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#3 The Safest Place
16 octobre 2011, par kent1
Mis à jour : Février 2013
Langue : English
Type : Audio
Tags : creative commons, Musique, mp3, Elephant dreams, soundtrack
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#4 Emo Creates
15 octobre 2011, par kent1
Mis à jour : Février 2013
Langue : English
Type : Audio
Tags : creative commons, Musique, mp3, Elephant dreams, soundtrack
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#2 Typewriter Dance
15 octobre 2011, par kent1
Mis à jour : Février 2013
Langue : English
Type : Audio
Tags : creative commons, Musique, mp3, Elephant dreams, soundtrack
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#1 The Wires
11 octobre 2011, par kent1
Mis à jour : Février 2013
Langue : English
Type : Audio
Tags : creative commons, Musique, mp3, Elephant dreams, soundtrack
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ED-ME-5 1-DVD
11 octobre 2011, par kent1
Mis à jour : Octobre 2011
Langue : English
Type : Audio
Tags : opensource, audio, open film making, Elephant dreams, ac3, karaoke
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Revolution of Open-source and film making towards open film making
6 octobre 2011, par kent1
Mis à jour : Juillet 2013
Langue : English
Type : Texte
Autres articles (99)
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Automated installation script of MediaSPIP
25 avril 2011, par kent1To overcome the difficulties mainly due to the installation of server side software dependencies, an "all-in-one" installation script written in bash was created to facilitate this step on a server with a compatible Linux distribution.
You must have access to your server via SSH and a root account to use it, which will install the dependencies. Contact your provider if you do not have that.
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Sur d’autres sites (13341)
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What is Behavioural Segmentation and Why is it Important ?
28 septembre 2023, par Erin — Analytics TipsAmidst the dynamic landscape of web analytics, understanding customers has grown increasingly vital for businesses to thrive. While traditional demographic-focused strategies possess merit, they need to uncover the nuanced intricacies of individual online behaviours and preferences. As customer expectations evolve in the digital realm, enterprises must recalibrate their approaches to remain relevant and cultivate enduring digital relationships.
In this context, the surge of technology and advanced data analysis ushers in a marketing revolution : behavioural segmentation. Businesses can unearth invaluable insights by meticulously scrutinising user actions, preferences and online interactions. These insights lay the foundation for precisely honed, high-performing, personalised campaigns. The era dominated by blanket, catch-all marketing strategies is yielding to an era of surgical precision and tailored engagement.
While the insights from user behaviours empower businesses to optimise customer experiences, it’s essential to strike a delicate balance between personalisation and respecting user privacy. Ethical use of behavioural data ensures that the power of segmentation is wielded responsibly and in compliance, safeguarding user trust while enabling businesses to thrive in the digital age.
What is behavioural segmentation ?
Behavioural segmentation is a crucial concept in web analytics and marketing. It involves categorising individuals or groups of users based on their online behaviour, actions and interactions with a website. This segmentation method focuses on understanding how users engage with a website, their preferences and their responses to various stimuli. Behavioural segmentation classifies users into distinct segments based on their online activities, such as the pages they visit, the products they view, the actions they take and the time they spend on a site.
Behavioural segmentation plays a pivotal role in web analytics for several reasons :
1. Enhanced personalisation :
Understanding user behaviour enables businesses to personalise online experiences. This aids with delivering tailored content and recommendations to boost conversion, customer loyalty and customer satisfaction.
2. Improved user experience :
Behavioural segmentation optimises user interfaces (UI) and navigation by identifying user paths and pain points, enhancing the level of engagement and retention.
3. Targeted marketing :
Behavioural segmentation enhances marketing efficiency by tailoring campaigns to user behaviour. This increases the likelihood of interest in specific products or services.
4. Conversion rate optimisation :
Analysing behavioural data reveals factors influencing user decisions, enabling website optimisation for a streamlined purchasing process and higher conversion rates.
5. Data-driven decision-making :
Behavioural segmentation empowers data-driven decisions. It identifies trends, behavioural patterns and emerging opportunities, facilitating adaptation to changing user preferences and market dynamics.
6. Ethical considerations :
Behavioural segmentation provides valuable insights but raises ethical concerns. User data collection and use must prioritise transparency, privacy and responsible handling to protect individuals’ rights.
The significance of ethical behavioural segmentation will be explored more deeply in a later section, where we will delve into the ethical considerations and best practices for collecting, storing and utilising behavioural data in web analytics. It’s essential to strike a balance between harnessing the power of behavioural segmentation for business benefits and safeguarding user privacy and data rights in the digital age.
Different types of behavioural segments with examples
- Visit-based segments : These segments hinge on users’ visit patterns. Analyse visit patterns, compare first-time visitors to returning ones, or compare users landing on specific pages to those landing on others.
- Example : The real estate website Zillow can analyse how first-time visitors and returning users behave differently. By understanding these patterns, Zillow can customise its website for each group. For example, they can highlight featured listings and provide navigation tips for first-time visitors while offering personalised recommendations and saved search options for returning users. This could enhance user satisfaction and boost the chances of conversion.
- Interaction-based segments : Segments can be created based on user interactions like special events or goals completed on the site.
- Example : Airbnb might use this to understand if users who successfully book accommodations exhibit different behaviours than those who don’t. This insight could guide refinements in the booking process for improved conversion rates.
- Campaign-based segments : Beyond tracking visit numbers, delve into usage differences of visitors from specific sources or ad campaigns for deeper insights.
- Example : Nike might analyse user purchase behaviour from various traffic sources (referral websites, organic, direct, social media and ads). This informs marketing segmentation adjustments, focusing on high-performance channels. It also customises the website experience for different traffic sources, optimising content, promotions and navigation. This data-driven approach could boost user experiences and maximise marketing impact for improved brand engagement and sales conversions.
- Ecommerce segments : Separate users based on purchases, even examining the frequency of visits linked to specific products. Segment heavy users versus light users. This helps uncover diverse customer types and browsing behaviours.
- Example : Amazon could create segments to differentiate between visitors who made purchases and those who didn’t. This segmentation could reveal distinct usage patterns and preferences, aiding Amazon in tailoring its recommendations and product offerings.
- Demographic segments : Build segments based on browser language or geographic location, for instance, to comprehend how user attributes influence site interactions.
- Example : Netflix can create user segments based on demographic factors like geographic location to gain insight into how a visitor’s location can influence content preferences and viewing behaviour. This approach could allow for a more personalised experience.
- Technographic segments : Segment users by devices or browsers, revealing variations in site experience and potential platform-specific issues or user attitudes.
- Example : Google could create segments based on users’ devices (e.g., mobile, desktop) to identify potential issues in rendering its search results. This information could be used to guide Google in providing consistent experiences regardless of device.
The importance of ethical behavioural segmentation
Respecting user privacy and data protection is crucial. Matomo offers features that align with ethical segmentation practices. These include :
- Anonymization : Matomo allows for data anonymization, safeguarding individual identities while providing valuable insights.
- GDPR compliance : Matomo is GDPR compliant, ensuring that user data is handled following European data protection regulations.
- Data retention and deletion : Matomo enables businesses to set data retention policies and delete user data when it’s no longer needed, reducing the risk of data misuse.
- Secured data handling : Matomo employs robust security measures to protect user data, reducing the risk of data breaches.
Real-world examples of ethical behavioural segmentation :
- Content publishing : A leading news website could utilise data anonymization tools to ethically monitor user engagement. This approach allows them to optimise content delivery based on reader preferences while ensuring the anonymity and privacy of their target audience.
- Non-profit organisations : A charity organisation could embrace granular user control features. This could be used to empower its donors to manage their data preferences, building trust and loyalty among supporters by giving them control over their personal information.
Examples of effective behavioural segmentation
Companies are constantly using behavioural insights to engage their audiences effectively. In this section, we’ll delve into real-world examples showcasing how top companies use behavioural segmentation to enhance their marketing efforts.
- Coca-Cola’s behavioural insights for marketing strategy : Coca-Cola employs behavioural segmentation to evaluate its advertising campaigns. Through analysing user engagement across TV commercials, social media promotions and influencer partnerships, Coca-Cola’s marketing team can discover that video ads shared by influencers generate the highest ROI and web traffic.
This insight guides the reallocation of resources, leading to increased sales and a more effective advertising strategy.
- eBay’s custom conversion approach : eBay excels in conversion optimisation through behavioural segmentation. When users abandon carts, eBay’s dynamic system sends personalised email reminders featuring abandoned items and related recommendations tailored to user interests and past purchase decisions.
This strategy revives sales, elevates conversion rates and sparks engagement. eBay’s adeptness in leveraging behavioural insights transforms user experience, steering a customer journey toward conversion.
- Sephora’s data-driven conversion enhancement : Data analysts can use Sephora’s behavioural segmentation strategy to fuel revenue growth through meticulous data analysis. By identifying a dedicated subset of loyal customers who exhibit a consistent preference for premium skincare products, data analysts enable Sephora to customise loyalty programs.
These personalised rewards programs provide exclusive discounts and early access to luxury skincare releases, resulting in heightened customer engagement and loyalty. The data-driven precision of this approach directly contributes to amplified revenue from this specific customer segment.
Examples of the do’s and don’ts of behavioural segmentation
Behavioural segmentation is a powerful marketing and data analysis tool, but its success hinges on ethical and responsible practices. In this section, we will explore real-world examples of the do’s and don’ts of behavioural segmentation, highlighting companies that have excelled in their approach and those that have faced challenges due to lapses in ethical considerations.
Do’s of behavioural segmentation :
- Personalised messaging :
- Example : Spotify
- Spotify’s success lies in its ability to use behavioural data to curate personalised playlists and user recommendations, enhancing its music streaming experience.
- Example : Spotify
- Transparency :
- Example : Basecamp
- Basecamp’s transparency in sharing how user data is used fosters trust. They openly communicate data practices, ensuring users are informed and comfortable.
- Example : Basecamp
- Anonymization
- Example : Matomo’s anonymization features
- Matomo employs anonymization features to protect user identities while providing valuable insights, setting a standard for responsible data handling.
- Example : Matomo’s anonymization features
- Purpose limitation :
- Example : Proton Mail
- Proton Mail strictly limits the use of user data to email-related purposes, showcasing the importance of purpose-driven data practices.
- Example : Proton Mail
- Dynamic content delivery :
- Example : LinkedIn
- LinkedIn uses behavioural segmentation to dynamically deliver job recommendations, showcasing the potential for relevant content delivery.
- Example : LinkedIn
- Data security :
- Example : Apple
- Apple’s stringent data security measures protect user information, setting a high bar for safeguarding sensitive data.
- Example : Apple
- Adherence to regulatory compliance :
- Example : Matomo’s regulatory compliance features
- Matomo’s regulatory compliance features ensure that businesses using the platform adhere to data protection regulations, further promoting responsible data usage.
- Example : Matomo’s regulatory compliance features
Don’ts of behavioural segmentation :
- Ignoring changing regulations
- Example : Equifax
- Equifax faced major repercussions for neglecting evolving regulations, resulting in a data breach that exposed the sensitive information of millions.
- Example : Equifax
- Sensitive attributes
- Example : Twitter
- Twitter faced criticism for allowing advertisers to target users based on sensitive attributes, sparking concerns about user privacy and data ethics.
- Example : Twitter
- Data sharing without consent
- Example : Meta & Cambridge Analytica
- The Cambridge Analytica scandal involving Meta (formerly Facebook) revealed the consequences of sharing user data without clear consent, leading to a breach of trust.
- Example : Meta & Cambridge Analytica
- Lack of control
- Example : Uber
- Uber faced backlash for its poor data security practices and a lack of control over user data, resulting in a data breach and compromised user information.
- Example : Uber
- Don’t be creepy with invasive personalisation
- Example : Offer Moment
- Offer Moment’s overly invasive personalisation tactics crossed ethical boundaries, unsettling users and eroding trust.
- Example : Offer Moment
These examples are valuable lessons, emphasising the importance of ethical and responsible behavioural segmentation practices to maintain user trust and regulatory compliance in an increasingly data-driven world.
Continue the conversation
Diving into customer behaviours, preferences and interactions empowers businesses to forge meaningful connections with their target audience through targeted marketing segmentation strategies. This approach drives growth and fosters exceptional customer experiences, as evident from the various common examples spanning diverse industries.
In the realm of ethical behavioural segmentation and regulatory compliance, Matomo is a trusted partner. Committed to safeguarding user privacy and data integrity, our advanced web analytics solution empowers your business to harness the power of behavioral segmentation, all while upholding the highest standards of compliance with stringent privacy regulations.
To gain deeper insight into your visitors and execute impactful marketing campaigns, explore how Matomo can elevate your efforts. Try Matomo free for 21-days, no credit card required.
- Visit-based segments : These segments hinge on users’ visit patterns. Analyse visit patterns, compare first-time visitors to returning ones, or compare users landing on specific pages to those landing on others.
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Understanding Data Processing Agreements and How They Affect GDPR Compliance
9 octobre 2023, par Erin — GDPRThe General Data Protection Regulation (GDPR) impacts international organisations that conduct business or handle personal data in the European Union (EU), and they must know how to stay compliant.
One way of ensuring GDPR compliance is through implementing a data processing agreement (DPA). Most businesses overlook DPAs when considering ways of maintaining user data security. So, what exactly is a DPA’s role in ensuring GDPR compliance ?
In this article, we’ll discuss DPAs, their advantages, which data protection laws require them and the clauses that make up a DPA. We’ll also discuss the consequences of non-compliance and how you can maintain GDPR compliance using Matomo.
What is a data processing agreement ?
A data processing agreement, data protection agreement or data processing addendum is a contractual agreement between a data controller (a company) and a data processor (a third-party service provider.) It defines each party’s rights and obligations regarding data protection.
A DPA also defines the responsibilities of the controller and the processor and sets out the terms they’ll use for data processing. For instance, when MHP/Team SI sought the services of Matomo (a data processor) to get reliable and compliant web analytics, a DPA helped to outline their responsibilities and liabilities.
A DPA is one of the basic requirements for GDPR compliance. The GDPR is an EU regulation concerning personal data protection and security. The GDPR is binding on any company that actively collects data from EU residents or citizens, regardless of their location.
As a business, you need to know what goes into a DPA to identify possible liabilities that may arise if you don’t comply with European data protection laws. For example, having a recurrent security incident can lead to data breaches as you process customer personal data.
The average data breach cost for 2023 is $4.45 million. This amount includes regulatory fines, containment costs and business losses. As such, a DPA can help you assess the organisational security measures of your data processing methods and define the protocol for reporting a data breach.
Why is a DPA essential for your business ?
If your company processes personal data from your customers, such as contact details, you need a DPA to ensure compliance with data security laws like GDPR. You’ll also need a DPA to hire a third party to process your data, e.g., through web analytics or cloud storage.
But what are the benefits of having a DPA in place ?
A key benefit of signing a DPA is it outlines business terms with a third-party data processor and guarantees compliance with the relevant data privacy laws. A DPA also helps to create an accountability framework between you and your data processor by establishing contractual obligations.
Additionally, a DPA helps to minimise the risk of unauthorised access to sensitive data. A DPA defines organisational measures that help protect the rights of individuals and safeguard personal data against unauthorised disclosure. Overall, before choosing a data processor, having a DPA ensures that they are capable, compliant and qualified.
More than 120 countries have already adopted some form of international data protection laws to protect their citizens and their data better. Hence, knowing which laws require a DPA and how you can better ensure compliance is important.
Which data protection laws require a DPA ?
Regulatory bodies enact data protection laws to grant consumers greater control over their data and how businesses use it. These laws ensure transparency in data processing and compliance for businesses.
The following are some of the relevant data privacy laws that require you to have a DPA :
- UK GDPR
- Brazil LGPD
- EU GDPR
- Dubai PDPA
- Colorado CPA
- California CCPA/CPRA
- Virginia VCDPA
- Connecticut DPA
- South African POPIA
- Thailand PDPA
Companies that don’t adhere to these data protection obligations usually face liabilities such as fines and penalties. With a DPA, you can set clear expectations regarding data processing between you and your customers.
Review and update any DPAs with third-party processors to ensure compliance with GDPR and the laws we mentioned above. Additionally, confirm that all the relevant clauses are present for compliance with relevant data privacy laws.
So, what key data processing clauses should you have in your DPA ? Let’s take a closer look in the next section.
Key clauses in a data processing agreement
GDPR provides some general recommendations for what you should state in a DPA.
Here are the elements you should include :
Data processing specifications
Your DPA should address the specific business purposes for data processing, the duration of processing and the categories of data under processing. It should also clearly state the party responsible for maintaining GDPR compliance and who the data subjects are, including their location and nationality.
Your DPA should also address the data processor and controller’s responsibilities concerning data deletion and contract termination.
Role of processor
Your DPA should clearly state what your data processor is responsible for and liable for. Some key responsibilities include record keeping, reporting breaches and maintaining data security.
Other roles of your data processor include providing you with audit opportunities and cooperating with data protection authorities during inquiries. If you decide to end your contract, the data processor is responsible for deleting or returning data, depending on your agreement.
Role of controller
Your DPA should inform the responsibilities of the data controller, which typically include issuing processing instructions to the data processor and directing them on how to handle data processing.
Your DPA should let you define the lawful data processes the data processor should follow and how you’ll uphold the data protection rights of individuals’ sensitive data.
Organisational and technical specifications
Your DPA should define specifications such as how third-party processors encrypt, access and test personal data. It should also include specifications on how the data processor and controller will maintain ongoing data security through various factors such as :
- State of the technology : Do third-party processors have reliable technology, and can they ensure data security within their systems ?
- Costs of implementation : Does the data controller’s budget allow them to seek third-party services from industry-leading providers who can guarantee a certain level of security ?
- Variances in users’ personal freedom : Are there privacy policies and opt-out forms for users to express how they want companies to use their sensitive data ?
Moreover, your DPA should define how you and your data processor will ensure the confidentiality, availability and integrity of data processing services and systems.
What are the penalties for DPA GDPR non-compliance ?
Regulators use GDPR’s stiff fines to encourage data controllers and third-party processors to follow best data security practices. One way of maintaining compliance is through drafting up a DPA with your data processor.
The DPA should clearly outline the necessary legal requirements and include all the relevant clauses mentioned above. Understand what goes into this agreement since data protection authorities can hold your business accountable for a breach — even if a processor’s error caused it.
Data protection authorities can issue penalties now that the GDPR is in place. For example, according to Article 83 of the GDPR, penalties for data or privacy breaches or non-compliance can amount to up to €20 million or 4% of your annual revenue.
There are two tiers of fines : tier one and tier two. Violations related to data processors typically attract fines on the tier-one level. Tier one fines can cost your business €10 million or 2% of your company’s global revenue.
Tier-two fines result from infringement of the right to forget and the right to privacy of your consumer. Tier-two fines can cost your business up to €20 million or 4% of your company’s global revenue.
GDPR fines make non-compliance an expensive mistake for businesses of all sizes. As such, signing a DPA with any party that acts as a data processor for your business can help you remain GDPR-compliant.
How a DPA can help your business remain GDPR compliant
A DPA can help your business define and adhere to lawful data processes.
So, in what other ways can a DPA help you to remain compliant with GDPR ? Let’s take a look !
1. Assess data processor’s compliance
Having a DPA helps ensure that the data processor you are working with is GDPR-compliant. You should check if they have a DPA and confirm the processor’s terms of service and legal basis.
For example, if you want an alternative to Google Analytics that’s GDPR compliant, then you can opt for Matomo. Matomo features a DPA, which you can agree to when you sign up for web analytics services or later.
2. Establish lawful data processes
A DPA can also help you review your data processes to ensure they’re GDPR compliant. For example, by defining lawful data processes, you better understand personally identifiable information (PII) and how it relates to data privacy.
Further, you can allow users to opt out of sharing their data. As such, Matomo can help you to enable Do Not Track preferences on your website.
With this feature, users are given the option to opt in or out of tracking via a toggle in their respective browsers.
Indeed, establishing lawful data processes helps you define the specific business purposes for collecting and processing personal data. By doing so, you get to notify your users why you need their data and get their consent to process it by including a GDPR-compliant privacy policy on your website.
3. Anonymise your data
Global privacy laws like GDPR and ePrivacy mandate companies to display cookie banners or seek consent before tracking visitors’ data. You can either include a cookie consent banner on your site or stop tracking cookies to follow the applicable regulations.
Further, you can enable cookie-less tracking or easily let users opt out. For example, you can use Matomo without a cookie consent banner, exempting it from many countries’ privacy rules.
Additionally, through a DPA, you can define organisational measures that define how you’ll anonymise all your users’ data. Matomo can help you anonymise IP addresses, and we recommend that you at least anonymise the last two bytes.
As one of the few web analytics tools you can use to collect data without tracking consent, Matomo also has the French Data Protection Authority (CNIL) approval.
4. Assess the processor’s bandwidth
Having a DPA can help you implement data retention policies that show clear retention periods. Such policies are useful when ending a contract with a third-party service provider and determining how they should handle your data.
A DPA also helps you ensure the processor has the necessary technology to store personal data securely. You can conduct an audit to understand possible vulnerabilities and your data processor’s technological capacity.
5. Obtain legal counsel
When drafting a DPA, it’s important to get a consultation on what is needed to ensure complete compliance. Obtaining legal counsel points you in the right direction so you don’t make any mistakes that may lead to non-compliance.
Conclusion
Businesses that process users’ data are subject to several DPA contract requirements under GDPR. One of the most important is having DPAs with every third-party provider that helps them perform data processing.
It’s important to stay updated on GDPR requirements for compliance. As such, Matomo can help you maintain lawful data processes. Matomo gives you complete control over your data and complies with GDPR requirements.
To get started with Matomo, you can sign up for a 21-day free trial. No credit card required.
Disclaimer
We are not lawyers and don’t claim to be. The information provided here is to help give an introduction to GDPR. We encourage every business and website to take data privacy seriously and discuss these issues with your lawyer if you have any concerns.
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Top 5 Customer Segmentation Software in 2024
12 mars 2024, par ErinIn marketing, we all know the importance of reaching the right customer with the right message at the right time. That’s how you cut through the noise.
For that, you need data on your customers — even though gathering the data is not enough. You can have all the data worldwide, but that raises an ethical responsibility and the need to make sense of it.
Enter customer segmentation software — the answer to delivering personalised customer experiences at scale.
This article lists some of the best customer segmentation tools currently in the market.
We’ll also go over the benefits of using such tools and how you can choose the best one for your business.
Let’s get started !
What is customer segmentation software ?
Customer segmentation software is a tool that helps businesses analyse customer data and group them based on common characteristics like age, income, and buying habits.
The main goal of customer segmentation is to gain deeper insights into customer behaviours and preferences. This helps create targeted marketing and product strategies that fit each group and makes it easier to predict how customers will behave in the future.
Benefits of a customer segmentation software
Understanding your customers is the cornerstone of effective marketing, and customer segmentation software plays a pivotal role in this endeavour.
You can deliver more targeted and relevant marketing campaigns by dividing your audience into distinct groups based on shared characteristics.
Specifically, here are the main benefits of using customer segmentation tools :
- Understand your audience better : The software helps businesses group customers with common traits to better understand their preferences and behaviour.
- Make data-driven decisions : Base your business and marketing decisions on data analytics.
- Aid product development : Insights from segmentation analytics can guide the creation of products that meet specific customer group needs.
- Allocate your resources efficiently : Focusing on the customer segments that generate the most revenue leads to more effective and strategic use of your marketing resources.
Best customer segmentation software in 2024
In this section, we go over the top customer segmentation tools in 2024.
We’ll look at these tools’ key features and pros and cons.
1. Matomo
Matomo is a comprehensive web analytics tool that merges traditional web analytics, such as tracking pageviews and visitor bounce rates, with more advanced web analytics features for tracking user behaviour.
With robust segmentation features, users can filter website traffic based on criteria such as location and device type, enabling them to analyse specific visitor groups and their behaviour. Users can create custom segments to analyse specific groups of visitors and their behaviour.
Presenting as the ethical alternative to Google Analytics, Matomo emphasises transparency, 100% accurate data, and compliance with privacy laws.
Key features
- Heatmaps and Session Recordings : Matomo provides tools that allow businesses to understand website user interactions visually. This insight is crucial for optimising user experience and increasing conversions.
- Form Analytics : This feature in Matomo tracks how users interact with website forms, helping businesses understand user behaviour in detail and improve form design and functionality.
- User Flow Analysis : The tool tracks the journey of a website’s visitors, highlighting the paths taken and where users drop off. This is key for optimising website structure for better user experience and more conversions.
- A/B Testing : Businesses can use Matomo to test different versions of web pages, determining which is more effective in driving conversions.
- Conversion Funnels : This feature allows businesses to visualise and optimise the steps customers take toward conversion, identifying areas for improvement.
Pros
- Affordability : With plans starting at $19 per month, Matomo is a cost-effective solution for CRO.
- Free support : Matomo provides free email support to all Matomo Cloud users.
- Open-source benefits : Being open-source, Matomo offers enhanced security, privacy, customisation options, and a supportive community.
- Hosting options : Matomo is available either as a self-hosted solution or cloud-hosted.
Cons
- Cost for advanced features : Access to advanced features may incur additional costs for Matomo On-Premise users, although the On-Premise solution itself is free.
- Technical knowledge required : The self-hosted version of Matomo requires technical knowledge for effective management.
Try Matomo for Free
Get the web insights you need, without compromising data accuracy.
2. Google Analytics
Google Analytics 4 (GA4) comprehensively understands website and app performance. It focuses on event-based data collection, allowing businesses to understand user interactions across platforms.
Similarly to Matomo, GA4 provides features that allow businesses to segment their audience based on various criteria such as demographics, behaviours, events, and more.
Key features
- Event-based tracking : GA4’s shift to an event-based model allows for a flexible and predictive analysis of user behaviour. This includes a detailed view of user interactions on websites and apps.
- Machine Learning and Smarter Insights : GA4 uses machine learning to automatically detect trends, estimate purchase probabilities and provide marketing insights.
- Google Ads integration : The integration with Google Ads in GA4 enables tracking customer interactions from first ad engagement, providing a holistic view of the customer experience across various platforms.
- Customer-centric measurements : GA4 collects data as events, covering a wide range of user interactions and offering a comprehensive view of customer behaviour.
- Pathing reports : GA4 introduces new pathing reports, allowing detailed user flow analysis through websites and apps.
- Audiences and filters : GA4 allows the creation of audiences based on specific criteria and the application of filters to segment and refine data analysis.
Pros
- Integration with various platforms, including Google Ads, enhances cross-platform user journey analysis.
- GA4 has a clean reporting interface, making it easier for marketers to identify key trends and data irregularities.
- Google Analytics has an active community with an abundance of educational resources available for users.
Cons
- Complexity for beginners : The wide range of features and new event-based model might overwhelm users new to analytics tools.
- Dependence on machine learning : Reliance on machine learning for insights and predictions may require trust in the tool’s data processing and large volumes of traffic for accuracy.
- Transition from UA to GA4 : Users familiar with Universal Analytics (UA) might find the transition to GA4 challenging due to differences in features and data models.
3. HubSpot
HubSpot is a marketing and sales software that helps businesses attract visitors and turn them into paying customers.
It supports various business processes, from social media posts to email marketing, sales, and customer service. HubSpot organises and tracks user interactions across different channels, providing a unified and efficient approach to customer relationship management (CRM) and customer segmentation.
Businesses can leverage HubSpot’s customer segmentation through lists, workflows, and smart content.
Key features
- Integration capabilities : HubSpot offers over 1,000 integrations in its ecosystem, ensuring seamless connectivity across various marketing, sales, and service tools, which helps maintain data consistency and reduces manual efforts.
- Segmentation and personalisation : HubSpot allows businesses to deliver personalised content and interactions based on customer behaviour and preferences, using its robust CRM features and advanced automation capabilities.
Pros
- Comprehensive support : HubSpot offers a range of support options, including a knowledge base, real-time chat, and more.
- User-friendly interface : The platform is designed for ease of use, ensuring a smooth experience even for less tech-savvy users.
- Personalisation capabilities : HubSpot provides personalised marketing, sales and service experiences, leveraging customer data effectively.
Cons
- High price point : HubSpot can be expensive, especially as you scale up and require more advanced features.
- Steep learning curve : For businesses new to such comprehensive platforms, there might be an initial learning curve to utilise its features effectively.
4. Klaviyo
Klaviyo is a marketing automation software primarily focused on email and SMS messaging for e-commerce businesses. It’s designed to personalise and optimise customer communication.
Klaviyo integrates with e-commerce platforms like Shopify, making it a go-to solution for online stores. Its strength lies in its ability to use customer data to deliver targeted and effective marketing campaigns.
Key features
- Email marketing automation : Klaviyo allows users to send automated and personalised emails based on customer behaviour and preferences. This feature is crucial for e-commerce businesses in nurturing leads and maintaining customer engagement.
- SMS marketing : It includes SMS messaging capabilities, enabling businesses to engage customers directly through text messages.
- Segmentation and personalisation : Klaviyo offers advanced segmentation tools that enable businesses to categorise customers based on their behaviour, preferences and purchase history, facilitating highly targeted marketing efforts.
- Integration with e-commerce platforms : Klaviyo integrates with popular e-commerce platforms like Shopify, Magento, and WooCommerce, allowing easy data synchronisation and campaign management.
Pros
- Enhanced e-commerce integration : Klaviyo’s deep integration with e-commerce platforms greatly benefits online retailers regarding ease of use and campaign effectiveness.
- Advanced segmentation and personalisation : The platform’s strong segmentation capabilities enable businesses to tailor their marketing messages more effectively.
- Robust automation features : Klaviyo’s automation tools are powerful and user-friendly, saving time and improving marketing efficiency.
Cons
- Cost : Klaviyo can be more expensive than other options in this list, particularly as you scale up and add more contacts.
- Complexity for beginners : The platform’s wide range of features and advanced capabilities might overwhelm beginners or small businesses with simpler needs.
5. UserGuiding
UserGuiding is a no-code product adoption tool that lets businesses create in-app user walkthroughs, guides, and checklists to onboard, engage, and retain users.
UserGuiding facilitates customer segmentation by enabling businesses to create segmented onboarding flows, analyse behavioural insights, deliver personalised guidance, and collect feedback tailored to different user segments.
Key features
- In-app walkthroughs, guides and checklists : UserGuiding has multiple features that can promote product adoption early in the user journey.
- In-app messaging : UserGuiding offers in-app messaging to help users learn more about the product and various ways to get value.
- User feedback : UserGuiding allows businesses to gather qualitative feedback to streamline the adoption journey for users.
Pros
- User-friendly interface
- Customisable onboarding checklists
- Retention analytics
Cons
- Need for technical expertise to maximise all features
- Limited customisation options for less tech-savvy users
What to look for in a customer segmentation software
When choosing a customer segmentation software, choosing the right one for your specific business needs is important.
Here are a few factors to consider when choosing your customer segmentation tool :
- Ease of use : Select a tool with an intuitive interface that simplifies navigation. This enhances the user experience, making complex tasks more manageable. Additionally, responsive customer support is crucial. It ensures that issues are promptly resolved, contributing to a smoother operation.
- Scalability and flexibility : Your chosen tool should adjust to your needs. A flexible tool like Matomo can adjust to your growing requirements, offering capabilities that evolve as your business expands.
- Integration capabilities : The software should seamlessly integrate with your existing systems, such as CRM, marketing, and automation platforms.
- Advanced analytics and reporting : Assess the software’s capability to analyse and interpret complex data sets, without relying on machine learning to fill data gaps. A robust tool should provide accurate insights and detailed reports, enabling you to make informed decisions based on real data.
- Privacy and security considerations : Data security is paramount in today’s digital landscape. Look for features like data encryption, security storage, and adherence to privacy standards like GDPR and CCPA compliance.
- Reviews and recommendations : Before making a decision, consider the reputation of the software providers. Look for reviews and recommendations from other users, especially those in similar industries. This can provide real-world insights into the software’s performance and reliability.
Leverage Matomo’s segmentation capabilities to deliver personalised experiences
Segmentation is the best place to start if you want to deliver personalised customer experiences. There are several customer segmentation software in the market. But they’re not all the same.
In this article, we reviewed the top segmentation tools — based on factors like their user base, features, and ethical data privacy considerations.
Ideally, you want a tool to support your evolving business and segmentation needs. Not to mention one that cares about your customers’ privacy and ensures you stay compliant.
Enter Matomo at the top of the list. You can leverage Matomo’s accurate insights and comprehensive segmentation capabilities without compromising on privacy. Try it free for 21-days. No credit card required.
Try Matomo for Free
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