## What is UX research?
UX research is the study of how users interact with your website and product. From the perspective of whether they have a “good experience” (in terms of both value and enjoyment) or not. It should be carried out continuously throughout a product’s lifecycle, not just at the beginning. You will ask why?

Because UX research helps to uncover what’s relevant for users. Identify the best ways to meet their needs; put proposed improvements to the test; and enable you to model and predict user behavior. Once you have collected these insights, you can make the improvements they point to.

## Types of UX research data
There are two big, overlapping fault lines running through the UX research field:

- quantitative versus qualitative research
- attitudinal versus behavioral research 



**Quantitative research data** looks at what users do and seeks patterns in this by analyzing user activity in bulk. Your analytics software provides you with quantitative data in this way, as do closed-question surveys, micro surveys, A/B tests, etc. 

**Qualitative research** is all about “why” users do the things they do. So while quantitative research may tell you what percentage of users who got to your checkout left without completing a transaction, qualitative research would tell you what caused them to leave.

As such, qualitative research typically involves much smaller samples: relevant methods include interviews, focus groups, surveys with open-ended questions, etc. 

Attitudinal research looks at users’ attitudes towards products or brands. It can combine quantitative insights (it can be done at scale and produce numerical results) as well as qualitative (by asking questions about opinions, feelings, loyalty, etc.) – tracking where and when [rage clicks](https://cux.io/blog/analytics/what-is-a-rage-clicks/) occur most frequently, for example.

Finally, behavioral research is again concerned with what users do in observational studies. However, it doesn’t have to be aggregated into numerical terms. Individual use patterns observed in usability tests, for example, would be behavioral research data without being quantitative. 

## What is product adoption?
Product adoption takes place when a customer decides that they are going to use your product. Product adoption occurs when customers decide that they will use your product. They find that it delivers the value they were looking for. Furthermore, that they will stop looking for alternatives. So, product adoption is different from new user acquisition, which is when someone decides to give your product a try for the first time. 

Product adoption matters because SaaS businesses make money through subscription revenue. The longer you retain a customer, the more money you will make. Users who have adopted your product are less likely to churn than others. Not only that, studies have shown that it is usually between [5 and 25 times more expensive to acquire new users than to keep existing ones](https://hbr.org/2014/10/the-value-of-keeping-the-right-customers) and that [increasing retention by 5% increases profit by between 25% and 95%](https://media.bain.com/Images/BB_Prescription_cutting_costs.pdf).

## How UX affects adoption at each stage of product adoption?
Product adoption doesn’t happen immediately out of anywhere. It’s a gradual process that includes several distinct stages. We’ve highlighted six – where the user’s needs, knowledge, and motivations are very different. At each touchpoint, UX affects users’ rates of progress towards adoption.

![Product Adoption Process](/uploads/Product_Adoption_Process_1_700x602_1161303649.png)

### UX and Awareness

A user has to know that your product exists and what it does before anything else! The experience the audience receives when they encounter your marketing has a huge impact in getting users to the Awareness stage. 

A good UX will cover making sure your product is discoverable by the right people (eg. that your website is well-optimized for relevant keywords; that the snippets that appear in search engine results pages are clear and accurate; that your ads are well-targeted; etc..). It will also ensure that visitors come away understanding the problem your product solves.

### UX and Interest

The second stage is “Interest” when a potential user starts seeking information about your product for themselves. To provide a good user experience here, you need to understand what different segments of users need to know. Moreover, help them find it with as little effort as possible. Most of this will take place on your website. However, they can also be conducted through earned media and social media. It’s important to ensure that the information and experience provided are consistent, wherever it is housed. 

### UX and Evaluation

At the “Evaluation” stage, users are weighing up the pros and cons of giving your product a try. Again, a good UX here is all about helping users accomplish that. So, your efforts should focus on communicating the best use cases. And also highlighting your strongest features, comparisons with competitors, and minimizing the perceived costs of testing your product out. 

### UX and Trial

When you have convinced a user to give your product a go – at the “Trial” stage – UX becomes even more important. Difficulties in signing up for a free trial, booking a demo, or confronting the user with confusing onboarding material can undermine all the good work done at earlier stages. 

### UX and Activation

This stage is missed out of many descriptions of the product adoption process. Nevertheless, we think it’s an essential step. Activated users have experienced the value your product promises for the first time. This is a key milestone along the way to long-term adoption. 

Your [user onboarding](https://userpilot.com/blog/interactive-walkthroughs-saas/) UX needs to focus on getting users to that point as quickly as possible (minimizing the Time To First Value KPI) and with minimal friction. It’s also important that users’ expectations of value are met: if you have created expectations your product doesn’t live up to, this is where it will be exposed!

### UX and Adoption

Finally! Now that a user has activated, the last stage is about convincing them that they need your product long-term. A good UX here is all about making it easy for users to realize more and more value from your product; resolving problems that they encounter quickly and smoothly; building up a relationship between users and your brand; and, on a more practical level, making it easy for users to pay.

## Applying UX research findings to product adoption
So, now you’ve seen some of how UX affects product adoption rates at each of the six stages, plus how many different types of UX research there are. The next question we’ll examine is how to go about carrying out the research which will tell you how to improve adoption.

### Define your UX research plan 

Any research is only as good as the questions you ask, and UX research is no exception. Your first step is to determine the questions you want the research to answer. These should always be “actionable” and “specific” questions: actionable in the sense that it’s clear how to go about answering it; and specific in that you will recognize the answer when you see it. In a research plan, the questions should be broad, breaking down into different subtasks or questions.

It is also important when devising your questions to decide who the stakeholders you will need to consult with are; what budget you have available; and – in particular – what the most appropriate research methods are answering the questions you have chosen. 

### Map the ideal customer journey to adoption

If the research plan casts a broad eye across product adoption, the next step is to get granular. What in practice, “counts” as a user reaching one of the product adoption stage milestones? And what specific actions you should take to reach this threshold? 

Work your way through your current marketing, sales, and onboarding funnels step-by-step: what will a potential customer need and feel at each touchpoint? What are the steps they need to take in each of those situations to make progress? 

Once you have mapped your ideal customer journey from total unawareness to adoption. Then you can start looking into the pain points where users are diverging from their ideal journey. And also begin fixing them. 

### Identify the pain points that block product adoption

When your analytics software is configured to show the numbers and percentages of users who are passing each touchpoint successfully, in line with the ideal journey, you can start to see what needs to be improved. It can be very useful to use visualization software – like cux.io in the example below – to build out a dashboard showing a “conversion waterfall”.

![CUX report](/uploads/cux_report_b394c4720c.png)

When you see a sharp drop-off, it’s a cue to dig deeper into what’s happening. You can get a lot of information with session recordings and heatmaps. Session recordings show what a single user was doing in real-time – and [our version records across different tabs](https://cux.io/features/#experience-metrics), to give you unparalleled insight into actual user behavior. Heatmaps aggregate this data to show patterns in where multiple users are hovering and clicking. This will give you some insight into why users are not completing the desired actions. But you can close the loop by asking the question directly. When a user abandons a task midway through, for example, use a triggered micro survey to ask why. The answers you get will build up to form an image of how you can improve the UX to improve task completion rates. 

Alternatively, at the end of a workflow, you could deploy a quick NPS survey. Thanks to this you can get a more general view of user satisfaction with the task as a whole.

![Userpilot nps survey](/uploads/userpilot_nps_survey_16b242a6f6.png)

A low level of NPS satisfaction will point to a need to probe further into the details of that task workflow! But this is not the only way to approach pain points. You could equally start with qualitative questions (in a survey, for example) and look for quantitative evidence that other users are experiencing the same issues. This is a great way of discovering problems that you were not aware of, and which you may not have configured your analytics to report on. 

### Drive feature discovery and adoption with different UI patterns

One sure-fire way to improve product adoption is to provide more and more value to users. Using in-app prompts and experiences to drive new feature adoption is an excellent way to do this. Not only does it add value for satisfied customers, but it may also win over unconvinced users. This refers to users who have been assigned to the wrong audience segment and would benefit more from a different onboarding focus. 

With an onboarding platform like Userpilot, for example, you can build out experiences that include lots of different UI elements – checklists, interactive walkthroughs, tooltips, modals, hotspots, etc. – to see which get the best user response. Alternatively, they can all be configured to be contextually triggered. Based on user segment, history, previous interactions, etc.

### A/B test solutions against one another

Combining your quantitative and qualitative research, you will have come up with various hypotheses about how to improve adoption. But how will you know if your proposed solution is better than what you had before? Simple: A/B testing. Split similar users into two groups: the first group gets the old workflow; the second, the new one. Track the relative performance of each group and you’ll see which gives the better UX. 

UX experiments of this kind depend on agility and responsiveness. It is important to be able to set them up and get them running fast. For that reason, it’s much better to use no-code applications for building your website, app, onboarding experiences, etc. This will allow your product team to create and run the experiments themselves, rather than waiting for developer time to write custom code. 

### Define the best product adoption metrics

Of course, what counts as product adoption will be specific to your product. However, there are some common metrics that most businesses use in this respect:

- Time To First Value (TTFV) – how quickly users go from trial to activation
- Customer Lifetime Value (CLV) – the average amount of revenue a user yields overall
- Product Activation Rate (PAR) – the percentage of users getting to the activation point
- Feature Adoption Rate – which as we’ve already mentioned is an excellent indicator of added value.


## Conclusion
Understanding what your customers struggle with and why enables you to optimize your marketing and sales funnels, as well as your user onboarding. As we’ve shown if UX research is applied in the right way, it can be a major driver of improved product adoption. If you ignore it, you’re leaving money on the table!


Ready to start your journey with smarter analytics and UX automation? Drop us a line at [team@cux.io](mailto:team@cux.io)! 

Want to harvest the freshest analytical crops? Sign up for the cux.io nourishing [newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b)! Be careful! We may grow on you! 🥑 😉

UX-reaserch-product-adoption.png

Conducting UX research will provide insights that you can then use to get more customers using your product more regularly. Also, getting more value from it once they do. Asking the right questions of users is key. With the answers you get, it’s very easy to devise solutions and improvements and to test their effectiveness. Whether it’s quantitative behavioral data or qualitative information about how they feel and what they think.


In this article, we’ll explain how, but before that, we need to define some of the concepts involved.

How to act on UX research to improve product adoption?

## 4 reasons why you don't need Session Replay Tools
### 1. You have no time for it
Let’s face it: no one has time to watch hundreds of thousands of videos of their users’ visits in session replay tools! It’s not a gripping thriller, but a tedious – quite often dry as dust – duty. The research shows that entrepreneurs can dedicate – with favorable conditions – about 5% of their time to the entire analytical process. And you want to tell me that someone will spend their 5% on binge-watching session replay of this one customer who was not able to get through to the checkout on their own? My eye!

>**Over half (57 percent) of marketers worldwide feel overwhelmed by the incoming data.**

The Brand Experience Playbook For 2021.

### 2. Sessions are not worth a cracker
If I’ve told you once, I’ve told you a thousand times: visits are a much more reliable analytical value than sessions! How come? The difference between a visit and a session (if we take into account web analytics) is enormous. A session is only a fragment of the user’s entire visit to the site. If we want our analysis to be complete and accurate, we need to take account of the whole visit. It may consist of many tabs (and each of these tabs will be a separate session) that the customer opens to compare the products or services we offer.

![Visits vs sessions ](/uploads/explainer_700x357_aef0a72718.png)
_<center>The difference between sessions and visits</center>_

Imagine that the user opens 7 tabs and then makes a final purchase. If you’ll be analyzing sessions – like most of the analytical tools do – you’ll be analyzing each tab separately. This may lead you to wrongly conclude that there are not one, but seven users, of whom only one made a purchase and the rest left our site without converting. Whilst analyzing all the tabs as components of one visit, you’ll have a full picture of what is happening on the site. You’ll see that this was only one customer who opened seven tabs just to compare products before making a purchase. The conversion for this analysis will be 100% (one customer = one finalization of the transaction). Since this is the best possible conversion rate, you don’t have to think about additional expenses for advertising campaigns or changes on the website.

### 3. Cognitive biases are inevitable
Until now, working with data in any organization very often consisted of randomly checking statistics, viewing occasionally selected visit recordings, and seeking support for your hypotheses. Possibly downloading ready-made reports for presentation to the boss at the end of the month. Of course, this has nothing to do with being data-driven! Data collection is only 1/3 of the success. You need to be able to combine information to check if hypotheses are correct and to deepen them. To do this, while avoiding cognitive biases, you must create an articulate and comprehensive analytical strategy of the company.

The session replay tools provide crude figures, not conclusions. So it’s up to you to make sense of the numbers and translate them into business recommendations. And this is a truly friendly environment for most cognitive biases to appear.

The most common cognitive biases in analytics are:

- **IKEA EFFECT** – overestimating the things we have done ourselves,
- **STREET LIGHT EFFECT** – searching for information in places known, easy and accessible,
- **CONFIRMATION BIAS** – looking for information that confirms our initial hypotheses,
- **SELECTIVE PERCEPTION** – how we interpret data largely depends on our expectations.


### 4. You can automate your work
If you can measure something, you can optimize it! So why waste time (and often nerves – you won’t fool us) on single-handed and tedious data analysis when you can use tools that will do it for you?

CUX is the first and only UX Automation platform in the world. This means that it will recognize, detect and define the behavioral patterns of your users by itself. Then the tool will show you how those experiences influence UX regarding your business goals. As a result, you’ll get hard-to-understand emotions converted into easily approachable metrics.

![Experience Metrics in cux.io](/uploads/Experience_Metrics_700x425_054457ae43.png)

_<center>CUX recognizes, detects, and defines the behavioural patterns of your users. Then shows you how it influences UX regarding your business goals. The tool also converts hard-to-understand emotions into easily approachable metrics</center>_

#### Data analysis automation that CUX will carry out for you:

- CUX will select recordings and [heatmaps](https://cux.io/blog/analytics/how-to-read-a-heatmap-part-1/) from visits that meet your goals (sales, purchase intention, newsletter subscription, form filling, document download, etc.). You don’t have to watch all the recordings anymore!
- CUX will [track user frustrations](https://cux.io/features/#experience-metrics) and alert you when they reach a disturbing level. You don’t have to keep an eye on your data!
- CUX will prepare quick [segments](https://cux.io/blog/product/walkthrough/user-segmentation-cux/) for you that you can use to filter your data. You can also create your filters and save them into segments – so you will be able to come back to them at any time.
- CUX works retroactively, which means you can return to your data at any time and perform analysis even on historical data.
- CUX autocaptures events on your site. You don’t have to code each of them separately!


Ready to start your journey with smarter analytics and UX automation? Drop us a line at [team@cux.io](mailto:team@cux.io)! 

Want to harvest the freshest analytical crops? Sign up for the cux.io nourishing [newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b)! Be careful! We may grow on you! 🥑 😉

session-replay-tools.png

A while ago, we came across the article “X Reasons Why You Need Session Replay Tools”. And we have only one thing to say: bull! 

4 reasons you DON’T need session replay tools

Correctly read heatmap is able to show you the exact history of activity on your website. Thanks to it, you’ll find out where exactly people clicked and where they didn’t click, even though you wanted them to. Do they click on things that aren’t linking? Do they click in anger or frustration? You will see which links are not working, and identify places where the links should appear (the so-called dead clicks).

When you look at a heatmap, don’t take anything for granted! What you see is a generalized view of the user’s activities. To see more details and analyze specific scenarios, you’ll have to dig into the settings. Look for new points of view, find specific segments. And I’m here to tell you how to do it.

![Heatmap CUX](/uploads/Screenshot_2020_10_21_at_12_24_34_700x405_1_4b6a256ac6.png)

_<center>Heatmap in CUX</center>_

## Heatmap ≠ Linkmap
When you read a heatmap remember: a heatmap is always static. Some tools scrape the page (i.e. extract data from web pages) immediately after connecting the code. Others, such as CUX, display the latest recorded view in the heatmap preview. This is especially important for the timeliness and accuracy of the collected data on user behavior.

Remember that the heatmap applies to all clicks on the page – regardless of their severity and location. Heatmaps where you can see that users click and hit the buttons perfectly are probably linkmaps. Linkmaps exclude any clicks that are not clicks on links to other subpages, and therefore cannot provide you with a complete picture of user behavior.

## Pop-ups, widgets, drop-down menus
If your website has multiple states – that may be an analytical problem. All clicks and interactions with pop-ups, widgets or hovers appearing on your website will be extremely important for user behavior analysis. Unfortunately, if they don’t generate separate URLs, you won’t see a separate heatmap for them.

When analyzing a heatmap and seeing clicks “floating in the air”, consider whether these are the places with additional content appearing. Like pop-ups, widgets or drop-down menus. While you won’t see them on the heatmap, remember that they have great analytical value! They’ll tell you a lot about what the users are facing.

## Tracking campaign traffic
Do you run an online business? You certainly drive traffic to your website from paid campaigns or social media. But are you following that movement properly on your heatmaps?

Remember that each redirection from external sources “attaches” a piece of text to your address. For users coming from Facebook it will be _fbclid_, for clicks from Google it will be _gclid_. If you have many campaigns or social media inputs, a heatmap for a single URL is not enough. In such a case, it is worth registering all URLs in heatmaps and using the [“grouped heatmap”](https://cux.io/blog/analytics/grouped-heatmaps/) function. We used it with great results while [optimizing the Valentine’s Day campaign for aniakruk.pl.](https://cux.io/blog/use-case/valentines-campaign-analysis-aniakruk-case/)


![aniakruk.pl heatmap CUX](/uploads/Ania_Kruk_case_5_700x392_1_a1303345c1.png)

_<center> Grouped heatmap for campaign traffic in cux.io (for rage clicks) </center>_

## Logging frustration
No matter how much time you devoted to designing your perfect website or product – user frustration is a phenomenon that you will definitely encounter! Tracking user behavior patterns, the so-called [Experience Metrics](https://cux.io/features/#experience-metrics) allows you to catch negative emotions before they turn into serious problems that threaten to decrease conversions.

Heatmaps are the perfect solution here. If read correctly, they can become a source of knowledge about users’ frustrations. Imagine a situation where some page element has many more clicks than your CTA (Call to Action). This is not a proof of its popularity, but most often of its problems. It may turn out that users cannot click on it. Thus, they increase the traffic in its area, which is distinguished by red on our heatmap. Heatmaps of [rage clicks](https://cux.io/blog/analytics/what-is-a-rage-clicks/) will also be useful in tracking frustration.


Ready to start your journey with smarter analytics and UX automation? Drop us a line at [team@cux.io](mailto:team@cux.io)! 

Want to harvest the freshest analytical crops? Sign up for the cux.io nourishing [newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b)! Be careful! We may grow on you! 🥑 😉

How-to-read-heatmaps.png

Heatmaps are graphic representations of the most important activities of users on your pages. Any action, such as clicking or moving the mouse, increases the attractiveness of the heatmap area by making it “warmer”. Places where users click frequently are red. The places where users click less often are blue and green. Simple? Not exactly! Heatmaps are real goldmines of knowledge about users, which, unfortunately, we often cannot decipher. So how to read your heatmap?

How to read a heatmap? Part 2


## What is a heatmap?

As you probably know, a heatmap graphically shows users’ most significant actions on your pages.  Every single activity – like a click or mouse move, scroll, chaotic movement – adds to the hotness of a given area. The places where users click most often are marked as hot areas (yellow, orange, red). The places where users click less often are shown as cold (blue and green). Any areas without colors are the places where there’s no user action.

<center><iframe src="https://giphy.com/embed/5wFkqt6A8R4qAqGIFQ" width="480" height="270" frameBorder="0" class="giphy-embed" allowFullScreen></iframe><p><a href="https://giphy.com/gifs/abcnetwork-modern-family-eric-stonestreet-jesse-tyler-ferguson-5wFkqt6A8R4qAqGIFQ">via GIPHY</a></p></center>

## What heatmap is trying to tell me?
In CUX heatmaps can show you the most valuable things that happen on your website. Like places here people click or don’t click (but were supposed to click). Phrases that users clicked on thinking that they’re links. Anger and frustrated clicks. You can also use heatmaps for debugging your website. For example, you’ll be able to spot clicks on broken links or missed opportunities to have links (dead clicks).

## How to read a heatmap?
There is a one simple rule for you to follow: don’t take anything for granted. Working with heatmaps require a bit of time and commitment. Heatmaps, by default, show a generalized, summary view of user actions. To see more details and analyze specific use scenarios, you need to change heatmap settings.

**You can for example:**

- change the type of device for which the image is displayed (desktop, mobile, tablet, smart TV, console, wearable, embedded browsers),
- check out images for different types of events (clicks, [rage clicks](https://cux.io/blog/analytics/what-is-a-rage-clicks/), mouse movements),
- set time intervals that interest you,
- change page resolutions,
- examine single or [grouped heatmaps](https://cux.io/knowledge-base/heatmaps/what-are-grouped-heatmaps/).

![Heatmap CUX](/uploads/heatmap1_700x333_e430c61515.png)

_<center> Adjust heatmap to your analytical needs </center>_

>The default heatmap view in CUX is the desktop view. If you need a pixel perfect view you should select a required resolution in heatmap settings. You can start by finding out which screen resolutions are the most frequently used by your site visitors. Next, adjust the CUX heatmap settings to see what happens when people see your pages using this resolution.

## See better, know more from CUXs' heatmap
You can use an advanced filtering option for a better insight into heatmaps. Play with opacity – increase and decrease the transparency of hot areas to adjust visibility. Change intensity to find precise user activity points. Increase **intensity** to see exact click points if your page generates a lot of events. Decrease it to see specific places if you’ve fewer events. Play with spread to focus on single areas (low **spread** for high traffic pages, high for low traffic pages).

![Heatmap cux.io ](/uploads/advanced_700x333_90e2941150.png)

_<center> Advanced options to read a heatmap </center>_

## Why does a heatmap look messy?
It’s all about precision. If you’re looking at a nice heatmap with even borders you’re probably the victim of overgeneralization. Need an example? Let’s say you have a button on a page. The overgeneralized heatmap will show you clicks at the very center of it. But in reality the button rarely attract the mouse cursor to their center.

![Grouped Heatmaps in cux.io](/uploads/Grouped_Heatmap_main_1_700x359_1993e23ba9.png)

_<center> When you read a heatmap you’ll rarely see even borders </center>_

In CUX we’d rather our heatmaps to look messy and at the same time show you specific clicks. The exact clicked places. The right birthplaces of your user’s frustrations. And – thanks to this untidiness – a whole new level of understanding your customers.

## Making heatmap-based decisions
When people cannot access page elements, they won’t use them. If this concerns the “Buy now” button, it would be a bummer, wouldn’t it? Can you afford not to know that your conversion call-to-action doesn’t work? Probably not! Keep an eye out for heatmaps showing a button that often gets clicked close to its edges or on one side only. Think if this is an indication that you should change the element placement on the page.

Examine if numerous clicks on text are related to copying text. The most obvious indicators are clicks before a piece of text, for example, at the beginning of a line. This often happens for emails that aren’t active links, promo codes or street addresses. If that’s the case for you – try to make it easier for users to copy the text. Perhaps highlighting content is not about non-copyable elements, but simply visibility problems? Maybe you used too little contrast font that is invisible to users?

It sometimes happens that even images that aren’t linked receive clicks. Think of this as an unrivalled opportunity. Let’s say you have a fashion e-commerce. One day you find out that a static photo on a product page gets clicks. Where do the visitors click? Is this a watch, a bracelet, or a cardigan that is clicked. If you have it in stock, you’ve just found an excellent opportunity to cross-sell your products!

## Mind the traps!
That may come as a surprise to you but heatmaps don’t show any dynamic elements! They’re always static snapshots of your page. That’s why you won’t be able to see elements like: pop-ups, tooltips, modal windows or drop-downs. However, we’ll show clicks that those elements received.

![Heatmap CUX](/uploads/Ania_Kruk_case_4_700x401_1_73341482c8.png)

_<center> If you read this heatmap you’ll see clicks on the menu bar after its expansion </center>_

When you see unexpected hot areas, think if a dynamic or temporary page element appears there. Do not mislead those areas as rage clicks. Our algorithms understand your page behavior and can distinguish clicking on a dynamic page element and angry behavior.


Ready to start your journey with smarter analytics and UX automation? Drop us a line at [team@cux.io](mailto:team@cux.io)! 

Want to harvest the freshest analytical crops? Sign up for the cux.io nourishing [newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b)! Be careful! We may grow on you! 🥑 😉

Blog-post-Recenzje-Partner-LP-31-700x394.png

People get hot about some things on your website. And they are totally cold about other stuff. Frustrations, chaotic movements, problems and solutions – that’s all you can spot on a heatmap. But in order to make it a goldmine of user’s insights, you have to know how to properly read a heatmap.

How to read a heatmap? Part 1


>**Researcher’s comment:** when I think about feedback from clients I frequently come back to a, clichéd in the UX context yet very accurate quote by Henry Ford: “If at the beginning of my career as an entrepreneur I had asked clients what they wanted, they would have said faster horses. So I never asked.” Luckily, observing people in their natural environment provides us with an opportunity to learn the most about their real behavior. If there is such an opportunity, why not use it?

## What value does observing users provide? Why and when should you do it?

It’s pretty obvious that most time and money required for the development of a product is invested during the pre-production phase. But usually it’s a shot in the dark, as there is never a 100% certainty about how the market will respond. Below, you’ll find out when and what you should check in order to minimize the risk of designing a useless product.

### 1. Prototyping/creating mock-ups - save some time! 

An idea is sprouting up in your head, you have a clear vision of what you want to accomplish and to what need of the market you want to respond, but what you lack is the validation from the potential users. That’s why, when you are creating mock-ups, you should confront your current ideas with potential users – thanks to that you will save time by introducing corrections before designing and coding your project.

> **Programmer’s comment:** when you show your team who they’re designing for, and how people actually use their product, it will allow them to save time and energy. This is because they will be able to see the real problems, which can usually be solved quickly. I know from my experience that it will boost team’s level of engagement and can solve a frequent problem: software developers and designers don’t understand project manager’s vision and get into disputes.

Obviously, when you create mock-ups not all details are polished, but you can definitely observe a few things:

- How users move around and use the functionalities you’ve proposed,
- Whether they search for information or CTAs where you located them, or are ignoring them,
- How the traffic on the website looks – whether the planned information architecture of the service is intuitive,
- whether the direction of development you’re headed is the right one or maybe you should introduce a small change that would better respond to customer needs.


At this point, a good solution is to give your users a, so called, free hand. Let them use their own computers so they’re not distracted, are not trying to be polite, or prove that “of course that you have a great product!” People, when tested, tend to act as if they were experts and accommodate to potential expectations. On the other hand, sticking to specific scenarios narrows down the way of using a product to what you imagine. And who knows how it might actually be utilized by users?

### 2. Redesign of existing product/website - leverage accumulated data! 

Yet another situation is the moment when the website advertising your product or service needs a redesign. This is a much simpler situation. Based on previous user behavior you are able to, for example, diagnose current problems or define the aim of the visit on the website. Very often, during workshops or interviews with clients, we come across a statement that they intentionally don’t test user behavior because the website will be redesigned anyway and there is no point in testing it. That’s a mistake! If you’re not planning to change line or character of your business, this is the perfect moment for testing:

- What your users interacted with so far?
- What are they not interested in the least?
- What draws their attention?
- What is causing problems for them?


Translating your observations into business goals will allow you to eliminate irrelevant content from your website, simplify user flow, and drop inessential features. You can knowingly build a new, much more usable website, not relying on your intuition and current trends, but on data.

### 3. Testing – how does the product fall when interacting with users.

In an ideal workflow, even if it has not been possible before, the moment for testing always comes. Usually, this is the first moment when, after hours of project team’s work, the product meets users. Then, you might come across a problem where to find testers. If you have a budget and time, the best option is to hire an agency for [UX research](https://uxstudioteam.com/ux-agency/). But let’s be honest – very often, there are no resources for that. Many UXers use opinions of their colleagues from different departments as support, which does not convey the real picture of how users will deal with the product.Researcher’s comment: to be clear, I’ve got nothing against hallway testing, it often is a good solution to quickly verify your idea. But it can’t be a replacement for confronting the idea with those who will actually be using our product. Especially at this stage.

#### The tools for observing users online allow you to:

1. Acquire hard evidence (concrete data, for example in the form of heat maps, will act as a perfect argument for the decision makers),
2. Conduct research even with a very tight budget and little time,
3. Conduct remote testing,
4. Enrich tests with users’ natural reactions and behavior,
5. Avoid the situation when your colleagues play the role of potential clients.

These are of course only some of the advantages that observing users give you. In the era of client-centric approach, and from a business point of view, it’s always good to know as much as possible about your users. It’s also important to be aware that you don’t have to be an analyst in order to start observing your users. You just need to know which tools you should use.

Originally published in polish [here](https://mamstartup.pl/produkt/11903/kiedy-badac-uzytkownikow-i-na-co-zwrocic-uwage-na-poszczegolnych-etapach-czesc-1). 

Translation: Magdalena Sobieszuk

Observing your users before the production phase

Observing-users-before-the-production-phase.png

Everyone who works on projects knows that in the IT industry there’s no such thing as a finished product. There are various reasons: sales is not going as you’ve expected, you don’t like some things, or your clients tell you to introduce some changes. The latter is a dream situation because you’re assured that what you change will meet their needs and usability requirements. However, you shouldn’t count on all of your users to give you feedback, let alone constructive one.