Digital Products, The study of data collected by tools such as Google Analytics is associated with digital marketing and search engine positioning (SEO) strategies. However, the analysis of these metrics is valuable to maintain a healthy user experience in a digital product, whether it is a website, an e-commerce portal, a mobile app, etc.
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Why Measure?
UX (User Experience) design includes a series of techniques to ensure that the user has an experience aligned with their wants and needs and, at the same time. With the objectives and purposes of our business.
That’s why we talk about the UX umbrella, which Dan Willis sums up like this:
Experience designers turn to measurement in the different phases of product life, research, organization, design and testing. The data helps us locate problems. After applying a solution, we can rely on them to validate the measures taken. Corroborate if they convert better after the change, and otherwise iterate, adapting the process to agile development methodologies.
By focusing the analysis on concrete actions, we will ensure that the motion applied is optimal for our evaluated objective.
Tools to Optimize the UX of our Digital Product
On the network, there are multiple tools to collect metrics of the use of a digital product. To work with this data. It is necessary to install the instrument well in advance to obtain a good volume of information and thus be compared and analyzed.
To improve usability, we will start by measuring user behavior quantitatively, a functionality present in almost all tools of this type.
With the information analyzed, you can locate the problem and solve it. However. It is challenging to recognize why the user, for example, did not finish a goal. Analytics provides measurable data, but to know why it is necessary to resort to other techniques that provide qualitative information such as heuristic analysis or working directly with the user through interviews, face-to-face tests, surveys of mental models …
Here are some of the tools to measure and value UX:
- Google Analytics
- Flurry Analytics de Yahoo
- Kissmetrics
- Piwik
- Crazy Egg
- Adobe Marketing Cloud
The different analyses that we will make of the metrics obtained with these tools will allow us to understand the users and their behavior better. This will help us make the necessary adjustments to the products and services to optimize them and thus offer a better user experience.
What does Google Analytics give us to optimize UX?
- Helpful information to Create Buyer Personas
- Know how the user accesses the product
- How it behaves in the product (click path, bounce rate, time spent performing a task, tracking events…)
- Navigation flows
- Tests AB
- Measuring the effects of changes
Data also justify UX Success
As we have already seen, the information collected by the tool allows to locate problems in the product and serves to measure the success of the UX consultant after his work.
Google Analytics offers us the possibility to compare different periods .Moreover From a glance, we can see the before and after the applied change:
The ROI (Return on Investment) is a project that can be measured in two ways: through revenue generated and user satisfaction.
- Increased revenue
- Greater contracting of services
- Increased productivity
- Increase in contacts
- Decreased bounce rate
- Fewer errors
- Decrease in complaints
- Increased positive feedback
Moreover, There is a crucial point in the valuation of ROI. In many cases. The UX specialist begins his work after identifying a problem by the company. Above all. This translates into a higher cost than if he were available from the beginning since the estimates are more accurate if they are studied from the start. The price is reduced in corrections and redesign of the components. Not to mention all the frustration of recording and going through all production environments again at each modification.
However, UX design is not merely an aesthetic issue but focuses on solving problems. Its optimization will positively revert to the business results, and this can only be done if we trust the data and bet on measurement and constant analysis