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• Enterprise web analytics : Quick start guide (and top tools)

  10 juillet, par Joe — Analytics Tips

  Without data, you’ll get lost in the sea of competition.

  This is even more important for large organisations.

  Data helps you :

  • Optimise customer experiences
  • Navigate complex business decisions
  • Create a roadmap to sustainable brand growth
  • Data can power differentiation, especially within fiercely competitive sectors.

  How do you get the benefits of data in a large organisation ?

  Enterprise web analytics.

  In this guide, we’ll cover everything you need to know about enterprise web analytics to enhance website performance, improve customer experiences and increase conversions.

  What is enterprise web analytics ?

  Enterprise web analytics help large organisations capture, analyse, and act on website data to optimise customer experiences and make informed decisions. By providing insight into customer interactions, user behaviour and preferences, they’re vital in helping big businesses improve their websites.

  

  Enterprise web analytics can extract data from web pages and reveal a range of performance metrics, including :

  • Pageviews
  • Average time on page
  • Actions per visit
  • Bounce rate
  • Conversions
  • Traffic sources
  • Device type
  • Event tracking
  • And more

  You can track this data daily or access monthly reports, which will give you valuable insights into optimising user engagement, improving your website’s search engine traffic, and meeting business goals like increased conversion rates.

  For large organisations, web analytics isn’t just about measuring traffic. Instead, it’s an asset you can use to identify issues in your web strategy so you can gain insights that will fuel sustainable business growth.

  An advanced analytics strategy goes beyond the digital channels, page views and bounce rates of traditional analytics.

  Instead, modern web analytics incorporates behavioural analytics for deeper analysis and insight into user experiences. These advanced features include :

  • Heatmaps (or scroll maps) to track scroll behaviour on each page
  • User flow reports to see the pages your users visit in the customer journey
  • Session recordings to analyse user interactions (step-by-step)

  Taking a two-pronged approach to web analytics that includes both traditional and behavioural metrics, organisations get a clearer picture of users and their brand interactions.

  Different needs of enterprise companies

  Let’s dive deeper into the different needs of enterprise companies and how enterprise web analytics can help solve them :

  Access more storage

  Let’s face it. Large organisations have complex IT infrastructures and vast amounts of data.

  The amount of data to capture, analyse and store isn’t slowing down anytime soon.

  Enterprise web analytics can help handle and store large amounts of data in ways that serve the entire organisation.

  Enable cross-organisational data consumption

  It’s one thing to access data in a small company. You’ve got yourself and a few employees. That’s easy.

  But, it’s another thing to enable an organisation with thousands of employees with different roles to access complex data structures and large amounts of data.

  Enterprise web analytics allows big companies to enable their entire workforce to gain access to the data they need when they need it.

  Increase security

  As mentioned above, large organisations can use enterprise web analytics to help hundreds or even thousands of employees access their web data.

  However, some data shouldn’t be accessed by every type of employee. For example, some organisations may only want certain data accessed by executives, and some employees may not need to access certain types of data that may confuse or overwhelm them.

  Enterprise web analytics can help you grant access to certain types of data based on your role in the company, ensuring the security of sensitive data in your organisation.

  Improve privacy

  You can keep your data secure from internal breaches with enterprise web analytics. But, how do you protect customer data ?

  With all-inclusive privacy measures.

  To ensure that your customers’ privacy and data are protected, choose a web analytics solution that’s compliant with the latest and most important privacy measures, such as GDPR, LGPD and CCPA.

  Taking a privacy-first approach to data helps ensure your protection from potential legal action or fines.

  Enterprise web analytics best practices

  Want to make sure you get the most out of your web analytics strategy ?

  

  Be clear on what metrics you want to track

  You can track a ton of data in your organisation, but you may not need to. To ensure you’re not wasting time and resources tracking irrelevant numbers, you should make sure you’re clear from day one on the metrics you want to track.

  Start by making a list of key data points relevant to your business.

  For example, if you have an online marketplace, you’ll want to track specific ecommerce metrics like conversion rate, total visits, bounce rates, traffic source, etc.

  Don’t take data at face value

  Numbers alone can’t tell you the whole story of what’s happening in your organisation. It’s crucial you add context to your data, no matter what.

  Dozens of factors could impact your data and visitors’ interactions with your site, so you should always try to look beyond the numbers to see if there are other factors at play.

  For example, you might see that your site traffic is down and think your search engine optimisation (SEO) efforts aren’t working. Meanwhile, there could have been a major Google algorithm update or some sort of seasonality in a key market.

  On the other hand, you might see some positive signals that things are going well with your organic social media strategy because you saw a large influx of traffic from Instagram. But, there could be more to the story.

  For example, an Instagram influencer with five million followers may have just posted a reel reviewing your product or service without you knowing it, leading to a major traffic spike for your website.

  Remember to add notes to your web analytics data if necessary to ensure you can reference any insights from your data to maintain that point of context.

  Ensure your data is accurate

  With web analytics, data is everything. It will help you see where your traffic is coming from, how your users are behaving, and gain actionable insights into how you can improve your website and user experience.

  But if your data isn’t accurate, your efforts will be futile.

  Accurate data is crucial for launching an effective web analytics strategy. Data sampling and simple tracking errors can lead to inaccurate numbers and misleading conclusions. 

  If a tool relies on cookies to collect data, then it’s relying on a faulty data collection system. Cookies give users the option to opt out of tracking, making it challenging to get a clear picture of every user interaction.

  For example, some platforms like Google Analytics use data sampling to make predictions about traffic rather than relying on accurate data collection, leading to inaccurate numbers and conclusions.

  To ensure you’re making decisions based on accurate data, find a solution that doesn’t rely on inaccurate data collection methods like data sampling or cookies.

  Lean on visual data tools to improve analysis

  Enterprise organisations deal with a ton of data. There are endless data points to track, and it can be easy to lose track of what’s going on with the bigger picture.

  One of the best ways to interpret your data is to use a data visualisation tool to integrate with your web analytics solution, like Looker or PowerBI.

  Make sure your chosen platform lets you export your data easily so you can link it with a visual support tool.

  With Matomo, you can easily export your data into Google BigQuery to warehouse your customer data and visualise it through other tools (without the need for APIs, scripts or additional tools).

  Use advanced web analytics

  Web analytics is quite broad, and different tools will offer various features you can access in your analytics dashboard.

  Take advantage of advanced features that utilise both traditional and behavioural data for deeper insights.

  • Use heatmaps to better understand what parts of your web pages your visitors are focusing on to improve conversion rates.
  • Review session recordings to see the exact steps your customers take as they interact with your website.
  • Conduct A/B tests to see which call to action, headline, or image provides the optimal user experience.

  There are dozens of advanced features available, so take the time to make sure your chosen tool has everything you need.

  Choose a privacy-focused tool

  Obviously, not every tool is created equal, and most of the software on the market isn’t suitable for enterprise businesses.

  As a large organisation, the most important step is to choose a trusted enterprise web analytics tool to ensure it’s capable of fitting within a company of your size.

  It needs to have great infrastructure and be able to handle large amounts of data.

  Another crucial factor is to check that the tool is compatible with your website or app. Does it integrate easily with it ? What about your other software ? Will it integrate with those as well and fit into your current tech stack ?

  Most importantly, you need a platform that can provide the data and insights your organisation needs.

  Make sure the tool you choose is GDPR-compliant and privacy-friendly. The last thing you want is to be sued or fined because you chose the wrong software. 

  Consumers are growing more cautious about privacy and data risks, so picking a privacy-focused tool will help build trust with customers.

  Top 5 enterprise web analytics tools

  Now that you understand enterprise web analytics and how to get the most out of it, it’s time to talk about tools.

  You need to make sure you’re using the right web analytics software to improve productivity, optimise website performance and grow your brand without compromising on the infrastructure required for large organisations to thrive.

  Here are five of the best enterprise solutions available :

  Features and pricing comparison

  	GDPR compliant	On-premise option	100% data ownership	Traditional analytics	Behavioural analytics	Awarded best enterprise software
  Matomo	✔️	✔️	✔️	✔️	✔️	✔️
  Amplitude	✔️	✔️			✔️
  Adobe	✔️			✔️	✔️
  GA360				✔️
  Contentsquare	✔️	✔️			✔️	✔️

  Use Matomo to power your website analytics

  Web analytics help enterprise organisations reach new users, improve engagement with current users or grow their web presence.

  These advanced solutions support cross-organisational data consumption, enhance data privacy and security and allow brands to create the web experiences they know customers will love.

  

  Matomo can help you unlock the potential of your website strategy with traditional and behavioural analytics and accurate data. Trusted by over 1 million websites, Matomo’s open-source software is an ethical web solution that helps organisations of all sizes improve decision-making and customer experiences without compromising on privacy or security.

  Start your free 21-day trial now. No credit card required.

• Output file does not show up after executing ffmpeg command [closed]

  19 février 2024, par davai

  I'm using ffmpeg to combine an MP3 + G file and produce an MP4 file. I've placed the source code / .exe file for 'ffmpeg' in the project folder, and the MP3 + G files are also in the project folder. I also set the MP4 output to show up in the project folder as well. The weird thing is that, initially, I was producing output files, and while trying to tweak the constant rate factor, the MP4 output just stopped showing up entirely. I'm also not receiving any errors while running the code, and it does print out that the file has been successfully created, despite nothing showing up in the project folder.

  


  
        String mp3FilePath = "C:/Users/exampleuser/pfolder/example.mp3";
        String gFilePath = "C:/Users/exampleuser/pfolder/example.cdg";
        String mp4OutputPath = "C:/Users/exampleuser/pfolder/example.mp4";

        try
        {
            String[] command = {
                    "C:/Users/tonih/IdeaProjects/MP3GtoMP4Conversion/ffmpeg/ffmpeg-2024-02-19-git-0c8e64e268-full_build/bin/ffmpeg.exe",
                    "-i", mp3FilePath,       // Input MP3 file
                    "-r", "25",              // Frame rate
                    "-loop", "1",            // Loop input video
                    "-i", gFilePath,         // Input G file
                    "-c:v", "libx264",       // Video codec
                    "-preset", "slow",       // Encoding preset for quality (choose according to your requirement)
                    "-crf", "18",            // Constant Rate Factor (lower is higher quality, typical range 18-28)
                    "-c:a", "aac",           // Audio codec
                    "-b:a", "320k",          // Audio bitrate
                    "-shortest",             // Stop when the shortest stream ends
                    mp4OutputPath            // Output MP4 file
            };

            Process process = Runtime.getRuntime().exec(command);
            process.waitFor();
            System.out.println("MP4 file created successfully: " + mp4OutputPath);
        }
        catch (IOException | InterruptedException e)
        {
            e.printStackTrace();
        }


  


• How to send a camera capture frame to YouTube streaming using ffmpeg

  2 mars 2024, par 유혜진

  import subprocess 
import cv2

# YouTube streaming settings
YOUTUBE_URL = "rtmp://a.rtmp.youtube.com/live2/"
KEY = "..."

# OpenCV camera setup
cap = cv2.VideoCapture(0)
cap.set(cv2.CAP_PROP_FRAME_WIDTH, 640)
cap.set(cv2.CAP_PROP_FRAME_HEIGHT, 480)

# FFmpeg command for streaming
command = [r"C:\utility\ffmpeg\ffmpeg-2024-02-22-git-76b2bb96b4-full_build\ffmpeg-2024-02-22-git-76b2bb96b4-full_build\bin\ffmpeg.exe",
            '-f', 'rawvideo',
            '-pix_fmt', 'bgr24',
            '-s', '640x480',
            '-i', '-',
            '-ar', '44100',
            '-ac', '2',
            '-acodec', 'pcm_s16le',
            '-f', 's16le',
            '-ac', '2',
            '-i', 'NUL',   
            '-acodec', 'aac',
            '-ab', '128k',
            '-strict', 'experimental',
            '-vcodec', 'h264',
            '-pix_fmt', 'yuv420p',
            '-g', '50',
            '-vb', '1000k',
            '-profile:v', 'baseline',
            '-preset', 'ultrafast',
            '-r', '30',
            '-f', 'flv', 
            f"{YOUTUBE_URL}/{KEY}",]

# Open a subprocess with FFmpeg
pipe = subprocess.Popen(command, stdin=subprocess.PIPE)

while True:
    # Read a frame from the camera
    ret, frame = cap.read()
    if not ret:
        break

    # Display the frame
    cv2.imshow('Frame', frame)
    cv2.waitKey(1)  # Wait for 1ms

    # Send the frame through the pipe for streaming
    pipe.stdin.write(frame.tobytes())

    # Check for 'q' key press to stop streaming
    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

# Release resources
cap.release()
cv2.destroyAllWindows()


  


  I'm trying to implement capturing the camera screen using opencv and transmitting this frame to the YouTube streaming broadcast via ffmpeg. YouTube streaming does start when I run this code. However, it appears to be a black screen, not a camera screen. I don't see what the problem is.

  


  I didn't even start streaming at first, but I changed the command option to various things, and when I ran the code, I succeeded in starting streaming. There are many references to transmitting mp4, but there are not many references to transmitting real-time capture. I'm going to process the camera screen using opencv and then send it to streaming. I don't know what the problem is. Please help me.