always relates to successful change management. So, mastering the tech part is one thing, but change management, meaning bringing teams together, instilling a high mode of cross-departmental collaboration, is equally important.