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Autres articles (54)
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Supporting all media types
13 avril 2011, par kent1Unlike most software and media-sharing platforms, MediaSPIP aims to manage as many different media types as possible. The following are just a few examples from an ever-expanding list of supported formats : images : png, gif, jpg, bmp and more audio : MP3, Ogg, Wav and more video : AVI, MP4, OGV, mpg, mov, wmv and more text, code and other data : OpenOffice, Microsoft Office (Word, PowerPoint, Excel), web (html, CSS), LaTeX, Google Earth and (...)
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Librairies et logiciels spécifiques aux médias
10 décembre 2010, par kent1Pour un fonctionnement correct et optimal, plusieurs choses sont à prendre en considération.
Il est important, après avoir installé apache2, mysql et php5, d’installer d’autres logiciels nécessaires dont les installations sont décrites dans les liens afférants. Un ensemble de librairies multimedias (x264, libtheora, libvpx) utilisées pour l’encodage et le décodage des vidéos et sons afin de supporter le plus grand nombre de fichiers possibles. Cf. : ce tutoriel ; FFMpeg avec le maximum de décodeurs et (...) -
List of compatible distributions
26 avril 2011, par kent1The table below is the list of Linux distributions compatible with the automated installation script of MediaSPIP. Distribution nameVersion nameVersion number Debian Squeeze 6.x.x Debian Weezy 7.x.x Debian Jessie 8.x.x Ubuntu The Precise Pangolin 12.04 LTS Ubuntu The Trusty Tahr 14.04
If you want to help us improve this list, you can provide us access to a machine whose distribution is not mentioned above or send the necessary fixes to add (...)
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What is Web Log Analytics and Why You Should Use It
26 juin 2024, par ErinCan’t use JavaScript tracking on your website ? Need a more secure and privacy-friendly way to understand your website visitors ? Web log analytics is your answer. This method pulls data directly from your server logs, offering a secure and privacy-respecting alternative.
In this blog, we cover what web log analytics is, how it compares to JavaScript tracking, who it is best suited for, and why it might be the right choice for you.
What are server logs ?
Before diving in, let’s start with the basics : What are server logs ? Think of your web server as a diary that notes every visit to your website. Each time someone visits, the server records details like :
- User agent : Information about the visitor’s browser and operating system.
- Timestamp : The exact time the request was made.
- Requested URL : The specific page or resource the visitor requested.
These “diary entries” are called server logs, and they provide a detailed record of all interactions with your website.
Server log example
Here’s what a server log looks like :
192.XXX.X.X – – [24/Jun/2024:14:32:01 +0000] “GET /index.html HTTP/1.1” 200 1024 “https://www.example.com/referrer.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:02 +0000] “GET /style.css HTTP/1.1” 200 3456 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:03 +0000] “GET /script.js HTTP/1.1” 200 7890 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
192.XXX.X.X – – [24/Jun/2024:14:32:04 +0000] “GET /images/logo.png HTTP/1.1” 200 1234 “https://www.example.com/index.html” “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
Breakdown of the log entry
Each line in the server log represents a single request made by a visitor to your website. Here’s a detailed breakdown of what each part means :
- IP Address : 192.XXX.X.X
- This is the IP address of the visitor’s device.
- User Identifier : – –
- These fields are typically used for user identification and authentication, which are not applicable here, hence the hyphens.
- Timestamp : [24/Jun/2024:14:32:01 +0000]
- The date and time of the request, including the timezone.
- Request Line : “GET /index.html HTTP/1.1”
- The request method (GET), the requested resource (/index.html), and the HTTP version (HTTP/1.1).
- Response Code : 200
- The HTTP status code indicates the result of the request (200 means OK).
- Response Size : 1024
- The size of the response in bytes.
- Referrer : “https://www.example.com/referrer.html“
- The URL of the referring page that led the visitor to the current page.
- User Agent : “Mozilla/5.0 (Windows NT 10.0 ; Win64 ; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36”
- Information about the visitor’s browser and operating system.
In the example above, there are multiple log entries for different resources (HTML page, CSS file, JavaScript file, and an image). This shows that when a visitor loads a webpage, multiple requests are made to load all the necessary resources.
What is web log analytics ?
Web log analytics is one of many methods for tracking visitors to your site.
Web log analytics is the process of analysing server log files to track and understand website visitors. Unlike traditional methods that use JavaScript tracking codes embedded in web pages, web log analytics pulls data directly from these server logs.
How it works :
- Visitor request : A visitor’s browser requests your website.
- Server logging : The server logs the request details.
- Analysis : These logs are analysed to extract useful information about your visitors and their activities.
Web log analytics vs. JavaScript tracking
JavaScript tracking
JavaScript tracking is the most common method used to track website visitors. It involves embedding a JavaScript code snippet into your web pages. This code collects data on visitor interactions and sends it to a web analytics platform.
Differences and benefits :
Privacy :
- Web log analytics : Since it doesn’t require embedding tracking codes, it is considered less intrusive and helps maintain higher privacy standards.
- JavaScript tracking : Embeds tracking codes directly on your website, which can be more invasive and raise privacy concerns.
Ease of setup :
- Web log analytics : No need to modify your website’s code. All you need is access to your server logs.
- JavaScript tracking : Requires adding tracking code on your web pages. This is generally an easier setup process.
Data collection :
- Web log analytics : Contain requests of users with adblockers (ghostery, adblock, adblock plus, privacy badger, etc.) sometimes making it more accurate. However, it may miss certain interactive elements like screen resolution or user events. It may also over-report data.
- JavaScript tracking : Can collect a wide range of data, including Custom dimensions, Ecommerce tracking, Heatmaps, Session recordings, Media and Form analytics, etc.
Why choose web log analytics ?
Enhanced privacy
Avoiding embedded tracking codes means there’s no JavaScript running on your visitors’ browsers. This significantly reduces the risk of data leakage and enhances overall privacy.
Comprehensive data collection
It isn’t affected by ad blockers or browser tracking protections, ensuring you capture more complete and accurate data about your visitors.
Historical data analysis
You can import and analyse historical log files, giving you insights into long-term visitor behaviour and trends.
Simple setup
Since it relies on server logs, there’s no need to alter your website’s code. This makes setup straightforward and minimises potential technical issues.
Who should use web log analytics ?
Web log analytics is particularly suited for businesses that prioritise data privacy and security.
Organisations that handle sensitive data, such as banks, healthcare providers, and government agencies, can benefit from the enhanced privacy.
By avoiding JavaScript tracking, these entities minimise data exposure and comply with strict privacy regulations like Sarbanes Oxley and PCI.
Why use Matomo for web log analytics ?
Matomo stands out as a top choice for web log analytics because it prioritises privacy and data ownership
Here’s why :
- Complete data control : You own all your data, so you don’t have to worry about third-party access.
- IP anonymisation : Matomo anonymises IP addresses to further protect user privacy.
- Bot filtering : Automatically excludes bots from your reports, ensuring you get accurate data.
- Simple migration : You can easily switch from other tools like AWStats by importing your historical logs into Matomo.
- Server log recognition : Recognises most server log formats (Apache, Nginx, IIS, etc.).
Start using web log analytics
Web log analytics offers a secure, privacy-focused alternative to traditional JavaScript tracking methods. By analysing server logs, you get valuable insights into your website traffic while maintaining high privacy standards.
If you’re serious about privacy and want reliable data, give Matomo’s web log analytics a try.
Start your 21-day free trial now. No credit card required.
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21 day free trial. No credit card required.
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A Guide to Bank Customer Segmentation
18 juillet 2024, par ErinBanking customers are more diverse, complex, and demanding than ever. As a result, banks have to work harder to win their loyalty, with 75% saying they would switch to a bank that better fits their needs.
The problem is banking customers’ demands are increasingly varied amid economic uncertainties, increased competition, and generational shifts.
If banks want to retain their customers, they can’t treat them all the same. They need a bank customer segmentation strategy that allows them to reach specific customer groups and cater to their unique demands.
What is customer segmentation ?
Customer segmentation divides a customer base into distinct groups based on shared characteristics or behaviours.
This allows companies to analyse the behaviours and needs of different customer groups. Banks can use these insights to target segments with relevant marketing throughout the customer cycle, e.g., new customers, inactive customers, loyal customers, etc.
You combine data points from multiple segmentation categories to create a customer segment. The most common customer segmentation categories include :
- Demographic segmentation
- Website activity segmentation
- Geographic segmentation
- Purchase history segmentation
- Product-based segmentation
- Customer lifecycle segmentation
- Technographic segmentation
- Channel preference segmentation
- Value-based segmentation
By combining segmentation categories, you can create detailed customer segments. For example, high-value customers based in a particular market, using a specific product, and approaching the end of the lifecycle. This segment is ideal for customer retention campaigns, localised for their market and personalised to satisfy their needs.
Matomo’s privacy-centric web analytics solution helps you capture data from the first visit. Unlike Google Analytics, Matomo doesn’t use data sampling (more on this later) or AI to fill in data gaps. You get 100% accurate data for reliable insights and customer segmentation.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Why is customer segmentation important for banks ?
Customer segmentation allows you to address the needs of specific groups instead of treating all of your customers the same. This has never been more important amid a surge in bank switching, with three in four customers ready to switch to a provider that better suits their needs.
Younger customers are the most likely to switch, with 19% of 18-24 year olds changing their primary bank in the past year (PDF).
Customer expectations are changing, driven by economic uncertainties, declining trust in traditional banking, and the rise of fintech. Even as economic pressures lift, banks need to catch up with the demands of maturing millennials, Gen Z, and future generations of banking customers.
Switching is the new normal, especially for tech-savvy customers encouraged by an expanding world of digital banking options.
To retain customers, banks need to know them better and understand how their needs change over time. Customer retention provides the insights banks need to understand these needs at a granular level and the means to target specific customer groups with relevant messages.
At its core, customer segmentation is essential to banks for two key reasons :
- Customer retention : Holding on to customers for longer by satisfying their personal needs.
- Customer lifetime value : Maximising ongoing customer revenue through retention, purchase frequency, cross-selling, and upselling.
Here are some actionable bank customer segmentation strategies that can achieve these two objectives :
Prevent switching with segment analysis
Use customer segmentation to prevent them from switching to rivals by knowing what they want from you. Analyse customer needs and how they change throughout the lifecycle. Third-party data reveals general trends, but what do your customers want ?
Use first-party customer data and segmentation to go beyond industry trends. Know exactly what your customers want from you and how to deliver targeted messages to each segment — e.g., first-time homebuyers vs. retirement planners.
Keep customers active with segment targeting
Target customer segments to keep customers engaged and motivated. Create ultra-relevant marketing messages and deliver them with precision to distinct customer segments. Nurture customer motivation by continuing to address their problems and aspirations.
Improve the quality of services and products
Knowing your customers’ needs in greater detail allows you to adapt your products and messages to cater to the most important segments. Customers switch banks because they feel their needs are better met elsewhere. Prevent this by implementing customer segmentation insights into product development and marketing.
Personalise customer experiences by layering segments
Layer segments to create ultra-specific target customer groups for personalised services and marketing campaigns. For example, top-spending customers are one of your most important segments, but there’s only so much you can do with this. However, you can divide this group into even narrower target audiences by layering multiple segments.
For example, segmenting top-spending customers by product type can create more relevant messaging. You can also segment recent activity and pinpoint specific usage segments, such as those with a recent drop in transactions.
Now, you have a three-layered segment of high-spending customers who use specific products less often and whom you can target with re-engagement campaigns.
Maximise customer lifetime value
Bringing all of this together, customer segmentation helps you maximise customer lifetime value in several ways :
- Prevent switching
- Enhance engagement and motivation
- Re-engage customers
- Cross-selling, upselling
- Personalised customer loyalty incentives
The longer you retain customers, the more you can learn about them, and the more effective your lifetime value campaigns will be.
Balancing bank customer segmentation with privacy and marketing regulations
Of course, customer segmentation uses a lot of data, which raises important legal and ethical questions. First, you need to comply with data and privacy regulations, such as GDPR and CCPA. Second, you also have to consider the privacy expectations of your customers, who are increasingly aware of privacy issues and rising security threats targeting financial service providers.
If you aim to retain and maximise customer value, respecting their privacy and protecting their data are non-negotiables.
Regulators are clamping down on finance
Regulatory scrutiny towards the finance industry is intensifying, largely driven by the rise of fintech and the growing threat of cyber attacks. Not only was 2023 a record-breaking year for finance security breaches but several compromises of major US providers “exposed shortcomings in the current supervisory framework and have put considerable public pressure on banking authorities to reevaluate their supervisory and examination programs” (Deloitte).
Banks face some of the strictest consumer protections and marketing regulations, but the digital age creates new threats.
In 2022, the Consumer Financial Protection Bureau (CFPB) warned that digital marketers must comply with finance consumer protections when targeting audiences. CFPB Director Rohit Chopra said : “When Big Tech firms use sophisticated behavioural targeting techniques to market financial products, they must adhere to federal consumer financial protection laws.”
This couldn’t be more relevant to customer segmentation and the tools banks use to conduct it.
Customer data in the hands of agencies and big tech
Banks should pay attention to the words of CFPB Director Rohit Chopra when partnering with marketing agencies and choosing analytics tools. Digital marketing agencies are rarely experts in financial regulations, and tech giants like Google don’t have the best track record for adhering to them.
Google is constantly in the EU courts over its data use. In 2022, the EU ruled that the previous version of Google Analytics violated EU privacy regulations. Google Analytics 4 was promptly released but didn’t resolve all the issues.
Meanwhile, any company that inadvertently misuses Google Analytics is legally responsible for its compliance with data regulations.
Banks need a privacy-centric alternative to Google Analytics
Google’s track record with data regulation compliance is a big issue, but it’s not the only one. Google Analytics uses data sampling, which Google defines as the “practice of analysing a subset of data to uncover meaningful information from a larger data set.”
This means Google Analytics places thresholds on how much of your data it analyses — anything after that is calculated assumptions. We’ve explained why this is such a problem before, and GA4 relies on data sampling even more than the previous version.
In short, banks should question whether they can trust Google with their customer data and whether they can trust Google Analytics to provide accurate data in the first place. And they do. 80% of financial marketers say they’re concerned about ad tech bias from major providers like Google and Meta.
Matomo is the privacy-centric alternative to Google Analytics, giving you 100% data ownership and compliant web analytics. With no data sampling, Matomo provides 20-40% more data to help you make accurate, informed decisions. Get the data you need for customer segmentation without putting their data at risk.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Bank customer segmentation examples
Now, let’s look at some customer segments you create and layer to target specific customer groups.
Visit-based segmentation
Visit segmentation filters audiences based on the pages they visit on your website and the behaviors they exhibit—for example, first-time visitors vs. returning visitors or landing page visitors vs. blog page visitors.
If you look at HSBC’s website, you’ll see it is structured into several categories for key customer personas. One of its segments is international customers living in the US, so it has pages and resources expats, people working in the US, people studying in the US, etc.
By combining visit-based segmentation with ultra-relevant pages for specific target audiences, HSBC can track each group’s demand and interest and analyse their behaviours. It can determine which audiences are returning, which products they want, and which messages convert them.
Demographic segmentation
Demographic segmentation divides customers by attributes such as age, gender, and location. However, you can also combine these insights with other non-personal data to better understand specific audiences.
For example, in Matomo, you can segment audiences based on the language of their browser, the country they’re visiting from, and other characteristics. So, in this case, HSBC could differentiate between visitors already residing in the US and those outside of the country looking for information on moving there.
It could determine which countries they’re visiting, which languages to localise for, and which networks to run ultra-relevant social campaigns on.
Interaction-based segmentation
Interaction-based segmentation uses events and goals to segment users based on their actions on your website. For example, you can segment audiences who visit specific URLs, such as a loan application page, or those who don’t complete an action, such as failing to complete a form.
With events and goals set up, you can track the actions visitors complete before making purchases. You can monitor topical interests, page visits, content interactions, and pathways toward conversions, which feed into their customer journey.
From here, you can segment customers based on their path leading up to their first purchase, follow-up purchases, and other actions.
Purchase-based segmentation
Purchase-based segmentation allows you to analyse the customer behaviours related to their purchase history and spending habits. For example, you can track the journey of repeat customers or identify first-time buyers showing interest in other products/services.
You can implement these insights into your cross-selling and upselling campaigns with relevant messages designed to increase retention and customer lifetime value.
Get reliable website analytics for your bank customer segmentation needs
With customers switching in greater numbers, banks need to prioritise customer retention and lifetime value. Customer segmentation allows you to target specific customer groups and address their unique needs — the perfect strategy to stop them from moving to another provider.
Quality, accurate data is the key ingredient of an effective bank customer segmentation strategy. Don’t accept data sampling from Google Analytics or any other tool that limits the amount of your own data you can access. Choose a web analytics tool like Matamo that unlocks the full potential of your website analytics to get the most out of bank customer segmentation.
Matomo is trusted by over 1 million websites globally, including many banks, for its accuracy, compliance, and reliability. Discover why financial institutions rely on Matomo to meet their web analytics needs.
Start collecting the insights you need for granular, layered segmentation — without putting your bank customer data at risk. Request a demo of Matomo now.
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7 Benefits Segmentation Examples + How to Get Started
26 mars 2024, par ErinEvery copywriter knows the importance of selling a product’s benefits, not its features. So why should your marketing efforts be different ?
Answer : they shouldn’t.
It’s time to stop using demographic or behavioural traits to group customers and start using benefits segmentation instead.
Benefits segmentation groups your customers based on the value they get from your product or service. In this article, we’ll cover seven real-life examples of benefits segmentation, explain why it’s so powerful and show how to get started today.
What is benefits segmentation ?
Benefits segmentation is a way for marketers to group their target market based on the value they get from their products or services. It is a form of customer segment marketing. Other types of market segmentation include :
- Geographic segmentation
- Demographic segmentation
- Psychographic segmentation
- Behavioural segmentation
- Firmographic segmentation
Customers could be the same age, from the same industry and live in the same location but want drastically different things from the same product. Some may like the design of your products, others the function, and still more the price.
Whatever the benefits, you can make your marketing more effective by building advertising campaigns around them.
Why use benefits segmentation ?
Appealing to the perceived benefits of your product is a powerful marketing strategy. Here are the advantages of you benefit segmentation can expect :
More effective marketing campaigns
Identifying different benefits segments lets you create much more targeted marketing campaigns. Rather than appeal to a broad customer base, you can create specific ads and campaigns that speak to a small part of your target audience.
These campaigns tend to be much more powerful. Benefits-focused messaging better resonates with your audience, making potential customers more likely to convert.
Better customer experience
Customers use your products for a reason. By showing you understand their needs through benefits segmentation, you deliver a much better customer experience — in terms of messaging and how you develop new products.
In today’s world, experience matters. 80% of customers say a company’s experience is as important as its products and services.
Stronger customer loyalty
When products or services are highly targeted at potential customers, they are more likely to return. More than one-third (36%) of customers would return to a brand if they had a positive experience, even if cheaper or more convenient alternatives exist.
Using benefits segmentation will also help you attract the right kind of people in the first place — people who will become long-term customers because your benefits align with their needs.
Improved products and services
Benefits segmentation makes it easier to tailor products or services to your audiences’ wants and needs.
Rather than creating a product meant to appeal to everyone but doesn’t fulfil a real need, your team can create different ranges of the same product that target different benefits segments.
Higher conversion rates
Personalising your pitch to individual customers is powerful. It drives performance and creates better outcomes for your target customer. Companies that grow faster drive 40 per cent more revenue from personalisation than their slower-growing counterparts.
When sales reps understand your product’s benefits, talking to customers about them and demonstrating how the product solves particular pain points is much easier.
In short, benefits segmentation can lead to higher conversion rates and a better return on investment.
7 examples of benefits segmentation
Let’s take a look at seven examples of real-life benefits segmentation to improve your understanding :
Nectar
Mattress manufacturer Nectar does a great job segmenting their product range by customer benefits. That’s a good thing, given how many different things people want from their mattress.
It’s not just a case of targeting back sleepers vs. side sleepers ; they focus on more specific benefits like support and cooling.
Take a look at the screenshot above. Nectar mentions the benefits of each mattress in multiple places, making it easy for customers to find the perfect mattress. If you care about value, for example, you might choose “The Nectar.” If pressure relief and cooling are important to you, you might pick the “Nectar Premier.”
24 Hour Fitness
A gym is a gym is a gym, right ? Not when people use it to achieve different goals, it’s not. And that’s what 24 Hour Fitness exploits when they sell memberships to their audience.
As you can see from its sales page, 24 Hour Fitness targets the benefits that different customers get from their products :
Customers who just care about getting access to weights and treadmills for as cheap as possible can buy the Silver Membership.
But getting fit isn’t the only reason people go to the gym. That’s why 24 Hour Fitness targets its Gold Membership to those who want the “camaraderie” of studio classes led by “expert instructors.”
Finally, some people value being able to access any club, anywhere in the country. Consumers value flexibility greatly, so 24 Hour Fitness limits this perk to its top-tier membership.
Notion
Notion is an all-in-one productivity and note-taking app that aims to be the only productivity tool people and teams need. Trying to be everything to all people rarely works, however, which is why Notion cleverly tweaks its offering to appeal to the desires of different customer segments :
For price-conscious individuals, it provides a pared solution that doesn’t bloat the user experience with features or benefits these consumers don’t care about.
The Plus tier is the standard offering for teams who need a way to collaborate online. Still, there are two additional tiers for businesses that target specific benefits only certain teams need.
For teams that benefit from a longer history or additional functionality like a bulk export, Notion offers the Business tier at almost double the price of the standard Plus tier. Finally, the Enterprise tier for businesses requires much more advanced security features.
Apple
Apple is another example of a brand that designs and markets products to customers based on specific benefits.
Why doesn’t Apple just make one really good laptop ? Because customers want different things from them. Some want the lightest or smallest laptop possible. Others need ones with higher processing power or larger screens.
One product can’t possibly deliver all those benefits. So, by understanding the precise reasons people need a laptop, Apple can create and market products around the benefits that are most likely to be sold.
Tesla
In the same way Apple understands that consumers need different things from their laptops, Tesla understands that consumers derive different benefits from their cars.
It’s why the company sells four cars (and now a truck) that cover various sizes, top speeds, price points and more.
Tesla even asks customers about the benefits they want from their car when helping them to choose a vehicle. By asking customers to pick how they will use their new vehicle, Tesla can ensure the car’s benefits match up to the consumers’ goals.
Dynamite Brands
Dynamite Brands is a multi-brand, community-based business that targets remote entrepreneurs around the globe. But even this heavily niched-down business still needs to create benefit segments to serve its audience better.
It’s why the company has built several different brands instead of trying to serve every customer under a single banner :
If you just want to meet other like-minded entrepreneurs, you can join the Dynamite Circle, for example. But DC Black might be a better choice if you care more about networking and growing your business.
It’s the same with the two recruiting brands. Dynamite Jobs targets companies that just want access to a large talent pool. Remote First Recruiting targets businesses that benefit from a more hands-on approach to hiring where a partner does the bulk of the work.
Garmin
Do you want your watch to tell the time or do you want it to do more ? If you fall into the latter category, Garmin has designed dozens of watches that target various benefits.
Do you want a watch that tracks your fitness without looking ugly ? Buy the Venu.
Want a watch designed for runners ? Buy the Forerunner.
Do you need a watch that can keep pace with your outdoor lifestyle ? Buy the Instinct.
Just like Apple, Garmin can’t possibly design a single watch that delivers all these benefits. Instead, each watch is carefully built for the target customer’s needs. Yes, it makes the target market smaller, but it makes the product more appealing to those who care about those benefits.
How to get started with benefits segmentation
According to Gartner, 63% of digital marketing leaders struggle with personalisation. Don’t be one of them. Here’s how you can improve your personalisation efforts using benefits segmentation.
Research and define benefits
The first step to getting started with benefit segmentation is understanding all the benefits customers get from your products.
You probably already know some of the benefits, but don’t underestimate the importance of customer research. Hold focus groups, survey customers and read customer reviews to discover what customers love about your products.
Create benefit-focused customer personas
Now you understand the benefits, it’s time to create customer personas that reflect them. Group consumers who like similar benefits and see if they have any other similarities.
Price-conscious consumers may be younger. Maybe people who care about performance have a certain type of job. The more you can do to flesh out what the average benefits-focused consumer looks like, the easier it will be to create campaigns.
Create campaigns focused on each benefit
Now, we get to the fun part. Make the benefit-focused customer personas you created in the last step the focus of your marketing campaigns going forward.
Don’t try to appeal to everyone. Just make your campaigns appeal to these people.
Go deeper with segmentation analytics
The quality of your benefit segmentation strategy hinges on the quality of your data. That’s why using a an accurate web analytics solution like Matomo to track how each segment behaves online using segmentation analytics is important.
This data can make your marketing campaigns more targeted and effective.
Benefits segmentation in practice
Let’s say you have an e-commerce website selling a wide range of household items, and you want to create a benefit segment for “Tech Enthusiasts” who are interested in the latest gadgets and cutting-edge technology. You want to track and analyse their behaviour separately to tailor marketing campaigns or website content specifically for this group.
- Identify characteristics : Determine key characteristics or behaviours that define the “Tech Enthusiasts” segment.
This might include frequent visits to product pages of the latest tech products, site searches that contain different tech product names, engaging with tech-specific content in emails or spending more time on technology-related blog posts.
One quick and surefire way to identify characteristics of a segment is to look historically at specific tech product purchases in your Matomo and work your way backwards to find out what steps a “Tech Enthusiast” takes before making a purchase. For instance, you might look at User Flows to discover this.
- Create segments in Matomo : Using Matomo’s segmentation features, you can create a segment that includes users exhibiting these characteristics. For instance :
- Segment by page visits : Create a segment that includes users who visited tech product pages or spent time on tech blogs.
- Segment by event tracking : If you’ve set up event tracking for specific actions (like clicking on “New Tech” category buttons), create a segment based on these events.
- Combine conditions : Combine various conditions (e.g., pages visited, time spent, specific actions taken) to create a comprehensive segment that accurately represents “Tech Enthusiasts.”
- Track and analyse : Apply this segment to your analytics data in Matomo to track and analyse the behaviour of this group separately. Monitor metrics like their conversion rates, time spent on site or specific products they engage with.
- Tailor marketing : Use the insights from analysing this segment to tailor marketing strategies. This could involve creating targeted campaigns or customising website content to cater specifically to these users.
Remember, the key is to define criteria that accurately represent the segment you want to target, use Matomo’s segmentation tools to isolate this group, and effectively derive actionable insights to cater to their preferences or needs.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
Track your segmentation efforts
Benefits segmentation is a fantastic way to improve your marketing. It can help you deliver a better customer experience, improve your product offering and help your sales reps close more deals.
Segmenting your audience with an analytics platform lets you go even deeper. But doing so in a privacy-sensitive way can be difficult.
That’s why over 1 million websites choose Matomo as their web analytics solution. Matomo provides exceptional segmentation capabilities while remaining 100% accurate and compliant with global privacy laws.
Find out how Matomo’s insights can level up your marketing efforts with our 21-day free trial, no credit card required.
Try Matomo for Free
21 day free trial. No credit card required.