In June 2021, Paulina Walkowiak – CEO of cux.io – was invited by the Swedish brand Prisjakt to run a webinar about data-driven organizations. Finally, the conclusions from the webinar turned into cooperation on the analysis and improvement of their business core – price comparison.

![Timeline of work on the Prisjakt case](/uploads/Building_analytical_strategy_defining_KP_Is_workshop_1536x768_d85466881a.png)

_<center>Work timeline – from data-driven webinar to internal analytical strategy</center>_

## Webinar: Developing a data-driven culture

During a webinar for Prisjakt, Paulina explained how to introduce and develop a data-driven culture. Moreover, how important it is to constantly learn and look for new ways to manage and use data. Intrigued by the data-driven concept, Prisjakt decided to explore the topic even further. A custom webinar turned out into a dedicated workshop. It focused on building an internal analytical strategy and defining meaningful KPIs. 

>_Paulina helped us with analyzing the data and explained which metrics can be significant. She gave us many tips and ideas on where to focus now and in the future. With CUX implemented, we were able to find issues and users’ pain points quickly and efficiently. The whole process was pleasant and intuitive, thus it gave a lot of satisfaction._

**- Kinga Słabowska**, Content Development Specialist at Prisjakt

![Data-Driven Businesses 2022](/uploads/prisjakt_prez_slajd_1536x861_b818081035.png)

_<center>source: https://blogs.gartner.com/andrew_white/2019/01/03/our-top-data-and-analytics-predicts-for-2019/</center>_

## Workshop: Building analytical strategy 
The personalized workshop agenda aimed to help the content team use data more effectively. In fact, the goal was to apply an analytics strategy in their department. Hence, a 30-person team, divided into 2 groups, worked together on common tasks for 2 days. The tasks included:

- defining business and analytical [Goals](https://cux.io/blog/analytics/analytics-goals-cux/),
- searching for the most effective KPIs and metrics,
- building the company’s analytics stack and qualitative data.

In conclusion, teams identified the most business-relevant touchpoints in the [user journey](https://cux.io/blog/analytics/optimize-customer-journey/). They’ve built data-driven dashboards. Therefore, this allowed them to better understand user behavior. 
![Photo of workshop with Paulina Walkowiak](/uploads/IMG_0546_1536x1152_d490c5ef0b.jpeg)

_<center>Data-driven design workshop which Paulina Walkowiak conducted for the Prisjakt team</center>_

## Building Content Visibility Strategy 

Prisjakt’s main goal was to define user scenarios in one segment. This was in order to automate the process for every other product segment. Also, to create KPIs and metrics to help monitor content’s effectiveness for each user group in real-time. They’ve decided to use UX automation to map users’ reality, instead of relying on classic methods and defining the strategy hypothetically.

The webinar and workshop arrived at the perfect time to use this knowledge in an internal Content Visibility Strategy project. To support the project with user-related data, CUX was implemented within the organization. As always, the GDPR-issues were to be addressed beforehand. 

>_It took Prisjakt over a month to establish a GDPR-secure process. We also had to make sure that all sensitive data that users can insert on our page will be hidden and excluded from scanning in CUX. A couple of improvements in Prisjakt’s code ended with securing this aspect as well._

**- Natalia Sroka**, Content Development Specialist at Prisjakt

With technicalities resolved, there were still a few matters to settle. It needed to be established whether CUX’s data would be consistent with what Prisjakt gathered so far. And, most importantly, if CUX would help detect pain points during the user’s journey. Issues that proved to be unfounded. 

![CUX security implementation info](/uploads/Projekt_bez_tytulu_2_2c07f89a1b.png)

_<center>CUX security implementation info</center>_

A protracted legal work, left the team with limited time to complete the project. Working with Paulina Walkowiak as a consultant and implementing CUX proved crucial in meeting the deadline. Therefore, the project, estimated to take a month, was completed in one week. On the whole, the team was able to present insights and conclusions from their work with CUX on the Content Visibility Strategy at the Demo Day to the stakeholders. Thanks to the usage of CUX, previously overlooked user pain points have been uncovered. Moreover, it was possible to define a user persona based not only on demographics but also on behavioral data. Parts of the user journey that relate to other segments were defined. As a result, it was possible to divide the analytical flow. 

Consequently, behavioral analytics has proven to be the missing piece of data for internal metrics that focus on the product dimension of their business.

## From webinar to close collaboration

![Paulina Walkowiak working with Prisjakt team](/uploads/IMG_0513_2_d758983981.jpeg)

_<center>A personalized webinar and workshop with Paulina Walkowiak lead to building an internal analytical strategy.</center>_

Both a webinar and workshops conducted by Paulina Walkowiak, CUX’s CEO, showed Prisjakt how valuable it is to develop a data-driven culture within an organization. The implementation of CUX and Paulina’s support resulted in close companies’ cooperation. Not only did it allow the Swedish brand to grow faster and more efficiently. It also helped to implement CUX in the Polish department. What is more, it can be now integrated into the whole analytical strategy.

>_Our entire journey – from webinar to working with CUX – was filled with unpredictable twists. The team’s determination implementing what we’ve learned and introducing it into the company yielded great results. On this path, Paulina was a mentor, and CUX was a tool to get to know our users better. For now, we’re still measuring and analyzing results, but one thing is certain – its effects are an added value for our company and its users._

**- Katarzyna Golonka-Gawęda**, Content Indexing Specialist at Prisjakt

_

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! 🥑 😉

_

![PJ_Logo_SENO_Dark-700x226.png](/uploads/PJ_Logo_SENO_Dark_700x226_b379ff362a.png)

**Prisjakt**

A premier Swedish shopping comparison engine. As one of the world’s best price and product comparison services, Prisjakt guides thousands of consumers to smarter purchases every day.

_

![Podróż-Cytaty-Kolaż-Fotograficzny-5-700x560.png](/uploads/Podroz_Cytaty_Kolaz_Fotograficzny_5_700x560_4ef450d30c.png)

**[Paulina Walkowiak](https://www.linkedin.com/in/paulinawalkowiak/)**, co-founder & CEO at CUX

Paulina’s the only specialist in the analysis of behavior patterns in CEE. She helps companies translate knowledge about users into specific business decisions. Paulina supports companies in building a data-driven culture and conducts user behaviour audits as a starting point for building market advantage in products. She’s the author of product analytics workshops “Data-driven design”, speaker at TEDx, and academic lecturer. Paulina has been featured twice in the Strong Women in IT 2019 and 2021 reports. In 2021, she and her husband receive a polish award for 50 Most Creative People in Business. One of Brief magazine’s 50 Creatives in Business. As a mom of two, she proudly calls herself Mompreneur. 

case-study-cux-prisjakt.png

From a custom webinar to the use of UX Automation on an internal analytical strategy to build a Content Visibility Strategy. Find out how Prisjakt, a Swedish comparison engine, turned into a data-driven organization, and how quickly they implemented CUX into their project, delivering it ready before the deadline.

Case study: From data-driven webinar to building an internal analytical strategy (Prisjakt x CUX)

## High traffic, low conversion
In today’s Quick Wins series, we present to you the case study of our footwear industry client. The well-known e-commerce with branded shoes at approachable prices came to us with a problem. Despite satisfactory traffic, their conversion rate remained at an alarmingly low level. To save the day, they’ve decided to start investing in abandoned carts, rather than user journey analysis. Reason? They heard on many webinars and conferences – it works! They came to CUX with their own conclusions, looking only for confirmation before moving to spending money on campaigns:

- People do not buy on mobile. They prefer to finish the purchasing process on the desktop and that’s just the way it is.
- Multivendor marketplaces (of which they have 90% of traffic) do not sell.
- We should invest in abandoned carts or invest in a new paid campaign, because the current activities didn’t work.


What’s worth mentioning is that when it comes to numbers, everything (except for the conversion, duh) seemed correct. Traffic was satisfactory even with the high bounce rate – but it rather raised a warning instead of a red flag. After preliminary interviews and basic analyzes, it also turned out that 55% of their users came from mobile. 90% of visits came from marketplaces, which they blamed for inhibiting sales. The main problem indicated by the numbers was a very low – even negligible – conversion from mobile.

![Misinterpret the data. Again.](/uploads/qw4_965afec92b.jpeg)

In addition, the conversion funnel of user journey set up by e-commerce showed that users enter and view the product page (as it turned out later, not necessarily the product itself) and exit. They did not add the product to the cart, they did not proceed to the purchase.

## Watch user journey, not just imagine it
And here is where the real adventure in searching for answers to analytical questions began! After connecting the client’s website to the tool and focusing only on traffic coming from mobile, it turned out that as many as 25% of users zoom in on the content. That was our first warning! The very first users’ visits recordings have already shown that people waste a lot of time before actually seeing the product. They were distracted, among other things, by annoying pop-ups. In many cases it took up to 1 minute to get to the “buy” button!!

Analyzing the events that the user had to perform to complete the purchase, we saw a very complicated path. Instead of an intuitive

>_product -> add to cart -> buy_

we got a complicated and multi-step waterfall

>_product -> close cookies -> close newsletter -> scroll about 300px banner with a great discount and special promotion -> add to cart -> buy_

Thanks to the recordings, we saw that not everyone closed both pop-ups. Some closed only one and tried to scroll further, which made it even longer to get to the CTA (if they’ve reached it at all)! We also saw that the button to close the newsletter sign-up window was too small. It caused mobile phone users to repeatedly click around the button, zoomed in and – worst of all – get extremely frustrated.

![Quick Wins - Customer Journey](/uploads/Picture_1_700x379_085ddac398.png)

## Quick win: 
### Shorten the user journey
In situations like this, you need to remember the basic truth: users who come to your site from the marketplace have already gone through one path entitled “find your dream sneakers”. At this stage, they are not interested in loyalty cards, newsletter subscriptions, satisfaction surveys and blog entries, but only in getting to the check out with their perfect shoe.

Smart analysis of data from user behavior allowed us to find quick wins almost immediately. The client should eliminate unnecessary content for marketplace traffic, focus the user’s attention only on the purchase and, above all, shorten the user journey. To sum up, instead of spending a fortune on a campaign to save abandoned carts, they’ve invested in two days of designer and programmer work.

Aren’t quick wins just awesome?! 😁

_

>**QUICK WINS** are quick solutions that immediately respond to the needs of your online consumers. Deployments do not require significant resources, implementing takes up to maximum 60 days (although it can be implemented right then and there). Quick wins are based on the constant observation of analytics metrics and customers’ behaviors. Thanks to analytics, we’re able to choose the right solutions that allow us to make business decisions based on data, and not on the intuitions or stakeholders’ wishes.

**Quick wins in brief:**

- do not require expenses (or generate only small costs)
- carry a low risk,
- easily accepted by business,
- recognized on the basis of data,
- results warranted,
- implemented in max. 60-90 days,
- the project team can implement them autonomously.

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! 🥑 😉

Quick Wins Series - Shorten the user journey

Quick-wins-CUX-4.png

We often come across a situation where the original conclusions drawn from the data are completely irrelevant to the reality of the user journey. How much time and – very often – money you’d be able to save by observing the users’ behavior behind these sad numbers. And how much fun it would be to implement the quick wins and watch them numbers grow!

Quick Wins #4 – Shorten the user journey

## Contact with the client is a priority
Our client from the metallurgical industry has recently found about the importance of building changes and introducing quick wins based on the expectations of our own customers. His goal – during the redesign of the current website – was to make it easier for customers to contact his company. Most of the large and significant orders for him were based on direct contact, so the contact form clarity was obviously his business biggest priority.

Presently – in the activities he was relatively satisfied with so far – the exposed form of contact on the customer-producer line was the form. However, the analysis of the heatmap data and the measurement of the business target fulfillment indicator showed that only 12% of customers go to the form page, and only 0.3% of them actually fill it in. In addition, the heatmap presenting the movements on the form page itself clearly showed that customers had skipped the fields with the form and their attention was drawn immediately to addresses, telephone numbers and e-mails.

![Contact form heatmap in CUX](/uploads/heatmapa_kontakt_CUX_700x665_3c815af75c.png)

_<center> View of the heatmap presenting the customers’ attention on the page with the form shown in CUX </center>_

## Quick win: 

### Simplify the contact page
The use of an analytical tool such as CUX allowed not only to discover a problem that the entrepreneur had not known about so far, but it also led to implementation of a solution that significantly increased his conversion (in this case, direct contact with the customer). Thanks to the simplification of the contact page, customers began to find the information they needed faster and the barrier in the form of… well, a form was eliminated. Such quick and simple implementation of changes is a perfect example of the impact of quick wins on the business potential of many companies.

 

>_**QUICK WINS** are quick solutions that immediately respond to the needs of your online consumers. Deployments do not require significant resources, implementing takes up to maximum 60 days (although it can be implemented right then and there). Quick wins are based on the constant observation of analytics metrics and customers’ behaviors. Thanks to analytics, we’re able to choose the right solutions that allow us to make business decisions based on data, and not on the intuitions or stakeholders’ wishes._

**Quick wins in brief:**

- do not require expenses (or generate only small costs)
- carry a low risk,
- easily accepted by business,
- recognized on the basis of data,
- results warranted,
- implemented in max. 60-90 days,
- the project team can implement them autonomously.

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! 🥑 😉


Quick-wins-CUX-3.png

More often than we’d like to admit, we fall into the traps of thinking: I designed it, I like it, I think it will work wonders. Unfortunately, there are only a few worse things that you can do to our business. Creating solutions checked only on ourselves, and not on our clients, has the potential of significantly reducing conversion levels or be the main reason for users’ frustration increase. It can also yield in never seeing your customers again – and they’d probably even leave you without any meaningful feedback. Unless you’ll use quick wins, like the one with contact form analysis. 

Quick Wins #3 – Contact form

## Check-out problem

One of our clients – a shop offering air purifiers for industrial spaces – has found out about this truth. Despite an efficiently operating e-commerce store, they could not cope with the huge number of customers who abandoned their full carts after placing the order. The problem was quickly detected by analyzing the customer behavior during the check-out process.

While analyzing the visits’ recordings, it became clear that the problem for the users was generated by the delivery and payment option. The store did not take into account the option of cash on delivery, which customers definitely preferred. So the obvious solution would be to add this option to the possibility of payment selection. Unfortunately, that wasn’t the only problem this e-commerce had to face.

![Choice of payment method](/uploads/wybor_sposobu_platnosci_1_700x118_d3aa6501e2.png)

_<center> Customers abandoned their shopping carts because they were unable to find the payment method they were interested in – cash on delivery </center>_

The heatmap analysis showed that customers, while navigating through the check-out, did not try to change the method of delivery or payment – even when introducing new options, which they had previously lacked. The change turned out to be definitely counterintuitive for them.

## Quick win: 
### Changing the sequence
The problem – thanks to quick wines – was solved in a few minutes, by changing the default delivery option to the one with the option of cash on delivery, i.e. the courier service. This reduced the number of direct contacts and orders via the hotline and e-mails by an impressive 37%!

![Fixed choice of payment method](/uploads/wybor_sposobu_platnosci_po_zmianach_700x142_7044ec1587.png)

_<center> Changing the default shipping and payment method reduced the number of orders placed through the hotline by 37% </center>_

Proper observation of user behavior on the website is able not only to spot problematic or frustrating places for customers, but also to direct us to quick implementations that can irretrievably solve those problems.

>_**QUICK WINS** are quick solutions that immediately respond to the needs of your online consumers. Deployments do not require significant resources, implementing takes up to maximum 60 days (although it can be implemented right then and there). Quick wins are based on the constant observation of analytics metrics and customers’ behaviors. Thanks to analytics, we’re able to choose the right solutions that allow us to make business decisions based on data, and not on the intuitions or stakeholders’ wishes._

**Quick wins in brief:**

- do not require expenses (or generate only small costs)
- carry a low risk,
- easily accepted by business,
- recognized on the basis of data,
- results warranted,
- implemented in max. 60-90 days,
- the project team can implement them autonomously.

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! 🥑 😉

Quick-wins-CUX-2.png

To say that it is important to know the specifics of our target group is to say nothing. It’s the knowledge that will not only tell us how and why customers buy, but also what they expect from us as a provider of shopping experiences. Among other things, it will be information in what order and arrangement they want to interact with our platform. 

Quick Wins #2 – Intuitive sequence

## Valentine’s jewelry brand campaign
For aniakruk.pl, one of the Polish jewelry brands, we conducted a quick analysis of the Valentine’s Day campaign. Quick, because all we had to do was to compare the whole Valentine’s Day traffic to the traffic form campaign itself. It helped us understand what exactly customers were doing on the site. It also guided us on how to design new campaigns that will better suit users needs in the future.

But let’s start from the beginning. CUX automatically collects and generates [heatmaps](https://cux.io/knowledge-base/heatmaps/how-to-read-a-heatmap/) for all URLs that the user has accessed at least once. Thanks to this, we can analyze the data at any time. We do not have to plan in advance what address we will research and at what time we’ll do it. This allows – especially in a problematic – to use analytics to better understand any occurring event.

In the case of aniakruk.pl, right after Valentine’s Day, we started the analysis by checking how customers generally behaved on the page with products specially selected for the occasion. We used heatmaps for “direct” entries and for visits navigating within the Valentine’s Day offer.

![aniakruk.pl and CUX: campaign analysis](/uploads/Ania_Kruk_case_1_700x240_f73d8c0d85.png)

_<center>The heatmap applies only to entries on a specific URL</center>_

By analyzing the clicks on the heatmap, we did not notice any unusual or questionable events. We’ve observed a rather natural, diffused flow of customers, without too much involvement in browsing individual products. Most of the clicks accumulate around the option to choose a specific assortment (on the left).

![aniakruk.pl campaign analysis: CUX Heatmap](/uploads/Ania_Kruk_case2_700x381_3db23b7c1c.png)

_<center>Heatmap for the aniakruk.pl Valentine’s campaign</center>_

## Filtering: Campaign only traffic
After the initial analysis, we’ve decided to check what the same entrances looked like in the case of customers who clearly came to the site from external campaigns. To do this, all you have to do is filter the entries after the given URL. The address should have an additional “tail” to recognize where a given client came from, e.g._ fbclid._

Using filtering, we have prepared a list of all addresses of interest to us. Then we’ve generated a [grouped heatmap](https://cux.io/knowledge-base/heatmaps/what-are-grouped-heatmaps/) for them (the function is in the upper right corner of the page). Such a heatmap allows to generate a collective image for many URLs. URLs under which there are pages with the same structure – e.g. product pages or just campaign entrances. Those addresses, in the basic analysis, will be only visable in the form of separate URLs.

![aniakruk.pl campaign analysis: CUX grouped Heatmap](/uploads/Ania_Kruk_case_3_700x278_bff833d7e8.png)

_<center>Grouped heatmap allows you to see the same page displayed by visitors using different entry points.</center>_

In this case, the situation is slightly different from the case of “direct” entries. First, we see a clearly greater involvement of users who clicked more often (more red spots). The grouped heatmap also allows us to observe that customers did not click on the products themselves as eagerly as on the filtering options. They were trying in all possible ways to narrow down the range of products! The item in the top menu under the name “Czego szukasz” [eng. _What are you looking for_] was also very popular.

## Searching for frustration
Interestingly, we did not see an increased or significant number of clicks in the menu after its expansion. Only a few clicks in the vicinity of the banner. Remember that a heatmap is only a visualization of a single page state. If customers expanded the menu, then in the classic heatmap we will observe clicks “floating in the air”. When in fact they may relate to elements such as pop-ups, widgets or just a sliding menu. From the analysis of the grouped heatmap, we can conclude that customers did not move further on the site. This may suggest that they did not find what they were looking for. A conclusion that is especially emphasized if we go deeper into the analysis.

![aniakruk.pl campaign analysis: CUX grouped Heatmap](/uploads/Ania_Kruk_case_4_700x401_7dd7c655a3.png)

_<center>Grouped heatmap of the jewelry brand’s Valentine’s Day campaign</center>_

Changing the data display type to [“rage clicks”](https://cux.io/features/#experience-metrics) only confirms our hypothesis. Customers were disappointed after clicking on the aforementioned category. In addition, it gave us valuable information about existing problems. Including the info about usefulness of a slider that allows filtering by prices. We could also observe the lack of decisiveness or difficulties of customers in choosing the way of displaying products.

![Campaign analysis: CUX rage clicks](/uploads/Ania_Kruk_case_5_1536x859_b87ed15813.png)

_<center>Grouped heatmap of the jewelry brand’s Valentine’s campaign focused on “rage clicks”</center>_

## Conclusion
Contextual campaigns focused on individual product categories sell up to 3x more. Based on the above analysis, customers need to narrow down the results they get in e-commerce. It mainly shows in their behavior on the website. Things like moving mainly around the filtering options, clicking the “What are you looking for” menu bar or rage clicks around the price changing slider.

Our recommendation is to base the next campaign on segments, e.g. products in specific price ranges. In the meantime, we also recommend further investigating the usability problems of the price slider. Working out a new solution for it could significantly improve conversion.

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! 🥑 😉

case-study-cux-ania-kruk.png

There are more and more methods of measuring the effectiveness of campaigns. From traditional indicators and Google Analytics support, to more advanced tools focusing on campaign analysis. Most often, however, we target our analytical thoughts at the results themselves – whether presented in the form of numbers, percentages or visualized with charts. When trying to improve campaigns, we use trends and research of customer preferences, as well as “proven methods” from the market’s specialist. However, it soon turns out that the analysis of historical (or current) data on the campaign and the actual User Journey can be much more effective.

Know your user’s mind: Valentine’s campaign analysis – The aniakruk.pl Case

Forms are ideal analytical examples. They illustrate the fact that often only by looking at our product through the eyes of the users we’ll be able to make a quick, effective and error-free assessment of the situation. Our client from the e-commerce sector has to found out about it the hard way.

## Form validation errors

The form validation message below seems to be correct – the fields marked in red need to be filled in. However, it quickly turned out that the validation itself generated basic problems. It made users abandon carts without completing the purchasing process.

![Form validation](/uploads/walidacja_komunikat_bledu_700x593_487c0f8158.png)

_<center> The form red-highlights the fields that must be completed </center>_

The situation appeared to be even more complicated. The errors in the form no longer applied to specific blank fields, but to unmarked checkboxes. Recordings of users’ visits clearly showed us the problem – consternation! Because the text that appeared under the checkbox was hardly visible – and of course in small red font – bewildered users, not seeing the place of the error, repeatedly and angrily clicked on the red text on the right.

![Form validation mistakes](/uploads/walidacja_komunikat_bledu_2_700x577_56637c053e.png)

_<center> Unable to see the small error validation text under the checkbox, users clicked on the red text on the right side of the page </center>_

## Quick win: 
### Cosmetic change

Only analytical tool focusing on the overview of user behavior patterns will be able to catch the “chaotic movements” indicator. It’s an evidence of a user being lost on the website (which in this case jumped from 0 to as much as 17%!). The introduction of cosmetic change on the form page, captured thanks to the analysis of recordings, results in even more than 20% increase in customer conversion!

Quick win – a solution that immediately eliminates the consumer’s problem – in this case was the introduction of small visual corrections on the form page. Changing the colors of individual fonts, emphasizing the need to check certain checkboxes. Thanks to quick wins, the client was able to quickly spot the problem and address it before the conversion rate would drop irreversibly.

>_**QUICK WINS** are quick solutions that immediately respond to the needs of your online consumers. Deployments do not require significant resources, implementing takes up to maximum 60 days. Although most implementations can be carried right then and there. Quick wins are based on the constant observation of analytics metrics and customers’ behaviors. Thanks to analytics, we’re able to choose the right solutions that allow us to make business decisions based on data, and not on the intuitions or stakeholders’ wishes._

**Quick wins in brief:**

- do not require expenses (or generate only small costs)
- carry a low risk,
- easily accepted by business,
- recognized on the basis of data,
- results warranted,
- improvements can be implemented in max. 60-90 days,
- the project team can implement them autonomously.

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! 🥑 😉

Quick-wins-CUX-1.png

The topic of analyzing forms – validating errors, designing checkboxes, avoiding popular mishaps – has already been widely covered. Unfortunately, despite the huge access to valuable reading, we’re dealing with form errors that result in customers’ decrease in conversion repeatedly. And this is what the first case of our Quick Wins series will be about. Enjoy & implement!

Quick Wins #1 – Form validation

For F1Brand, data analysis is extremely important, however, it’s not just a tool used to help design a marketing campaign. Data analysis is used throughout the whole customer journey – from the moment the customer sees the banner on the website all the way to the purchase.

>_Paulina and Kamil (founders of CUX) offer the best tool for deep analysis of the customer journey on the website. CUX gives me the opportunity to verify my hypotheses (based on Google Analytics data) and convert them to the data-driven recommendations for my clients. – says Marcelina Lipska, CEO & Founder of [F1Brand](https://f1brand.pl/)._

![user_journey-1536x673.png](/uploads/user_journey_1536x673_7070d4c073.png)

While managing one of its B2B sector clients, F1Brand noticed a rather strange phenomenon on the company’s shopping website. Although this was a low traffic site, the statistics showed a very high value for abandoned baskets. In such cases, the standard solution recommended by an agency is to try to recover these baskets. However, F1Brand decided to investigate further. As the numbers in Google Analytics did not provide enough information, they decided to make a qualitative analysis in CUX. It turned out that most of the users would never make a purchase upon their first visit. They would choose a product, put it in the basket, and then exit the site. Upon returning to this page after a few days, they would find the same product already in their basket waiting for them to be purchased. Although at that point they could proceed to checkout—for reasons known only to themselves—they would empty the basket, and then find the product and add it to the shopping cart again. This consumer behavior caused an exceptionally high level of abandoned baskets, without actually affecting the sales rate of the online store. Although alarming at first, the data did not actually reflect any real issue. Without analyzing the recordings in CUX, finding an explanation for the high rate of abandoned baskets would be impossible. The numbers in GA showed a problem, but only a qualitative analysis made it possible to see what caused these numbers.

Another client noticed that for a very large percentage of orders, there was a need to change the shipping method for a purchased item. During the analysis of recordings, it turned out that ‘personal pickup’ was the default option for shipping. The recordings revealed that customers skipped step with choosing shipping methods because one of them was preassigned. While this was not a major problem for local customers, it was a deal-breaker for the inhabitants of the other regions of Poland. After analyzing the recordings, F1Brand suggested the possibility of choosing shipping options by the client. Thanks to the decisions made on watching the recordings, the percentage of users who completed the form correctly all the way to the end increased significantly.

The examples above prove that the numbers F1Brand saw in Google Analytics were just the tip of the iceberg. GA statistics did highlight an issue but failed to give any insight into the matter. Qualitative analysis in CUX based on recordings, explained the reality behind numbers and suggested quick win actions that were able to fix both the customer journeys and numbers.


If you have any questions, doubts, would like to implement analytics or solve a problem on your website (or maybe you just want to say “hi” 😉) – drop a line at [paulina@cux.io](mailto:paulina@cux.io). We will be more than happy to hear from you ❤️ And if you would like to receive newest information about our product, sign up for [the CUX newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b).

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Aside from promotional activities carried out for their clients, marketing agencies analyze hundreds of pieces of information every day to make sure their campaigns are working properly. Besides basic metrics that everyone is checking, there is a world of data out there which increases the awareness of understanding the human behind the screen with each day. Smart agencies analyze customer journeys to help their clients understand them better, so that, together, they can build more effective marketing strategies. F1Brand is a great example of a smart agency. They deal with marketing on many levels – from strategy development and managing campaigns, through communication in social media, public relations to marketing workshops and online solutions.

How to support the customer journey on the client’s website (from a marketing agency’s point of view)? – The F1Brand case

[In our previous article](https://cux.io/blog/how-to-boost-your-conversion-rate-using-analytics-as-a-daily-routine-the-t-mobile-case/), we described the situation of T-Mobile using CUX to successfully detect the reason for a sudden decrease in conversion rate in one of its campaigns. However, this was not the only case in which CUX proved to be a salutary solution for T-Mobile. Here’s another example. This time an affiliate network was providing advertising services for the operator. At some point, it turned out, that one of the affiliates was not delivering the targets set at the start. The traffic from the campaign seemed to be right – increasing, the time of the visits implied that the users were real, but the conversion level was definitely not satisfying. Something was clearly not working.

![T-Mobile Case Study CUX](/uploads/case2_700x428_a87a23d8ed.png)

Was is a weak offer? The wrong rate? Or maybe this is not the best source of traffic? At that point of the campaign, a decision could well be made, based on reading the tea leaves. Thankfully, T-Mobile decided to look into CUX, watch several session recordings and verify the situation. Visit recordings showed, that most of the visits from the above-mentioned affiliate’s campaigns were opened in the background tab and the time spent on the site was negligible. Because of that, chances for conversion were close to zero.

![T-Mobile Case Study cux.io](/uploads/case2_1_700x301_3dfbcf3110.png)

Solving this puzzle was possible thanks to the unique indicators available in CUX. In our qualitative analytics tool, you can see, whether the site is currently being viewed by the customer or it is open in the background. You can also check the so-called ‘engagement time’, i.e. the time that the user spends actively on your website. Thanks to these indicators, T-Mobile discovered that the affiliate was smart enough to open pages in order to inflate the cost of the campaign, which was implemented in the CPC (cost per click) model.

If you have any questions, doubts, would like to implement analytics or solve a problem on your website (or maybe you just want to say “hi” 😉) – drop a line at [paulina@cux.io](mailto:paulina@cux.io). We will be more than happy to hear from you ❤️ And if you would like to receive newest information about our product, sign up for [the CUX newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b).

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T-Mobile - as one of the largest mobile operators in Poland and the world – cannot afford a lack of media presence. They use activities carried out by marketing agencies in order to build brand awareness and acquire new customers via the internet. According to the “trust but control” principle, T-Mobile monitors most of its campaigns in CUX.


How to monitor a campaign with CUX? The T-Mobile case

T-Mobile. One of the largest mobile operators in Poland, with over 12 million customers, offering mobile and fixed services to both private customers and business clients.  Sure, they owe a large portion of their success to huge marketing campaigns. But it’s analytics that gives them the advantage. Daily examination of gathered data and key indicators allows for verifying business decisions and increasing response time.

During one of T-Mobile’s campaigns, the level of conversion suddenly dropped. Customers eagerly moved from the landing page to the next step, but—for some reason—wouldn’t go a single step further. They were quitting the shopping cart/exiting at the shopping cart stage, causing the campaign’s level of conversion to drop drastically.

![T-mobile conversion drop](/uploads/image001_4_1_700x147_c103195a59.png)

The situation was detected by T-Mobile employees at a daily analytical meeting, however, before any decision-making, they decided to use CUX and go through the quitting customers’ visits – of exactly those people who added to the cart but did not convert.  After watching several recordings, the situation cleared up. The offer people had seen directly on the landing page differed from what they saw after adding it to the cart.  The price of the device was different, the internet package was different and this led them to give up their purchase and leave the operator’s website. Thanks to the visit recordings, T-Mobile easily detected the problem users were facing, and the cause of the sudden drop. They could immediately make the appropriate changes and implement quick-wins to save both, the campaign and the conversion.

![T-mobile offer view](/uploads/screen_tmobile_700x433_2ce2129c61.png)

![T-mobile cart view ](/uploads/tmobile_screen2_700x358_9d84cfd8d5.png)

Such efficient problem detection was possible thanks to the integration of our tool with Google Tag Manager. The numbers, which are usually seen in Google Analytics, analyzed separately from the recordings, do not always quickly and clearly bring the answers.  Some hypotheses can be made based on GA, but GA alone does not allow you to make good business decisions with a clear conscience. Integration with GTM brings qualitative and quantitative analysis as close together as possible. We capture all the data from the site and all the events from the data layer to CUX, where, thanks to simple filtering by names and categories, you can search for specific recordings.

Looking at such selected events, we can define the cause of the error and – as in the case of T-Mobile – quickly make a decision to return to the desired level of conversion.

[Start to use](https://app/cux.io/register) GTM integration and be smart as T-Mobile specialist.


If you have any questions, doubts, would like to implement analytics or solve a problem on your website (or maybe you just want to say “hi” 😉) – drop a line at [paulina@cux.io](mailto:paulina@cux.io). We will be more than happy to hear from you ❤️ And if you would like to receive newest information about our product, sign up for [the CUX newsletter](https://share.hsforms.com/1zmJkyNsvRPSLaAgf-pYNWA2pu7b).

Conversion rate – the main metric monitored by every e-commerce manager. When it grows – we celebrate, when it falls – we want to know why. However, numbers alone will never help us solve the problem – they can show us the drop-offs, but without proper analysis, they do not tell us why the drop happened. The reasons for the conversion’s decrease vary- just like our users. So, how can we find a tailor-made solution?