We live in a world in which more and more data is available. That data can help companies understand how their product or service is being used in ‘the real world’. It allows us to make informed decisions on what and how to improve next.

We work a lot with product owners and alike who are responsible for such decisions. What we often see is that they focus on only a subset of data, mainly analytics and call center data. Although this information is important, it doesn’t tell the whole story. Product owners could benefit from other data that would expand their understanding of the real world and make better data-driven decisions.

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Sailing with blinders on

We like to use the metaphor of product owners sailing on the agile sea with the quest to maximize the value of the next product improvement. However, they are unaware they are wearing blinders that don’t allow them to see the bigger picture and make more effective decisions on how to reach their goal.

While we’ll never be able to totally get rid of the eye patch and get a full understanding of the real world, collecting what and why data as part of the Experience Management (XM) framework is a way to get closer. In this article, we’ll cover what 'what' and 'why' data is, how it's beneficial to you to make better data-driven decisions, how to make the best use of the data through an XM framework and how an XM platform can bring this to the next level. 

Experience Management (XM) is the process of monitoring every interaction customers experience with a company to define data-driven insights and opportunities and continuously improve products and/or services enabled by a user-centric organization. 

What and why data

What data will tell about what is happening and give an understanding of the size it is happening in. It shows the overall behavior of customers, hence also called behavioral data. For example, “What is the user flow like on this website?” or “What products sell well?”

What data can be collected from sources such as analytics, commerce, marketing, sales, supply chain, customer support, et cetera. This data can then, for example, show which pages on your website drive the most traffic or which product features are frequently used.

Most companies already collect a lot of what data but only little why data. That's odd as the why data is so important to understand why things are happening in the what data. That's where attitudinal data comes into play. Attitudinal data is data that shows a customer’s attitude toward products and services offered. “Why do customers like this feature?” or “Why don’t they understand this functionality?”

These kinds of data can be gathered in the form of ad hoc feedback, surveys (like NPS, customer satisfaction, effort score), comments on social media, in-depth interviews, focus groups, online reviews, and more. These data then help you to understand why customers are satisfied or not and, thus, provide a direction on how to tackle an issue. For example, when an NPS score shows a decline, you can analyze the open text questions from the NPS survey to discover what topics play a role in this.

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Combining what and why data

When you look at what and why data separately, it can bring you valuable insights that you can act upon. The value of the data is, however, amplified when they are combined. When, for example, analytics show that the biggest drop-off in the commerce journey is in the checkout flow, you can analyze the why data to see why they are dropping off. It might be the case that customers are missing a new type of payment method.

So, combining what and why data can show you where you can have the most impact and indicate what to tackle in order to fix it. Some examples of combining what and why data:

 What data

Why data

Action

Impact

 High bounce rate on   the home page

“Couldn’t easily find the search bar so left”

Improve findability of search

Increase site traffic

 The new product isn’t   selling as expected

“The product pictures aren’t clear enough”        

Improve product pictures

Increase sales conversion

 High cart   abandonment

“Unexpected shipping costs”

Investigate how to inform users better

Decrease cart abandonment

What why and why data to collect

It’s easy to get lost in the sea of data and not know where to start. Deciding upfront what you want to know and why is then essential.

Imagine an organization where there's no or little data collection, we’d start by looking at the key customer journeys and define those important touchpoints. Based on those goals and KPIs, we’d map out per touchpoint which 'why data' we'd want to collect and how. For example, by sending out a satisfaction survey after a purchase to understand which aspects of the journey went well or not.

Along with this, we'd define which 'what data' would be valuable to collect to gain deeper insight into the context. This is an ongoing process where you should add, adjust or remove data collection moments based on what you measure and learn to keep improving your view of the real world.

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Figure: Experience Management framework

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XM framework

So, when your company gathers the right what and why data, all problems will be solved? No. Taking the right actions based on your data is just as important. An XM framework will help you here, making sure you ‘close the loop’.

An XM framework is successful if it creates a loop that:

  1. Measures and collects data on how your operational product/service performs.
  2. Understands what is happening to derive insights and uses design thinking to ideate.
  3. Designs the final solution in an agile approach to continuously deliver improvements and innovations.

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Using what and why data with an XM platform

A way to streamline the data collection and understanding as shown in the figure is to leverage an XM platform. In general, they allow to collect and combine what and why data to generate insights and act on them to close the loop.

XM platforms can collect why data by, for example, sending out surveys via different channels, placing feedback tabs on websites to ask about the experience, or scraping comments from customers on social media. The what data is usually already collected by other platforms, so most XM platforms allow you to combine the what and why data into one overview.

These platforms then help you drive insights from the collected data. This can be done with functionalities like dashboards, to visualize the data and drill down where necessary, or advanced text analysis, to analyze vast amounts of feedback, and discover what topics are mentioned and what sentiment is attached. And when the right data is available, XM platforms not only analyze what happened but also make a forecast, for example, by calculating the churn probability of a customer.

To help close the loop, these platforms are also capable of notifying employees about changes and updates in the analyzed experience so they can take action.

Your next move

While we'll never be able to capture the entire ‘real world’ in data, collecting the right what and why data in an XM framework and supported with an XM platform will get you a big step closer to reality. It will help you to remove that eye patch to see more and provide a map with more guidance to make better and data-driven decisions.

If you have any questions, want to chat about this topic, or want to learn more, let us know!

Contact details

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Tu Ngo

Senior Manager - Accenture Interactive, Experience Management Lead, the Netherlands

Theo Enzing

Consultant - Accenture Interactive, Experience Management

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Learn more about what we can do for you by browsing our work and capabilities, or dive deeper into our thinking

Tu Ngo

Senior Manager – Accenture Interactive, Experience Platforms, the Netherlands


Theo Enzing

UX Manager – Accenture Interactive, The Netherlands

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