For most brands aiming to improve customer experience (CX), analytics are invaluable and track the success metrics. In other words: how a particular product or campaign is performing, or in some cases not performing as expected. Having analytics helps brands identify problems and points of friction which then enables them to make the necessary changes to get better results. These measures for success, knowing what the end goal is that needs to be achieved, can also help get teams aligned on strategy and ultimately lead to better outcomes.
But as most marketers know, improving CX is highly complex. There are many variables and factors that influence buying behavior and these are constantly changing. In a recent Think CX webinar (THINK CX: PART 19 How to use analytics to improve the customer experience), career product manager Lina Mamut and UX strategist Dan Zola, shared their perspectives on the best use of analytics to improve CX. These are some key takeaways from the webinar which is available for on-demand replay:
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Identify a north star metric
Having a north star metric that is guiding the overall strategy is critical to navigating the complexities of CX. Defining what that north star metric is best done through collaborative brainstorming and requires a three pronged approach:
- First, identify all possible big metrics so that these can be refined down to the most important ones to target. The key here is to prioritize and align on common goals.
- Second, understand what website visitors need to do, what actions they need to take so that specific metrics can be achieved.
- Finally, identify what ties these two elements together. Once you’ve worked through both, it should become fairly obvious how they align. It then comes down to identifying the primary (north star) metric and related secondary metrics.
Once you agree on what the measures of success are, it becomes easier to identify what data is important and track how visitor actions are influenced.
2. Seek to understand user experience (UX) better
One of the biggest challenges brands face is understanding how new users perceive their products or services. For people working in a company, they know everything about the product. What it is supposed to do and the benefits it offers. This can skew perceptions and expectations because it is biased towards having an in-depth understanding of the product which new prospective customers don’t necessarily have. Brands are often surprised that customers don’t respond or behave like they think they should. There is immense value in finding out what is really meaningful to website visitors or first time customers.
The sweet spot is where user goals align with brand goals. For example: For the prospective customer, if it’s easy to purchase, they may purchase again, or refer friends. For the brand, the goal may be to drive sales and revenue. If the brand helps the customers achieve their goals, they’ll also achieve the brand’s goals. This exact strategy is reported to be the foundation of Amazon’s success from its very early days and they’re now a brand revered for their CX success.
Being able to experiment with a broad range of ideas can help brands see what visitors are responding to and by default what’s important to them. In a marketplace where customer preferences are constantly changing, being able to have this type of data is incredibly useful as it can help inform strategies to improve CX.
3. Make the case for customer centric strategies
Defining the best strategy to improve CX can be very challenging, especially when different departments within a company have several diverging priorities or goals that they need to achieve. Many industry experts in the marketing and optimization fields have a great deal of experience, but this also comes with bias and this can often hinder efforts to improve CX.
Having data that aligns to the brand’s north star metric and that indicates what website visitors are actually responding to can be the best weapon against conflicting opinions. It’s not subjective or influenced by bias, analytics simply tell the story as it is. It highlights what’s important to visitors as they’re browsing and what elements are progressing them further along the customer journey. Analytics can do a really good job at ensuring customer needs are being prioritized in strategies to improve CX.
With an increased focus on personalization and finding ways to create better connections with customers, being able to generate more relevant digital experiences is critical. Analytics, based on real website visitor responses can help brands understand their customers better. With AI-driven experimentation and personalization this becomes a possibility. AI learns from each unique response and builds on that learning to identify what the top performing experiences are. It can also show which ideas aren’t performing and pause these so that traffic is directed to top performing experiences in real-time. This advances the power of analytics to inform strategy and improve CX in production environments and with live visitors.
