Strengths & Weaknesses of 7 Metrics Used to Evaluate Digital Experiences

Liam Burns
Written by Liam Burns
June 17, 2020

At the enterprise level, the success of your website or app depends on your ability to continually measure and optimize digital experiences. Companies that prioritize and effectively manage customer experiences are 3x more likely than their peers to blow away their top business goals, increasing conversions, engagement, and loyalty.

As an analyst or optimizer, you know it’s crucial to establish a metric as your key performance indicator (KPI) to effectively monitor and measure UX performance across your website or app. Similar to a car’s ‘check engine light’ warning the driver of required maintenance, your KPI will indicate critical times to implement optimizations to improve user experiences.

The question is, which metric is best suited to be used as a KPI to measure the quality of customer experiences on your website or app?

In our survey report with Econsultancy, over 300 companies were asked to indicate the metrics they find most effective for measuring online experiences and the results yielded 11 highly popular metrics. We’ve identified 7 of the most relevant metrics listed to consider as your KPI based on their industry popularity, along with key functional strengths and weaknesses:

1. Customer Satisfaction Score (CSAT)

Usage rate: 58%

Among the most-used customer experience metrics, CSAT allows you to determine the general levels of customer satisfaction behind your customer experiences. As it translates to digital experiences, teams can analyze which customer journeys correlate with positive versus negative scoring feedback and investigate accordingly.

While you can make connections between feedback and experiences, this data is subjectively based on customer opinions and fails to link to specific experiences affecting scores. This limits optimizers from changing nuanced issues like a clunky user interface undermining engagements and lowering CSAT scores.

2. Repeat visits

Usage rate: 53%

Repeat visits are nearly always a positive sign as you can identify the positive customer experiences and journeys prompting those reoccurring user sessions. From here you discover overlapping patterns between journeys, and you can try to replicate those experiences within other journeys that resulted in abandonment.

However, web analysts cannot easily pinpoint whether experiences versus other buying factors promote these repeat visits. Without certainty, optimizing experiences using this data could backfire if the patterns deduced are just coincidental rather than real trends behind user experiences.

3. Conversion rate

Usage rate: 49%

Conversion rates highlight your success at convincing customers to complete an intended call to action – whether it’s a sale at checkout or signing up for a new bank account. This enables you to understand which types of experiences drive more conversions, then aim to recreate them across all user journeys.

Unfortunately, too many variables like price and selection affect purchasing decisions, which makes conversion-based experience data highly unreliable. Perhaps you have several popular products that create so much demand it supersedes possible experience issues embedded within those website or app experiences.

4. Retention rate

Usage rate: 46%

Retention rates allow you to track the journeys of retained and churned customers. With these journeys divided, you can categorize user experiences by their ability to maintain and boost customer loyalty versus those causing frustration and lost customers.

Like conversion rates, there are several purchasing factors beyond user experience that impact retention, which makes this data inconclusive. Without insights definitively pointing to something like a seamless account user experiences that keeps customers loyal, your team will be forced to guess which elements of the user journey work versus don’t.

5. Time on site

Usage rate: 39%

A user’s time on site allows you to measure experiences leading to longer versus shorter sessions. These differing session times indicate how certain experiences impact a user’s time on site, and you can dig into session lengths that don’t match the expected time on site for each journey.

In most cases, time on site data is more descriptive of user sessions rather than prescriptive for new optimizations. For instance, a short session could mean a user found the product they needed immediately, or that missing landing page content forced the user to bounce early – time is not necessarily tied to quality.

6. Net Promoter Score (NPS)

Usage rate: 28%

A notable industry favorite, NPS gauges experience quality through the likelihood of customer referrals. With NPS, you can determine which journeys generated high-loyalty customers, and further investigate experiences to find key touchpoints that supported and promoted those positive results.

The key flaw here lies in broad scoring data failing to indicate detailed experiences impacting customer loyalty. This forces web analysts to make tedious correlations and estimations based on this data, which makes website or app optimizations imprecise.

7. Digital Experience Score (DXS)

The core pitfall of the customer experience metrics listed so far emanates from a lack of definitive data that pinpoints the key experiences impacting your results. This uncertainty will limit the success of your optimization program.

To reveal the unknowns of your user experiences, Decibel created the Digital Experience Score (DXS): a holistic metric that automatically measures online experiences and identifies poor experiences impacting results.

What separates DXS from a typical customer experience metric?

  • Powered by AI for enterprise scalability and efficiency
  • Automatically crunches millions of data points and scores quality from 1-10
  • Tracks user behaviors indicating frustration or engagement
  • Measures 5 pillars of experience data like navigation and technical experiences
  • Trusted by major global brands like Adidas and Fidelity

Leader of Global Ecommerce Shopper Experience at LEGO, Tim Murphy highlights that “with DXS we finally have a quantifiable score that can be easily communicated to all levels of the company – from C-level down to the developers.” Using DXS, you can definitively quantify the quality of user experiences and predict conversions at the enterprise level without any second-guessing.

Implement & Follow a Simple Process for Optimizing Digital Experiences

With the pros and cons of every metric laid out, your team can align on one and establish a clear view of how user experiences are performing across your website or app.

However, it takes more than a benchmarking KPI to roll out highly successful improvements that will move the needle on engagements, conversions, and more. In fact, 70% of CX leaders said they struggle to design projects that increase customer loyalty and achieve results.

To successfully manage and optimize your website or app, download The Ultimate Guide to Optimizing Digital Experiences for Enterprise, which introduces a simple 4-phase process for delivering near perfect user experiences.

Topics: Analytics, Data, DXS, Website Performance
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