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• Top 5 Customer Segmentation Software in 2024

  12 mars 2024, par Erin

  In 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.

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  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 :

  1. 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.
  2. 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.
  3. Integration capabilities : The software should seamlessly integrate with your existing systems, such as CRM, marketing, and automation platforms. 
  4. 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.
  5. 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. 
  6. 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.

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• How to use audio frame after decode mp3 file using pyav, ffmpeg, python

  2 janvier 2021, par Long Tran Dai

  I am using using python with pyav, ffmpeg to decode mp3 in the memory. I know there are some other way to do it, like pipe ffmpeg command. However, I would like to explore pyav and ffmpeg API. So I have the following code. It works but the sound is very noisy, although hearable :

  


  import numpy as np&#xA;import av # to convert mp3 to wav using ffmpeg&#xA;import pyaudio # to play music&#xA;&#xA;mp3_path = &#x27;D:/MyProg/python/SauTimThiepHong.mp3&#x27;&#xA;&#xA;def decodeStream(mp3_path):&#xA;  # Run NOT OK&#xA;  &#xA;  container = av.open(mp3_path)&#xA;  stream = next(s for s in container.streams if s.type == &#x27;audio&#x27;)&#xA;  frame_count = 0&#xA;  data = bytearray()&#xA;  for packet in container.demux(stream):&#xA;    # <class>&#xA;    # We need to skip the "flushing" packets that `demux` generates.&#xA;    #if frame_count == 5000 : break         &#xA;    if packet.dts is None:&#xA;        continue&#xA;    for frame in packet.decode():   &#xA;        #&#xA;        # type(frame) : <class>&#xA;        #frame.samples = 1152 : 1152 diem du lieu : Number of audio samples (per channel)&#xA;        # moi frame co size = 1152 (diem) * 2 (channels) * 4 (bytes / diem) = 9216 bytes&#xA;        # 11021 frames&#xA;        #arr = frame.to_ndarray() # arr.nbytes = 9216&#xA;&#xA;        #channels = []  &#xA;        channels = frame.to_ndarray().astype("float16")&#xA;        #for plane in frame.planes:&#xA;            #channels.append(plane.to_bytes()) #plane has 4 bytes / sample, but audio has only 2 bytes&#xA;        #    channels.append(np.frombuffer(plane, dtype=np.single).astype("float16"))&#xA;            #channels.append(np.frombuffer(plane, dtype=np.single)) # kieu np.single co 4 bytes&#xA;        if not frame.is_corrupt:&#xA;            #data.extend(np.frombuffer(frame.planes[0], dtype=np.single).astype("float16")) # 1 channel: noisy&#xA;            # type(planes) : <class>&#xA;            frame_count &#x2B;= 1&#xA;            #print( &#x27;>>>> %04d&#x27; % frame_count, frame)   &#xA;            #if frame_count == 5000 : break     &#xA;            # mix channels:&#xA;            for i in range(frame.samples):                &#xA;                for ch in channels: # dec_ctx->channels&#xA;                    data.extend(ch[i]) #noisy&#xA;                    #fwrite(frame->data[ch] &#x2B; data_size*i, 1, data_size, outfile)&#xA;  return bytes(data)&#xA;</class></class></class>

  


  I use pipe ffmpeg to get decoded data to compare and find they are different :

  


  def RunFFMPEG(mp3_path, target_fs = "44100"):
    # Run OK
    import subprocess
    # init command
    ffmpeg_command = ["ffmpeg", "-i", mp3_path,
                   "-ab", "128k", "-acodec", "pcm_s16le", "-ac", "0", "-ar", target_fs, "-map",
                   "0:a", "-map_metadata", "-1", "-sn", "-vn", "-y",
                   "-f", "wav", "pipe:1"]
    # excute ffmpeg command
    pipe = subprocess.run(ffmpeg_command, stdout=subprocess.PIPE, stderr=subprocess.PIPE, bufsize= 10**8)
    # debug
    #print(pipe.stdout, pipe.stderr)
    # read signal as numpy array and assign sampling rate
    #audio_np = np.frombuffer(buffer=pipe.stdout, dtype=np.uint16, offset=44)
    #audio_np = np.frombuffer(buffer=pipe.stdout, dtype=np.uint16)
    #sig, fs  = audio_np, target_fs
    #return audio_np
    return pipe.stdout[78:]     


  


  Then I use pyaudio to play data and find it very noisy

  


  p = pyaudio.PyAudio()
streamOut = p.open(format=pyaudio.paInt16, channels=2, rate= 44100, output=True)
#streamOut = p.open(format=pyaudio.paInt16, channels=1, rate= 44100, output=True)

mydata = decodeStream(mp3_path)
print("bytes of mydata = ", len(mydata))
#print("bytes of mydata = ", mydata.nbytes)

ffMpegdata = RunFFMPEG(mp3_path)
print("bytes of ffMpegdata = ", len(ffMpegdata)) 
#print("bytes of ffMpegdata = ", ffMpegdata.nbytes)

minlen = min(len(mydata), len(ffMpegdata))
print("mydata == ffMpegdata", mydata[:minlen] == ffMpegdata[:minlen]) # ffMpegdata.tobytes()[:minlen] )

#bytes of mydata =  50784768
#bytes of ffMpegdata =  50784768
#mydata == ffMpegdata False

streamOut.write(mydata)
streamOut.write(ffMpegdata)
streamOut.stop_stream()
streamOut.close()
p.terminate()


  


  Please help me to understand decoded frame of pyav api (after for frame in packet.decode() :). Should it be processed more ? or I have some error ?

  


  It makes me crazy for 3 days. I could not guess where to go.

  


  Thank you very much.

  


• How to contribute to open source, for companies

  18 octobre 2010, par Dark Shikari — development, open source, x264

  I have seen many nigh-incomprehensible attempts by companies to contribute to open source projects, including x264. Developers are often simply boggled, wondering why the companies seem incapable of proper communication. The companies assume the developers are being unreceptive, while the developers assume the companies are being incompetent, idiotic, or malicious. Most of this seems to boil down to a basic lack of understanding of how open source works, resulting in a wide variety of misunderstandings. Accordingly, this post will cover the dos and don’ts of corporate contribution to open source.

  Do : contact the project using their preferred medium of communication.

  Most open source projects use public methods of communication, such as mailing lists and IRC. It’s not the end of the world if you mistakenly make contact with the wrong people or via the wrong medium, but be prepared to switch to the correct one once informed ! You may not be experienced using whatever form of communication the project uses, but if you refuse to communicate through proper channels, they will likely not be as inclined to assist you. Larger open source projects are often much like companies in that they have different parts to their organization with different roles. Don’t assume that everyone is a major developer !

  If you don’t know what to do, a good bet is often to just ask someone.

  Don’t : contact only one person.

  Open source projects are a communal effort. Major contributions are looked over by multiple developers and are often discussed by the community as a whole. Yet many companies tend to contact only a single person in lieu of dealing with the project proper. This has many flaws : to begin with, it forces a single developer (who isn’t paid by you) to act as your liaison, adding yet another layer between what you want and the people you want to talk to. Contribution to open source projects should not be a game of telephone.

  Of course, there are exceptions to this : sometimes a single developer is in charge of the entirety of some particular aspect of a project that you intend to contribute to, in which case this might not be so bad.

  Do : make clear exactly what it is you are contributing.

  Are you contributing code ? Development resources ? Money ? API documentation ? Make it as clear as possible, from the start ! How developers react, which developers get involved, and their expectations will depend heavily on what they think you are providing. Make sure their expectations match reality. Great confusion can result when they do not.

  This also applies in the reverse — if there’s something you need from the project, such as support or assistance with development of your patch, make that explicitly clear.

  Don’t : code dump.

  Code does not have intrinsic value : it is only useful as part of a working, living project. Most projects react very negatively to large “dumps” of code without associated human resources. That is, they expect you to work with them to finalize the code until it is ready to be committed. Of course, it’s better to work with the project from the start : this avoids the situation of writing 50,000 lines of code independently and then finding that half of it needs to be rewritten. Or, worse, writing an enormous amount of code only to find it completely unnecessary.

  Of course, the reverse option — keeping such code to yourself — is often even more costly, as it forces you to maintain the code instead of the official developers.

  Do : ignore trolls.

  As mentioned above, many projects use public communication methods — which, of course, allow anyone to communicate, by nature of being public. Not everyone on a project’s IRC or mailing list is necessarily qualified to officially represent the project. It is not too uncommon for a prospective corporate contributor to be turned off by the uninviting words of someone who isn’t even involved in the project due to assuming that they were. Make sure you’re dealing with the right people before making conclusions.

  Don’t : disappear.

  If you are going to try to be involved in a project, you need to stay in contact. We’ve had all too many companies who simply disappear after the initial introduction. Some tell us that we’ll need an NDA, then never provide it or send status updates. You may know why you’re not in contact — political issues at the company, product launch crunches, a nice vacation to the Bahamas — but we don’t ! If you disappear, we will assume that you gave up.

  Above all, don’t assume that being at a large successful company makes you immune to these problems. If anything, these problems seem to be the most common at the largest companies. I didn’t name any names in this post, but practically every single one of these rules has been violated at some point by companies looking to contribute to x264. In the larger scale of open source, these problems happen constantly. Don’t fall into the same traps that many other companies have.

  If you’re an open source developer reading this post, remember it next time you see a company acting seemingly nonsensically in an attempt to contribute : it’s quite possible they just don’t know what to do. And just because they’re doing it wrong doesn’t mean that it isn’t your responsibility to try to help them do it right.