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Optimizing customer experience: experimentation and personalization

Our expertise working with clients for the past three decades has taught us that great digital experiences are not built overnight. They rather require an iterative approach by which marketers can continuously measure customer engagement in a live environment and optimize experiences accordingly.

Image: Felipe Pelaquim

In this blog post, we want to give an overview of the tools and processes required to make the best digital experiences come to life in an enterprise environment.

How to build an engaging experience for your customers

Building and delivering an engaging customer experience is usually not something you get right on the first try. It requires a thorough understanding of your audience, their interests, expectations and needs through every step of the customer journey.

However, putting yourselves in your customers’ shoes is not just a saying. Consulting with customers during the design and/or testing phase might offer you a way to get to learn about your users and optimize their experience accordingly. This tactic might be well-suited when launching the first version of your digital experience. Constant shifts in customer expectations, market dynamics and technology make it so that a “set-and-forget” tactic is all but optimal.

A more suitable approach is based on the practice of Experience Optimization: continuously iterating on your digital products with the goal of enhancing the customer experience.

Experience Optimization boils down to 2 key processes: Experimentation and Personalization, where both complement each other very well.

Experience optimization in a nutshell

Optimizing customer experience experimentation and personalization

Experimentation is used to test different digital experiences with users and measure the effectiveness of these experiences. In practice, these usually take the form of an A/B test or a multivariate test (MVT). Measuring happens by setting a specific goal and tracking user behavior in analytics. A common goal used is the number of “conversions”, which can take several forms. In its most simple form, it could be a higher Click-Through Rate (CTR) on a certain Call-to-Action (CTA) button. However, conversion can also be seen broader, like for example the number of completed orders or the average order volume over time.

After these tests, a choice can be made about which of the tested experiences is the most effective (a.k.a. the “winning” experience), which is often the one picked to be put live for all customers. However, if analytics show that a certain experience resonates more with a specific customer segment, it might be decided to set up a personalization rule that serves the most-suited experience for that specific segment of customers. This test-driven approach is considered a best practice in Experience Optimization: first test, then personalize!

This is a basic example of Experience Optimization, however, In an enterprise environment, Experience Optimization requires a streamlined process in which different departments of the organization need to collaborate efficiently.

How to optimize customer experiences at scale

Scaling customer experience at larger organizations is often challenging. In such an environment, the volume of content, teams and customer data rapidly increases, fueling the need for a robust technology platform.

In the context of Experience Optimization, a platform that fulfils these needs encompasses 3 key elements:

The connection in customer experience between content & assets, Data and Engine.

But, technology alone is not sufficient for running optimizations at scale. Processes and governance are equally important:

What technology is required to build and run great digital experiences?

When looking at technology, we see a clear evolution toward Digital Experience Platforms (DXP): well-integrated systems designed to streamline business and marketing operations.

At AmeXio, one of the technologies we use as the foundation for such a DXP is Adobe Experience Cloud (AEC). At its core, AEC consists of Adobe Experience Manager (AEM) as a Content Hub, Adobe Analytics and Adobe Target as an optimization engine.

These tools are deeply integrated off-the-shelf, enabling the creation of optimizations from day 1, without the need to set up custom integrations.

As an optimization engine, Adobe acknowledges the synergies between Experimentation and Personalization in their Target offering: capabilities for both are foreseen and designed to be used together.

Experimentation and personalization in customer experience management.

How to get started on experience optimization?

When establishing a culture of optimization at your organization, we recommend by starting off small. Here are our six rules of thumb: