Since last week’s reporting on 1.8 billion user sessions, we’ve been continuously analyzing digital behavior across key industries to understand in real-time the impact of the Covid-19 outbreak on global eCommerce activity.
By comparing a key set of visitor metrics (including traffic, transactions, time spent, etc) week to week, we’re able to uncover patterns in shifting online and shopping, putting facts behind the digital business trends everyone is talking about.
In today’s analysis, we compare data from billions of user sessions across 1,400 global websites, gathered over the course of three weeks:
Week 1 — 2/17 to 2/23
Week 2 — 2/24 to 3/1
Week 3 — 3/2 to 3/8
The Travel & Hospitality Sector Declines Continue
The traffic and transaction data on travel and hospitality sites confirm significantly fewer visits, with traffic dropping steadily from week to week. Dwindling transactions also reflect the recent travel restrictions and bans, and the general uncertainty over upcoming travel and holiday plans.
Visits to hotel and holiday park sites dropped –6.5% between weeks 1 and 2, decreasing a further 11.4% in week 3. The transactions gap also doubled week on week, with a –5.4% drop between weeks 1 and 2, and an –11.9% decrease in week 3.
Holiday booking sites recorded a slightly different trend, with traffic dropping by –12.9% from weeks 1 to week 2, followed by a slighter decrease of –6.4% in week 3 so customers main remain optimistic the situation is temporary. Transactions took a definite downward turn, with –19% fewer transactions from weeks 1 to 2, and a further –11.3% dip in week 3.
Meanwhile, traffic to car rental sites went down –13% in the first period, and –7.4% in the second. Transactions dropped by –8.3%, and then again by –9.2% in week 3.
Consumers Are Stocking Up On Necessities & Health Items
Reports of panic buying, empty shelves, product shortages and even store-imposed limits on certain purchases have been flooding the news. Our analysis shows that in the digital world, consumers have also been flocking to stores to stock up on essentials.
Traffic to grocery stores went up 7.1% between weeks 1 and 2, and another 10.3% between weeks 2 and 3. Transactions shot up 15.7% in that first period and increased a further 10.9% in week 3.
Visits to premium grocery stores — which initially went up by 4.7%, but in the second week period dropped by –6% — reflect the trend for stocking pantries with necessities. The number of transactions confirms this back to basics with week 3 recording a –20.7% decrease in sales, after an initial increase of 19.9% in the previous period.
But it’s not just groceries people are ordering in.
Visits to healthcare sites (think health food stores, vitamin stores, etc) went up 11% between weeks 1 and 2, and a whopping 24.6% between week 2 and 3. Sales rocketed by 27% in that first period, and 7.1% in the following week.
Social Distancing & The Impact On Digital
As officials restrict gatherings in certain regions of the world, and major sporting events get suspended, individual consumers are also spending less time on sites related to outdoor pursuits and more time consuming digital media.
Traffic to sporting goods stores went down –18.3% between weeks 1 and 2, and dropped again by 11.3% between week 2 and 3. Transactions fell –23.1% in that first period and –13.5% in the following period.
Our analysts also noticed that visits to footwear sites dropped slightly in the last few weeks (by –4.2% in the first period, and –1.8% in the second), with sales following suit and dropping –11.1% between weeks 2 and 3.
Visits to retail tech sites, on the other hand, grew from week to week: 11.5% in the first period and 5.5% in the second. Transactions also went up by 12.7% in the first period and 4.5% in the second. Again these figures reflect a greater reliance on technology as more meetings turn remote and people adapt to shifting working conditions.
Meanwhile, visits to media sites (news, tv, radio, etc) shot up 16.8% in the first period, and 14.2% in the following period. Tellingly, the number of hours spent on these sites increased by 22.1% between weeks 1 and 2, and by 13.9% from week 2 to 3.
Ironically we noted a change in trend for B2B Saas: traffic to B2B SaaS sites was down –5.7% between weeks 1 and 2, but shot up by 11.8% between week 2 and 3, perhaps reflecting a growing need for businesses to boost their digital strategies as more and more purchases, events, meetings and transactions shift from offline to online. The number of hours spent browsing these sites went up by 5.8% between weeks 2 and 3.
We will keep monitoring the data over the coming weeks to bring you timely updates of how events are impacting various sectors. In the meantime, our 2020 Digital Experience Benchmark report is available to download, and contains key verticalized insights on how today’s consumer likes to browse.
Hero image via Adobe Stock, by chonlatitImpact of the Coronavirus on Digital Retail: An Analysis of 1.8 Billion Site Visits
With the coronavirus outbreak leading to travel restrictions and affecting daily activities in several regions of the world, many have also been predicting the impact of the virus on brick-and-mortar retail and global ecommerce activity.
We analyzed 1.8 billion user sessions and 50 million transactions across 1,400 global websites to understand if and how digital consumer behavior has changed over the last two weeks.
We compared the conversion rate, number of transactions, number of visits and session duration between the week beginning 2/16 and the week beginning 2/23.
Here are the findings:
Purchases on Travel Sites Drop by a Fifth
With consumers limiting or abandoning travel plans in light of the outbreak, the outbreak is having a serious effect on the travel sector, and our data confirms lower engagement and a significant drop in sales.
Purchases on travel sites decreased by a fifth (-20.8%), while the average conversion rate on those sites also took a hit (-8.5%). Overall, consumers spent less time browsing trips, with 13.5% fewer sessions, and a 14% fewer hours spent browsing these sites.
Metrics on hospitality and hotel sites also dropped across the board with a 6.5% decrease in site visits and a 7.7% dropoff in conversions.
Transactions on transportation sites were down 6.6% and the average conversion rate also dropped slightly 0.8%.
Average Conversion Rate for Grocery Sector Increases by 8%
As reports come in of panic-buying in some areas of the world, we observed a surge in conversions on household and grocery items, and a significant increase in the number of hours spent browsing essential goods.
Supermarket sales went up by 16% and the average conversion rate for the sector increased by 8.1%. Premium online grocery purchases went up by a fifth (19.9%), while consumers clocked in 25.7% more hours browsing for groceries.
Large retailers and marketplaces saw sales increase by a fifth (21%) with a hefty conversion rate increase of 14.8%. Our data showed shoppers also spent 44% more time on these sites.
27% More Transactions for Health Retailers
Consumers also made 10.3% more visits to sites selling healthcare products including pharmacies and health food retailers. Visits were 23% shorter but the number of transactions increased by 27.3%, bringing the average conversion rate up by 15.4% and suggesting many shoppers were browsing with specific items in mind.
Sports Equipment Sales Drop by a Third
Sporting equipment retailers recorded a hefty 28.4% decrease in transactions, and a 9.5% dip in the conversion rate. There were 21% fewer sessions and overall, the amount of time spent on these sites decreased by 10.7%.
Conversion Rate Goes Up 7.3% in the Fashion Sector
Fashion retailers recorded a steady number of visits, yet sales and the average conversion rate both went up 7.3%. Visitors also spent 13.9% more time on these sites.
For stores specializing in lingerie, the increase was even greater, with a surprising 35.1% jump in the number of transactions week on week.
Customer behavior can be unpredictable. Our sweep of 2020 benchmark data cuts through the noise, bringing you key digital patterns, and insight into how people like to browse across industries. We analyzed over 7 billion sessions across 9 verticals on 400 global sites this past year and consolidated this data to fish out crucial trends and patterns.
Download our 2020 Digital Experience Benchmark today.
Leveraging Data Science to Understand User Behavior
This article was written by our partner Cognetik, as part of our series highlighting direct insights from our large ecosystem of partners.
Data Science is an umbrella term used for multiple industries, such as data analytics, big data, business intelligence, data mining, machine learning & AI, and predictive analytics, and is clearly on an upward trend. Specifically, the big data and business analytics market was valued at $168.8 billion in 2018 and is forecasted to grow up to $274.3 billion by 2022 at a CAGR of 13.2%, according to Market Reports World.
The surge in spending for data science solutions, talent within the industry, and successful implementations demonstrate that companies understand the tremendous impact data can have on business performance.
As business interactions around the world become increasingly digitized, massive amounts of data are created and can be evaluated through predictive analytics tools to help companies gain a better understanding of market dynamics and underlying trends. With this knowledge, companies can then uncover the needs and expectations of their customers, and ultimately improve the end-user experience.
Therefore, it is no surprise that predictive models rank as one of the top big data technology trends around the world. The value data science can provide for businesses today is unprecedented.
However, even though leveraging data is at the heart of many businesses today, data alone can not provide all of the answers organizations need. Companies require insights and actionable paths they can take to optimize and adjust their business for maximum results.
Impact of Data Science & Global Utilization
The rise of data science has helped analysts and digital teams at large become real-life wizards who gather data at an unparalleled pace, validate its accuracy, assess its meaning, generate insights, formulate actionable plans, and deliver incredible results. Companies all over the world have realized that this isn’t necessarily magic, but rather a transformation and process they need to adopt in order to stay competitive and maintain relevance in the digital age.
Data Science has provided solutions for many industries that have been struggling for a long time. For example, in retail, companies have completely revamped the way they interact with their customers by focusing on creating easier paths for purchasing and tailoring the experience to the needs of specific audiences. In the healthcare industry, data science has drastically reduced the time needed to develop new drugs and has streamlined the ability for patients to get professional help in remote areas.
Cities have also been forever changed by data science, with thousands of sensors embedded throughout our neighborhoods to optimize traffic, reduce crime rates, and improve the overall quality of life.
The Connection Between Data Science & User Behavior
A business may experience thousands of digital interactions with a single user across display, search, social, and on the site or app. These interactions take place on multiple devices, such as mobile, desktop, tablet, or wearable devices.
Initially, analyzing immense data volumes associated with each individual user to make relevant connections was no easy task. However, with the rise of AI and machine learning algorithms, analyzing data points from multiple data sources to create a holistic view of users is now realistic and attainable.
User behavior, including actions, what they search for, and how they interact with digital properties as a whole, can now be collected and transformed into specific customer segments. These insights ultimately lead to personalized user journeys to gain a comprehensive understanding of user behavior, develop targeted advertising, and improve digital experiences.
For retailers today, recommendation engines are among the most used tools because they can give businesses an in-depth look into the interests and goals of their customers and help predict trends. The recommendation engines are complex machine learning components and deep learning algorithms designed to keep a track record of customer segments, analyze behavioral patterns based on this data, and improve the digital experience for customers.
Why You Need to Understand User Behavior
Banks and retailers were among the first industries that realized understanding behavioral patterns of their clients can lead to incredible breakthroughs.
For example, with data science, banks can manage their resources efficiently and make smart decisions through customer segmentation, fraud detection, customer data, and risk modeling via real-time predictive analytics.
By leveraging data science, banks can also have a holistic view of their customer lifetime value as well as part of specific profiling patterns. This, alongside behavioral pattern analysis, allows banks to make accurate predictions about their clients.
In time, customer profiling became one of the top data science applications in finance. By leveraging data they collect from all sources linked to their customers, financial institutions have managed to assess risk and liabilities associated with specific clients before even working with them.
Cognetik: Taking Behavior to the Next Level with Data Science
Our valued partnership with Contentsquare helps numerous industries capture intricate behavior patterns of consumers, provide sophisticated segmentation, and improve digital properties through the power of data.
Data science takes data analysis to the next level, allowing businesses to predict what users might do, augment the user journey, and provide incredible insights that are unmatched.
As an analytics and data science company, Cognetik helps the Fortune 1000 go above and beyond the standard recipe for making data science a reality. Our team of experts can guide you through the process, analyze what would work best for your business, and help you implement it in order to gain a holistic view of your users and improve your digital properties.
Adobe Stock, via titima157How to Identify and Fix a Broken UX with User Behavior Analytics
Some website users undergo a bad UX, which leads them to exit — or worse — bounce from a website, possibly to never again return. Understanding what causes premature site exits is key to improving the customer experience (CX), and delivering journeys that help customers meet their wide-ranging digital expectations.
Making use of data for a UX analysis is the most practical approach to scrutinizing customer journeys, including high-level views that locate friction points and counter-intuitive navigation patterns. Once you’ve identified your problematic pages through a high-level view of user behavior, you can make more fine-tuned changes by assessing individual pages and elements.
Achieving a fulfilling digital experience is attainable, but you have to identify what constitutes a broken UX in the first place, and establish the visitor segments that come across one. Once you have this insight on hand, you can prioritize optimization efforts to improve your digital experience and make your visitors crave more.
Identifying What’s Amiss in the Customer Journey
We quizzed Ying Yang, our Lead Product Experience Manager, to get her thoughts on where to start. “The first thing you must look at when identifying a poor UX is the customer journey,” she said. “You should be able to break it apart page by page to see exactly how users traverse your site during each session.”
A well-built customer journey analysis tool will show you each step a customer takes during their time spent on a site, help uncover what they are trying to do, and how they went about doing it. You ought to be able to detect where the first UX friction lies on a high level; to find this, you have to pinpoint where users are bouncing or leaving the site, and what led to this outcome.
“You need to identify the last page that a segment of users stayed on during their journey before leaving your site. It is this page in which their UX was disrupted,” explained Ying.
“However, in longer customer journeys, note that a page from which a user has left the site may not signify a bad experience. Instead, the user may simply feel that their stay on the site is complete, and requires no further browsing.”
As such, observe the pages that contain bounces initially, as there is some shortage of retaining the visitors’ interest. Furthermore, since a bounce is more caustic than a regular site leave, it requires immediate attention. (Bounces reveal a non-existent journey, or one of one step/page visit).
Now that you’ve found the page with the UX culprit of bouncing or exiting, let’s delve further.
A Further Analysis of a Crippled UX
Entering step two of making corrections, you will need to work out the cause behind particular site exits or other behaviors indicative of frustration or unmet needs. In order to spot individual obstacles in the customer journey, you’ll need to analyze specific elements within a page.
Through this approach, you’ll be able to catch the exact cause of friction (whether it’s a CTA, image, product description, form field, etc), as opposed to guessing what regions and elements of a page led users to leave.
So what do you do when analyzing a particular page element? You take a hyper-focused turn in your UX analysis. “This is a more granular step,” says Ying. “As such, you’ll want to look at a robust batch of behavior and revenue metrics. These present a deeper dive of your UX to follow up the customer journey analysis.”
Here are just a few of the metrics you can appraise for a granular UX performance check:
Hover Rate: The percentage of pageviews in which visitors hovered over the zone at least once, determining which zones are consumed the most. This helps you rank zones and assess if they are consulted properly, by weighing in factors like averages of other zones and the page length.
Click Recurrence: represents the average number of times a zone was clicked when engaged with during a pageview. This exposes either engagement or frustration. For example, a high click recurrence on a carousel is good news, as it shows a high engagement with an element offering many clickable areas.
It can also point to frustration. For example, if users click on the same element multiple times — such as an image or link, it means the element is drawing up errors; it’s either unclickable or not performing its function correctly.
Conversion Rate Per Click: Applying only to clickable zone, this metric relays if clicking on a zone impacts the user’s behavior or conversion goal.This helps you determine which elements contribute to or deter from conversions. A conversion can be any behavior you set.
Exposure Rate: identifies how far down a page a user scrolls; it’s accounted for when at least half of a zone is viewed. This helps you understand how much users scroll, allowing you to make empirical sizing adjustments.
Attractiveness Rate: Relays the percentage of visitors who clicked on a zone after having been exposed to it. This informs you on optimizing the placement of content on your page. For example, if more users click below the fold, you should move that content further up for more of them to see it quicker. A high rate proves the high performing attractiveness of an element.
Segmenting Your Users for UX Comparisons
After you analyzed the elements of your page with granular behavior metrics, you’ll need to analyze further, by conducting comparisons. This will help you determine what comprises an underperforming UX more clearly. To do this, you would need to compare a good behavior with a bad behavior.
Comparing the experience of visitors who accomplished the goal of a page with those who didn’t, will further confirm what needs fixing. You can carry out a zoning analysis on these two segments as well as make comparisons on each metric.
This allows you to catch where non-converting visitors tend to hover and where they are more inactive. But most importantly, it allows you to weigh this data against the users who did convert/ achieve what they came to your site to do.
“For example, you can build a segment for the users who saw a 404 error page and compare it with the ones who had the same issue across different journeys or those who didn’t run into it,” explained Ying. “Additionally, you can create a segment around users who clicked on a CTA, deepening their journey against a segment of users who didn’t, or worse, ended their journey on that page.”
Main Examples of UX That Cuts the Customer Journey
One of the attributes of a broken UX is content that doesn’t engage users or is not seen, thus prompting visitors to exit the site. Pages that require too much scrolling, for example, may yield low engagement or little to no views.
For example, a particularly wide banner that takes up much of the screen may be obscuring other content that’s crucial to generating revenue. Some users may not even be aware of the content below the fold.
“Most high-performing content should have real estate above the fold,” Ying advises. “Does your business have a major campaign or sub campaign running? Post more than one type of content about it above the fold. These can exist as tiles, a carousel or both.”
This source of friction is especially damaging to mobile UX, which has a much smaller screen size than desktop. As such, some functionalities aren’t well suited to be crammed in. “Big banners, images and accordions (vertical menus) push everything down below the fold, so don’t overuse them. You will probably need to scale back on some of these elements to avoid a UX that has turned sour.”
Another example of poor content occurs when banner usage is slight and/or doesn’t achieve the goal of a page. For example, a banner can send users to a PDP (product details page) that cuts off their browsing journey.
“PDPs, in general, have high bounce rates, as in the case of our retail clients, so you need to be careful what products you send users to, should your banner send them to a PDP (or even a product landing page). Landing on a PDP is especially detrimental to the user experience when the real goal was to send users to a PLP (product landing page), which shows several product options as opposed to a PDP.”
Fixing Customer Journeys
Now you know how to move the needle from a high-level UX analysis to a granular level to spot what caused your customers to struggle or give up with your site. After you identify what leads to bad digital experiences, you are all set to start optimizing. Customer experience analytics are your best friend when it comes to augmenting your content ideation strategy.
Since it allows you to meticulously identify digital experience issues, it fastracks you to brainstorming sessions to rectify the issues in a data-backed way. Some things will be clearer than others. For example, if you find 404 errors and other dead-end pages, the quick fix is the get rid of them, or replace them with the proper pages.
“For example, if an item is no longer in stock, or no longer being digitally offered, make sure it doesn’t yield the 404 error. But if it’s a product users can purchase, or if a page offers any other type of conversion (signing up for content, etc.), make sure your page is functional and devoid of any confusing elements,” said Ying.”
Hero image via Adobe Stock, by Marvi7UX Global Map Lessons: Comparing Online Customer Acquisition Marketing Channels
There’s a lot to learn from the way site visitors browse and interact with your website. Then there’s customer acquisition marketing, since before users navigate your site, they must be acquired, which is a digital marketing feat on its own. Much of what we cover is UX (user experience) — the environment and associated feelings users undergo on your website and other digital offerings.
But drawing users in is a major step, a push further down the sales funnel, bring them closer to conversion and certainly a crucial to brand awareness. Sometimes it involves perfecting the UX as well, except as an alternative to onsite behaviors, it deals with those on acquisition channels, some of which you can customize, i.e., social media.
As the final installment of our 3-part series covering the UX International Map, this iteration will edify you on what customer acquisition marketing channels look like through a global lens. After all, if you’re going to set up websites for different countries, acquiring the users of these countries and their distinct acquisition manners is key to be mindful of.
Acquisition Channel Methodology
In the past 2 UX map lessons, you’ve read that we parsed through over 35 million visitor sessions in January and February 2019 on 11 luxury websites — that’s 150 million page views and 3 billion clicks.
The 7 countries we focused our analyses on were: the US, UK, France, Germany, Italy, China and Japan.
For each of the 7 countries we surveyed, we analyzed the performance of 12 acquisition channels — both paid and unpaid. For each country we scrutinized, we asked the following questions to get a deep read of how websites were gaining visitors:
- Do consumers prefer free or paid channels?
- How do they arrive at your site?
- Did users do independent research or follow a recommendation?
Free Vs Paid Acquisition Channels
The chief divide of digital acquisition channels is whether they are free or paid. Free acquisition channels, as their name suggests, are outlets that you can leverage for free. They encompass the following:
- Organic search results (SEO)
- Direct traffic
- Referral traffic
- Social media posts (unsponsored)
Paid acquisition channels are cost-based and these costs are not unilateral. In other words, while PPC ads will cost you for each click on the keyword you bid on, affiliate marketing will cost you the amount agreed upon with your affiliate marketer. These channels include:
- Paid Search (SEM/PPC)
- Paid Social (sponsored content)
- Display Ads
- Affiliate Marketing
- Brandzone (Baidu)
- Influencer marketing
The Global Majority of Online Consumers Prefer Free Acquisition Channels
While it’s patently obvious that brands and marketers prefer to acquire consumers through free means, our analysis has found that even from a consumer standpoint, the preferred method of arriving at a new website is from a free traffic source. With a 61% global average share of traffic from free channels, this is something of a global consensus.
The customer audiences in Japan and Italy are at the higher ends of the free acquisition spectrum, as they reach websites through free channels at the respective rates of 69% and 65% of their total acquisition. The US comes in at third, with 62% of its site visitors springing from free acquisition channels.
France has the lowest share of traffic from free channels, at 55%. Germany and China come in second at the low end of the free channel spectrum with traffic rates of 58% from both countries.
Acquisition through Consumer Research or Recommendation
Another way to gauge customer preferences and segment behaviors is by analyzing whether visitors land on your site from independent research or by following a product recommendation. It’s crucial to study this, since some consumers arrive at your website through their own due diligence from research, while some need to be marketed to concertedly, i.e., in a direct way, often involving recommendations. (Think targeted ads and sponsored social content).
Here are a few independent research channels:
- Organic search (SEO)
- Paid search
Here are a few recommendation research channels:
- Paid social
- Affiliate Marketing
- Influencer Marketing
So which acquisition method, independent research or product recommendation takes the victory among our swath of global consumers? In this type of acquisition square-off, the emerging winner is independent research, which holds the majority across every country we surveyed.
In Italy, 92% of consumers reach a site through their own research, overshadowing the country’s 8% of consumers who reach a site by following a link. China is at the lowest end of the independent research gamut, with 54% of its users reaching websites through their own research, but even this lower rate shows a favorability among consumers to visit a website based on their own findings instead of recommendations made to them.
Japan and the US follow Italy, with a respective 81% and 80% of users landing on a website through independent research.
Organic Search Traffic Dominates in the US, Italy and Japan
Organic search traffic (SEO) overshadows paid search, affiliate marketing and other acquisition sources in the US, Italy and Japan. This is due to the dominance of free acquisition in these 3 countries, raking in over 40% of user acquisition in these 3 countries, with a massive 70% in Japan.
Traffic from SEO has the highest influence in Japan, with 48% of traffic coming from organic search. Italy ranks in second on SEO acquisition, with 40% of consumers reaching websites this way and the US comes in at third, with 32%.
Reel in Traffic with Display Ads in China
Gaining site in traffic is heavily dependent on display ads, along with the Baidu Brand Zone technology. Procuring 28.2% of all traffic acquisition in China, this channel is a force to be reckoned with in order to increase site visitors. While globally, there is far less dependence on this channel (only 4.1%), in China it is a key player in obtaining traffic. Display ads go in tandem with this channel and also fall within the trend of using visuals to keep users interested.
Email Marketing and Social Reign Supreme in the UK
In the UK, customer acquisition is contingent on social marketing efforts. At 12.4%, social customer engagement spurs twice as much traffic in the UK as it does in any of the other countries surveyed. Aside from social, email campaigns are also drivers of successful traffic, raking in 6.7% on desktop and a heaping 18.4% on mobile. Organic search traffic lags behind in the UK, as far as traffic is concerned, accounting for only 23.1% of traffic, as opposed to the global 31.5% global ranking.
France is All About Paid Tactics
Whether it’s coming from SEM, PPC or paid social, paid tactics are driving up traffic in France. Paid channels account for almost half of all French traffic at 45%. This traffic mainly comes from paid search, which rakes in 29% of the traffic. SEM in France brings in roughly a third more in traffic than in all the other countries we analyzed. A significant part of the traffic in France is wrought by paid social — 8.4%, as opposed to the global average of 4.7%.
German Traffic: Paid Search and Direct
German traffic acquisition is dominated by two sources: paid search and direct traffic. Paid search yields 27.3% of all traffic in the country, while direct traffic is even more powerful in drawing in users, as it’s higher in Germany than any of the other 6 countries at 26.1%. The direct traffic average globally is at 21.9%. High direct traffic visitations suggest that visitors in this country have a vested interest and loyalty in big-name brands.
Optimizing The Landing Page — Whatever The Traffic Channel
Understanding how your site acquires visitors, who might later become customers, is as crucial as studying the UX of your website. After all, no matter how ideal your UX is, it won’t matter if little to no one arrives at your website. As such, acquisition channels provide a kind of hook, line and sinker approach where acquisition is concerned.
Acquisition channels are markedly useful and necessary for drawing in customers, but you must remember their limited scope in your overall digital marketing strategy. As their name suggests, they are good for acquisition but have little to do with retention. These channels may even hurt your UX and thereby conversions if these channels redirect visitors to irrelevant pages.
This is why the landing page is a critical aspect of acquisition — and retention. A landing page that’s relevant and optimized for users will maintain a good UX and digital happiness. So make sure to study the elements of your landings pages and see which ones are detrimental to the customer journey. There’s no point in optimizing acquisition only to lose your customers later on.
How Customer Behavior Analysis Can Help You Understand Your Customers
Wouldn’t it be nice to gain access to your customer’s every behavior on your website, much like search engines (Google, etc.) extract all the goings-on in your site through their crawling process?
Accessing a deep read of your customer’s digital experience will allow you to know where they’re struggling, as well as where they’re kept engaged and digitally happy.
This is of the essence where user experience (UX) is concerned, enabling brands to create experiences that delight and add value to their customers’ lives. It’s even more crucial when you consider that a visitor who has a bad experience is unlikely to return to a website, much less convert.
Visitors to a site communicate their frustration and satisfaction with every click, hover and tap — tracking these behaviors is the first step towards deciphering the digital conversation to help them achieve their goals.
What is Customer Behavior Analysis?
Customer behavior analysis has a rather self-evident purpose: the methods of analyzing user behaviors of a particular website. It reveals the areas of a site that users engage with, their points of friction and hesitation, and where they show interest or unsurety. It also refers to a slew of other behaviors such as how they click, tap or scroll, empowering you to better understand the impact of your website’s User Experience (UX).
The data and metrics of customer behavior analysis allow brands and marketers to make informed decisions on how to communicate with their audience, along with improving the customer journey on their digital platforms. User behavior analysis pivots you forward in optimizing both the UX of your website, your conversion rates and producing desired customer behaviors (purchases, sign-ups, engagement, etc).
In this way, understanding your customers can spur brand loyalty, in an optimized site, that is. If you understand where users are struggling, you’ll know exactly what to tweak to maintain a healthy brand perception. This keeps visitors engaged with your site and then making their way back to it, the foundation for brand loyalty.
The following is an examination of customer behaviors and their accompanying metrics for a behavioral analysis.
Zooming in on Visiting Manners
We’ll start with the basics; in order to extract insights about visitor behavior, we begin with their visit to your website. Now that they’ve made it to your site, you ought to parse the way they spend their visits and the way they leave, such as through bouncing. This behavior will help you arrive at the elements — whether specific zones or overall design of a page — that need improvement.
Metrics that capture the manners of user visits:
- Visit Time – This metric determines the duration of each session spent on your site. It is a measure of the average time visitors spend from their entry on the site to their exit. It is useful to have, as it can show you how visit duration varies based on unique customer journeys.
- Bounce Rate – The bounce rate shows the stickiness of your website along with the interest users have in the site or offering. The calculation is the ratio between the visitors who entered the site and left it without visiting another page. You should know that if a user scrolls, clicks through images and reads content, but doesn’t make it to a second page, it qualifies as a bounce.
Content Awareness & Views to Establish Your Brand
It is needless to say that if your site visitors don’t see your content, they won’t engage with it, let alone convert. That’s why you need to be kept informed on whether they see certain elements and to know the time they spent viewing them. This behavior is necessary to follow since it shows you how much of your content is known to your users. Before the users engage or hesitate, they come into view with your content, as it enters their consciousness… or not, so you have to measure to be certain.
Metrics that capture points of user awareness:
- Exposure Time – Showing the average time that zone was viewed during a page view, this metric pins down the zones that were viewed the longest. This is important in gauging a visitor’s’ awareness and viewing habits of your content, since it allows you to see which sections they are scrolling past and possibly ignoring.
- Exposure Rate – Identifying how far down a page your visitors are scrolling, this metric tells you how much of your creative content visitors are actually exposed to.
Hesitation: A Behavior Signaling Confusion or Interest in the Content
User hesitation is defined by inactivity while at or around a clickable or interactive element. It reveals your site visitors’ inactivity within areas that would typically require some kind of action. This is also important to record as it shows whether your content is easily understood or leads visitors to pause, or hesitate.
Metrics that capture points of hesitation:
- Hesitation Time – the time elapsed between the last hover and the first click on a zone. This metric helps you understand if your customers are hesitating because they have trouble understanding or accessing your content. However, it may also reveal that they are interested in the content on which they are hesitating.
- Float Time – pointing to the average time spent hovering over an element, this metric also reveals if your users are digesting your content or are confused by it. Since it can represent either interest or confusion, it’s vital to take the type of element being looked at into consideration. Ex: High float times are positive for images viewed, negative when on a CTA.
These metrics should lead you to consider — of the people who hesitate, are they understanding your content? Once you know where your users are hesitating, you can make a move to tackle this hypothetical, from where you can optimize the hesitated elements of your UX.
Engagement: Showing How Well Your Elements Are Understood
Engagement can easily be seen as the opposite of hesitation, as it shows the points in which users are taking action with, or using, site elements. Engagement is a critical behavior to keep track of, as it conveys how intuitive site elements are. When an element is intuitive, it has a high capacity for demonstrating how it should be used by its design alone. For example, a CTA should be easy to see as a clickable element.
Metrics that capture points of engagement:
- Engagement Rate- Relays how intuitive an element is, determined by the number of page views with a click on the zone divided by the number of page views with a hover on the zone. Essentially, it tells you how well your users are engaging with a site element. Getting insight into this behavior allows you to understand if your site elements are doing their job, or at least appear to be. Ex: a clickable element must look clickable, otherwise, no one will engage, i.e., click on it.
- Click Recurrence- Measuring engagement and frustration, this metric shows the average number of times an element was clicked when engaged with during a page view. It’s calculated by the total of clicks on the zone / total number of page views with at least one click on the zone. It allows you to understand if a page element was satisfying or frustrating for your users. It also shows you if users are trying to engage with non- clickable elements. If so, you should change such elements accordingly.
Conversions: A UX Behavior in Itself
The behavior at the very bottom of the sales funnel and every brand’s ultimate goal for their site visitors, conversions need little introduction. These can be segmented as an overall user behavior, one that signifies the highest level of interest with your products.
Metrics that capture points of conversion:
- Conversion rate per click – this metric is able to help you decide if there is an impact on your behavior or conversion goal when a zone gets clicked. As such, it only applies to clickable zones. The calculation is the number of users who click on a zone and accomplished the behavior divided by the number of users who clicked on the zone. You can use this metric to see which zones are helping customers achieve the goal of clicking on a product page. If on a product page, this metric shows which zones help customers add to their carts.
- Conversion rate per hover – similar to the above metric, this one shows you if hovering over a zone impacts the behavior or conversion goal. It’s measured by the number of users who accomplished the behavior and hovered over the zone / number of users who hovered the zone. It helps you decide if hovering over a product’s details result in a high or higher conversion rate.
Customer Behavior Analysis: The First Towards UX Optimization
Site behavior can be measured through a variety of metrics, the more nuanced they are, the more precisely you can understand why your consumers and site visitors behave the way they do. As you can see, each behavior is not only measured by a single metric, in fact there are many more that can be attributed to the broader sense of a behavior. Thus, each behavior is not limited to the metrics laid out in this article. Scoping them out on your website is the first step towards UX optimization, achieving digital happiness for your customers and potential customers and ultimately attaining more conversions.