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• Python : ani.save very slow. Any alternatives to create videos ?

  14 novembre 2023, par Czeskleba

  Im doing some simple diffusion calculations. I save 2 matrices to 2 datasets every so many steps (every 2s or so) to a single .h5 file. After that I then load the file in another script, create some figures (2 subplots etc., see/run code - i know could be prettier). Then I use matplotlib.animation to make the animation. In the code below, in the very last lines, I then run the ani.save command from matplotlib.

  


  And that's where the problem is. The animation is created within 2 seconds, even for my longer animations (14.755 frames, done in under 2s at 8284 it/s) but after that, ani.save in line 144 takes forever (it didn't finish over night). It reserves/uses about 10gb of my RAM constantly but seemingly takes forever. If you run the code below be sure to set the frames_to_do (line 20) to something like 30 or 60 to see that it does in fact save an mp4 for shorter videos. You can set it higher to see how fast the time to save stuff increases to something unreasonable.

  


  I've been fiddling this for 2 days now and I cant figure it out. I guess my question is : Is there any way to create the video in a reasonable time like this ? Or do I need something other than animation ?

  


  You should be able to just run the code. Ill provide a diffusion_array.h5 with 140 frames so you dont have to create a dummy file, if I can figure out how to upload something like this safely. (The results are with dummy numbers for now, diffusion coefficients etc. are not right yet.)
I used dropbox. Not sure if thats allowed, if not I'll delete the link and uhh PM me or something ?

  


  https://www.dropbox.com/scl/fi/fv9stfqkm4trmt3zwtvun/diffusion_array.h5?rlkey=2oxuegnlcxq0jt6ed77rbskyu&dl=0

  


  Here is the code :

  


  import h5py
import matplotlib.pyplot as plt
import matplotlib.colors as mcolors
from matplotlib.animation import FuncAnimation
from tqdm import tqdm
import numpy as np


# saving the .mp4 after tho takes forever

# Create an empty figure and axis
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(16, 9), dpi=96)

# Load all saved arrays into a list
file_name = 'diffusion_array.h5'
loaded_u_arrays = []
loaded_h_arrays = []
frames_to_do = 14755  # for now like this, use # version once the slow mp4 convert is cleared up

# with h5py.File(file_name, 'r') as hf:
#     for key in hf.keys():
#         if key.startswith('u_snapshot_'):
#             loaded_u_arrays.append(hf[key][:])
#         elif key.startswith('h_snapshot_'):
#             loaded_h_arrays.append(hf[key][:])

with h5py.File(file_name, 'r') as hf:
    for i in range(frames_to_do):
        target_key1 = f'u_snapshot_{i:05d}'
        target_key2 = f'h_snapshot_{i:05d}'
        if target_key1 in hf:
            loaded_u_arrays.append(hf[target_key1][:])
        else:
            print(f'Dataset u for time step {i} not found in the file.')
        if target_key2 in hf:
            loaded_h_arrays.append(hf[target_key2][:])
        else:
            print(f'Dataset h for time step {i} not found in the file.')

# Create "empty" imshow objects
# First one
norm1 = mcolors.Normalize(vmin=140, vmax=400)
cmap1 = plt.get_cmap('hot')
cmap1.set_under('0.85')
im1 = ax1.imshow(loaded_u_arrays[0], cmap=cmap1, norm=norm1)
ax1.set_title('Diffusion Heatmap')
ax1.set_xlabel('X')
ax1.set_ylabel('Y')
cbar_ax = fig.add_axes([0.05, 0.15, 0.03, 0.7])
cbar_ax.set_xlabel('$T$ / K', labelpad=20)
fig.colorbar(im1, cax=cbar_ax)


# Second one
ax2 = plt.subplot(1, 2, 2)
norm2 = mcolors.Normalize(vmin=-0.1, vmax=5)
cmap2 = plt.get_cmap('viridis')
cmap2.set_under('0.85')
im2 = ax2.imshow(loaded_h_arrays[0], cmap=cmap2, norm=norm2)
ax2.set_title('Diffusion Hydrogen')
ax2.set_xlabel('X')
ax2.set_ylabel('Y')
cbar_ax = fig.add_axes([0.9, 0.15, 0.03, 0.7])
cbar_ax.set_xlabel('HD in ml/100g', labelpad=20)
fig.colorbar(im2, cax=cbar_ax)

# General
fig.subplots_adjust(right=0.85)
time_text = ax2.text(-15, 0.80, f'Time: {0} s', transform=plt.gca().transAxes, color='black', fontsize=20)

# Annotations
# Heat 1
marker_style = dict(marker='o', markersize=6, markerfacecolor='black', markeredgecolor='black')
ax1.scatter(*[10, 40], s=marker_style['markersize'], c=marker_style['markerfacecolor'],
            edgecolors=marker_style['markeredgecolor'])
ann_heat1 = ax1.annotate(f'Temp: {loaded_u_arrays[0][40, 10]:.0f}', xy=[10, 40], xycoords='data',
             xytext=([10, 40][0], [10, 40][1] + 48), textcoords='data',
             arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3"), fontsize=12, color='black')
# Heat 2
ax1.scatter(*[140, 85], s=marker_style['markersize'], c=marker_style['markerfacecolor'],
            edgecolors=marker_style['markeredgecolor'])
ann_heat2 = ax1.annotate(f'Temp: {loaded_u_arrays[0][85, 140]:.0f}', xy=[140, 85], xycoords='data',
             xytext=([140, 85][0] + 55, [140, 85][1] + 3), textcoords='data',
             arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3"), fontsize=12, color='black')

# Diffusion 1
marker_style = dict(marker='o', markersize=6, markerfacecolor='black', markeredgecolor='black')
ax2.scatter(*[10, 40], s=marker_style['markersize'], c=marker_style['markerfacecolor'],
            edgecolors=marker_style['markeredgecolor'])
ann_diff1 = ax2.annotate(f'HD: {loaded_h_arrays[0][40, 10]:.0f}', xy=[10, 40], xycoords='data',
             xytext=([10, 40][0], [10, 40][1] + 48), textcoords='data',
             arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3"), fontsize=12, color='black')
# Diffusion 2
ax2.scatter(*[140, 85], s=marker_style['markersize'], c=marker_style['markerfacecolor'],
            edgecolors=marker_style['markeredgecolor'])
ann_diff2 = ax2.annotate(f'HD: {loaded_h_arrays[0][85, 140]:.0f}', xy=[140, 85], xycoords='data',
             xytext=([140, 85][0] + 55, [140, 85][1] + 3), textcoords='data',
             arrowprops=dict(arrowstyle="->", connectionstyle="arc3,rad=0.3"), fontsize=12, color='black')


# Function to update the animation
def update(frame, *args):
    loaded_u_array, loaded_h_array = args

    s_per_frame = 2  # during weld/cooling you save a state every 2s
    frames_to_room_temp = 7803  # that means this many frames need to be animated
    dt_big = 87  # during "just diffusion" you save every 10 frame but 87s pass in those

    # Update the time step shown
    if frame <= frames_to_room_temp:
        im1.set_data(loaded_u_array[frame])
        im2.set_data(loaded_h_array[frame])
        time_text.set_text(f'Time: {frame * s_per_frame} s')

    else:
        im1.set_data(loaded_u_array[frame])
        im2.set_data(loaded_h_array[frame])
        calc_time = int(((2 * frames_to_room_temp) + (frame - frames_to_room_temp) * 87) / 3600)
        time_text.set_text(f'Time: {calc_time} s')

    # Annotate some points
    ann_heat1.set_text(f'Temp: {loaded_u_arrays[frame][40, 10]:.0f}')
    ann_heat2.set_text(f'Temp: {loaded_u_arrays[frame][85, 140]:.0f}')
    ann_diff1.set_text(f'HD: {loaded_h_arrays[frame][40, 10]:.0f}')
    ann_diff2.set_text(f'HD: {loaded_h_arrays[frame][85, 140]:.0f}')

    return im1, im2  # Return the updated artists


# Create the animation without displaying it
ani = FuncAnimation(fig, update, frames=frames_to_do, repeat=False, blit=True, interval=1,
                    fargs=(loaded_u_arrays, loaded_h_arrays))  # frames=len(loaded_u_arrays)

# Create the progress bar with tqdm
with tqdm(total=frames_to_do, desc='Creating Animation') as pbar:  # total=len(loaded_u_arrays)
    for i in range(frames_to_do):  # for i in range(len(loaded_u_arrays)):
        update(i, loaded_u_arrays, loaded_h_arrays)  # Manually update the frame with both datasets
        pbar.update(1)  # Update the progress bar

# Save the animation as a video file (e.g., MP4)
print("Converting to .mp4 now. This may take some time. This is normal, wait for Python to finish this process.")
ani.save('diffusion_animation.mp4', writer='ffmpeg', dpi=96, fps=60)

# Close the figure to prevent it from being displayed
plt.close(fig)



  


• Top 4 CRO Tools to Boost Your Conversion Rates in 2024

  31 octobre 2023, par Erin

  Are you tired of watching potential customers leave your website without converting ? You’ve spent countless hours creating an engaging website, but those high bounce rates keep haunting you.

  The good news ? The solution lies in the transformative power of Conversion Rate Optimisation (CRO) tools. In this guide, we’ll dive deep into the world of CRO tools. We will equip you with strategies to turn those bounces into conversions.

  Why are conversion rate optimisation tools so crucial ?

  CRO tools can be assets in digital marketing, playing a pivotal role in enhancing online businesses’ performance. CRO tools empower businesses to improve website conversion rates by analysing user behaviour. You can then leverage this user data to optimise web elements.

  Improving website conversion rates is paramount because it increases revenue and customer satisfaction. A study by VentureBeat revealed an average return on investment (ROI) of 223% thanks to CRO tools.

  173 marketers out of the surveyed group reported returns exceeding 1,000%. Both of these data points highlight the impact CRO tools can have.

  

  Coupled with CRO tools, certain testing tools and web analytics tools play a crucial role. They offer insight into user behaviour patterns, enabling businesses to choose effective strategies. By understanding what resonates with users, these tools help inform data-driven decisions. This allows businesses to refine online strategies and enhance the customer experience.

  CRO tools enhance user experiences and ensure business sustainability. Integrating these tools is crucial for staying ahead. CRO and web analytics work together to optimise digital presence. 

  Real-world examples of CRO tools in action

  In this section, we’ll explore real case studies showcasing CRO tools in action. See how businesses enhance conversion rates, user experiences, and online performance. These studies reveal the practical impact of data-driven decisions and user-focused strategies.

  

  Case study : How Matomo’s Form Analytics helped Concrete CMS 3x leads

  Concrete CMS, is a content management system provider that helps users build and manage websites. They used Matomo’s Form Analytics to uncover that users were getting stuck at the address input stage of the onboarding process. Using these insights to make adjustments to their onboarding form, Concrete CMS was able to achieve 3 times the amount of leads in just a few days.

  Read the full Concrete CMS case study.

  Best analytics tools for enhancing conversion rate optimisation in 2023

  Jump to the comparison table to see an overview of each tool.

  1. Matomo

  

  Matomo stands out as an all-encompassing tool that seamlessly combines traditional web analytics features (like pageviews and bounce rates) with advanced behavioural analytics capabilities, providing a full spectrum of insights for effective CRO.

  Key features

  • Heatmaps and Session Recordings :
    These features empower businesses to see their websites through the eyes of their visitors. By visually mapping user engagement and observing individual sessions, businesses can make informed decisions, enhance user experience and ultimately increase conversions. These tools are invaluable assets for businesses aiming to create user-friendly websites.

  • Form Analytics :
    Matomo’s Form Analytics offers comprehensive tracking of user interactions within forms. This includes covering input fields, dropdowns, buttons and submissions. Businesses can create custom conversion funnels and pinpoint form abandonment reasons. 

  • Users Flow :
    Matomo’s Users Flow feature tracks visitor paths, drop-offs and successful routes, helping businesses optimise their websites. This insight informs decisions, enhances user experience, and boosts conversion rates.

  • Surveys plugin :
    The Matomo Surveys plugin allows businesses to gather direct feedback from users. This feature enhances understanding by capturing user opinions, adding another layer to the analytical depth Matomo offers.

  • A/B testing :
    The platform allows you to conduct A/B tests to compare different versions of web pages. This helps determine which performs better in conversions. By conducting experiments and analysing the results within Matomo, businesses can iteratively refine their content and design elements.

  • Funnels :
    Matomo’s Funnels feature empower businesses to visualise, analyse and optimise their conversion paths. By identifying drop-off points, tailoring user experiences and conducting A/B tests within the funnel, businesses can make data-driven decisions that significantly boost conversions and enhance the overall user journey on their websites.

  Pros

  • Starting at $19 per month, Matomo is an affordable CRO solution.
  • Matomo guarantees accurate data, eliminating the need to fill gaps with artificial intelligence (AI) or machine learning. 
  • Matomo’s open-source framework ensures enhanced security, privacy, customisation, community support and long-term reliability. 

  Cons

  • The On-Premise (self-hosted) version is free, with additional charges for advanced features.
  • Managing Matomo On-Premise requires servers and technical know-how.

  Try Matomo for Free

  Get the web insights you need, without compromising data accuracy.

  Start for free

  No credit card required

  2. Google Analytics

  

  Google Analytics provides businesses and website owners valuable insights into their online audience. It tracks website traffic, user interactions and analyses conversion data to enhance the user experience.

  While Google Analytics may not provide the extensive CRO-specific features found in other tools on this list, it can still serve as a valuable resource for basic analysis and optimisation of conversion rates.

  Key features

  • Comprehensive Data Tracking :
    Google Analytics meticulously tracks website traffic, user behaviour and conversion rates. These insights form the foundation for CRO efforts. Businesses can identify patterns, user bottlenecks and high-performing areas.

  • Real-Time Reporting :
    Access to real-time data is invaluable for CRO efforts. Monitor current website activity, user interactions, and campaign performance as they unfold. This immediate feedback empowers businesses to make instant adjustments, optimising web elements and content for maximum conversions.

  • User flow analysis
    Visualise and understand how visitors navigate through your website. It provides insights into the paths users take as they move from one page to another, helping you identify the most common routes and potential drop-off points in the user journey.

  • Event-based tracking :
    GA4’s event-based reporting offers greater flexibility and accuracy in data collection. By tracking various interactions, including video views and checkout processes, businesses can gather more precise insights into user behaviour. 

  • Funnels :
    GA4 offers multistep funnels, path analysis, custom metrics that integrate with audience segments. These user behaviour insights help businesses to tailor their websites, marketing campaigns and user experiences.

  Pros

  • Flexible audience management across products, regions or brands allow businesses to analyse data from multiple source properties. 
  • Google Analytics integrates with other Google services and third-party platforms. This enables a comprehensive view of online activities.
  • Free to use, although enterprises may need to switch to the paid version to accommodate higher data volumes.

  Cons

  • Google Analytics raises privacy concerns, primarily due to its tracking capabilities and the extensive data it collects.
  • Limitations imposed by thresholding can significantly hinder efforts to enhance user experience and boost conversions effectively.
  • Property and sampling limits exist. This creates problems when you’re dealing with extensive datasets or high-traffic websites. 
  • The interface is difficult to navigate and configure, resulting in a steep learning curve.

  3. Contentsquare

  

  Contentsquare is a web analytics and CRO platform. It stands out for its in-depth behavioural analytics. Contentsquare offers detailed data on how users interact with websites and mobile applications.

  Key features

  • Heatmaps and Session Replays :
    Users can visualise website interactions through heatmaps, highlighting popular areas and drop-offs. Session replay features enable the playback of user sessions. These provide in-depth insights into individual user experiences.

  • Conversion Funnel Analysis :
    Contentsquare tracks users through conversion funnels, identifying where users drop off during conversion. This helps in optimising the user journey and increasing conversion rates.

  • Segmentation and Personalisation :
    Businesses can segment their audience based on various criteria. Segments help create personalised experiences, tailoring content and offers to specific user groups.

  • Integration Capabilities :
    Contentsquare integrates with various third-party tools and platforms, enhancing its functionality and allowing businesses to leverage their existing tech stack.

  Pros

  • Comprehensive support and resources.
  • User-friendly interface.
  • Personalisation capabilities.

  Cons

  • High price point.
  • Steep learning curve.

  4. Hotjar

  

  Hotjar is a robust tool designed to unravel user behaviour intricacies. With its array of features including visual heatmaps, session recordings and surveys, it goes beyond just identifying popular areas and drop-offs.

  Hotjar provides direct feedback and offers an intuitive interface, enabling seamless experience optimisation.

  Key features

  • Heatmaps :
    Hotjar provides visual heatmaps that display user interactions on your website. Heatmaps show where users click, scroll, and how far they read. This feature helps identify popular areas and points of abandonment.

  • Session Recordings :
    Hotjar allows you to record user sessions and watch real interactions on your site. This insight is invaluable for understanding user behaviour and identifying usability issues.

  • Surveys and Feedback :
    Hotjar offers on-site surveys and feedback forms that can get triggered based on user behaviour. These tools help collect qualitative data from real users, providing valuable insights.

  • Recruitment Tool :
    Hotjar’s recruitment tool lets you recruit participants from your website for user testing. This feature streamlines the process of finding participants for usability studies.

  • Funnel and Form Analysis :
    Hotjar enables the tracking of user journeys through funnels. It provides insights into where users drop off during the conversion process. It also offers form analysis to optimise form completion rates.

  • User Polls :
    You can create customisable polls to engage with visitors. Gather specific feedback on your website, products, or services.

  Pros

  • Starting at $32 per month, Hotjar is a cost-effective solution for most businesses. 
  • Hotjar provides a user-friendly interface that is easy for the majority of users to pick up quickly.

  Cons

  • Does not provide traditional web analytics and requires combining with another tool, potentially creating a less streamlined and cohesive user experience, which can complicate conversion rate optimization efforts.
  • Hotjar’s limited integrations can hinder its ability to seamlessly work with other essential tools and platforms, potentially further complicating CRO.

  Comparison Table

  Please note : We aim to keep this table accurate and up to date. However, if you see any inaccuracies or outdated information, please email us at marketing@matomo.org

  To make comparing these tools even easier, we’ve put together a table for you to compare features and price points :

  

  Conclusion

  CRO tools and web analytics are essential for online success. Businesses thrive by investing wisely, understanding user behaviour and using targeted strategies. The key : generate traffic and convert it into leads and customers. The right tools and strategies lead to remarkable conversions and online success. Each click, each interaction, becomes an opportunity to create an engaging user journey. This careful orchestration of data and insight separates thriving businesses from the rest.

  Are you ready to embark on a journey toward improved conversions and enhanced user experiences ? Matomo offers analytics solutions meticulously designed to complement your CRO strategy. Take the next step in your CRO journey. Start your 21-day free trial today—no credit card required.

  Try Matomo for Free

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• A Comprehensive Guide to Robust Digital Marketing Analytics

  30 octobre 2023, par Erin

  First impressions are everything. This is not only true for dating and job interviews but also for your digital marketing strategy. Like a poorly planned resume getting tossed in the “no thank you” pile, 38% of visitors to your website will stop engaging with your content if they find the layout unpleasant. Thankfully, digital marketers can access data that can be harnessed to optimise websites and turn those “no thank you’s” into “absolutely’s.”

  So, how can we transform raw data into valuable insights that pay off ? The key is web analytics tools that can help you make sense of it all while collecting data ethically. In this article, we’ll equip you with ways to take your digital marketing strategy to the next level with the power of web analytics.

  What are the different types of digital marketing analytics ?

  Digital marketing analytics are like a cipher into the complex behaviour of your buyers. Digital marketing analytics help collect, analyse and interpret data from any touchpoint you interact with your buyers online. Whether you’re trying to gauge the effectiveness of a new email marketing campaign or improve your mobile app layout, there’s a way for you to make use of the insights you gain. 

  As we go through the eight commonly known types of digital marketing analytics, please note we’ll primarily focus on what falls under the umbrella of web analytics. 

  1. Web analytics help you better understand how users interact with your website. Good web analytics tools will help you understand user behaviour while securely handling user data. 
  2. Learn more about the effectiveness of your organisation’s social media platforms with social media analytics. Social media analytics include user engagement, post reach and audience demographics. 
  3. Email marketing analytics help you see how email campaigns are being engaged with.
  4. Search engine optimisation (SEO) analytics help you understand your website’s visibility in search engine results pages (SERPs). 
  5. Pay-per-click (PPC) analytics measure the performance of paid advertising campaigns.
  6. Content marketing analytics focus on how your content is performing with your audience. 
  7. Customer analytics helps organisations identify and examine buyer behaviour to retain the biggest spenders. 
  8. Mobile app analytics track user interactions within mobile applications. 

  Choosing which digital marketing analytics tools are the best fit for your organisation is not an easy task. When making these decisions, it’s critical to remember the ethical implications of data collection. Although data insights can be invaluable to your organisation, they won’t be of much use if you lose the trust of your users. 

  Tips and best practices for developing robust digital marketing analytics 

  So, what separates top-notch, robust digital marketing analytics from the rest ? We’ve already touched on it, but a big part involves respecting user privacy and ethically handling data. Data security should be on your list of priorities, alongside conversion rate optimisation when developing a digital marketing strategy. In this section, we will examine best practices for using digital marketing analytics while retaining user trust.

  

  Clear objectives

  Before comparing digital marketing analytics tools, you should define clear and measurable goals. Try asking yourself what you need your digital marketing analytics strategy to accomplish. Do you want to improve conversion rates while remaining data compliant ? Maybe you’ve noticed users are not engaging with your platform and want to fix that. Save yourself time and energy by focusing on the most relevant pain points and areas of improvement.

  Choose the right tools for the job

  Don’t just base your decision on what other people tell you. Take the tool for a test drive — free trials allow you to test features and user interfaces and learn more about the platform before committing. When choosing digital marketing analytics tools, look for ones that ensure compliance with privacy laws like GDPR.

  Don’t overlook data compliance

  GDPR ensures organisations prioritise data protection and privacy. You could be fined up to €20 million, or 4% of the previous year’s revenue for violations. Without data compliance practices, you can say goodbye to the time and money spent on digital marketing strategies. 

  Don’t sacrifice data quality and accuracy

  Inaccurate and low-quality data can taint your analysis, making it hard to glean valuable insights from your digital marketing analytics efforts. Regularly audit and clean your data to remove inaccuracies and inconsistencies. Address data discrepancies promptly to maintain the integrity of your analytics. Data validation measures also help to filter out inaccurate data.

  Communicate your findings

  Having insights is one thing ; effectively communicating complex data findings is just as important. Customise dashboards to display key metrics aligned with your objectives. Make sure to automate reports, allowing stakeholders to stay updated without manual intervention. 

  Understand the user journey

  To optimise your conversion rates, you need to understand the user journey. Start by analysing visitors interactions with your website — this will help you identify conversion bottlenecks in your sales or lead generation processes. Implement A/B testing for landing page optimisation, refining elements like call-to-action buttons or copy, and leverage Form Analytics to make informed, data-driven improvements to your forms.

  Continuous improvement

  Learn from the data insights you gain, and iterate your marketing strategies based on the findings. Stay updated with evolving web analytics trends and technologies to leverage new growth opportunities.

  Why you need web analytics to support your digital marketing analytics toolbox

  You wouldn’t set out on a roadtrip without a map, right ? Digital marketing analytics without insights into how users interact with your website are just as useless. Used ethically, web analytics tools can be an invaluable addition to your digital marketing analytics toolbox. 

  The data collected via web analytics reveals user interactions with your website. These could include anything from how long visitors stay on your page to their actions while browsing your website. Web analytics tools help you gather and understand this data so you can better understand buyer preferences. It’s like a domino effect : the more you understand your buyers and user behaviour, the better you can assess the effectiveness of your digital content and campaigns. 

  Web analytics reveal user behaviour, highlighting navigation patterns and drop-off points. Understanding these patterns helps you refine website layout and content, improving engagement and conversions for a seamless user experience.

  

  Concrete CMS harnessed the power of web analytics, specifically Form Analytics, to uncover a crucial insight within their user onboarding process. Their data revealed a significant issue : the “address” input field was causing visitors to drop off and not complete the form, severely impacting the overall onboarding experience and conversion rate.

  Armed with these insights, Concrete CMS made targeted optimisations to the form, resulting in a substantial transformation. By addressing the specific issue identified through Form Analytics, they achieved an impressive outcome – a threefold increase in lead generation.

  This case is a great example of how web analytics can uncover customer needs and preferences and positively impact conversion rates. 

  Ethical implications of digital marketing analytics

  As we’ve touched on, digital marketing analytics are a powerful tool to help better understand online user behaviour. With great power comes great responsibility, however, and it’s a legal and ethical obligation for organisations to protect individual privacy rights. Let’s get into the benefits of practising ethical digital marketing analytics and the potential risks of not respecting user privacy : 

  • If someone uses your digital platform and then opens their email one day to find it filled with random targeted ad campaigns, they won’t be happy. Avoid losing user trust — and facing a potential lawsuit — by informing users what their data will be used for. Give them the option to consent to opt-in or opt-out of letting you use their personal information. If users are also assured you’ll safeguard personal information against unauthorised access, they’ll be more likely to trust you to handle their data securely.
  • Protecting data against breaches means investing in technology that will let you end-to-end encrypt and securely store data. Other important data-security best practices include access control, backing up data regularly and network and physical security of assets.
  • A fine line separates digital marketing analytics and misusing user data — many companies have gotten into big trouble for crossing it. (By big trouble, we mean millions of dollars in fines.) When it comes to digital marketing analytics, you should never cut corners when it comes to user privacy and data security. This balance involves understanding what data can be collected and what should be collected and respecting user boundaries and preferences.

  

  Learn more 

  We discussed a lot of facets of digital marketing analytics, namely how to develop a robust digital marketing strategy while prioritising data compliance. With Matomo, you can protect user data and respect user privacy while gaining invaluable insights into user behaviour. Save your organisation time and money by investing in a web analytics solution that gives you the best of both worlds. 

  If you’re ready to begin using ethical and robust digital marketing analytics on your website, try Matomo. Start your 21-day free trial now — no credit card required.

  Try Matomo for Free

  21 day free trial. No credit card required.

  
  

  Your email address
  

  Your website address
  

  Your Analytics subdomain will be .matomo.cloud (change)

  Choose your analytics subdomain
  

  .matomo.cloud

  I accept the terms and conditions and data processing agreement (DPA)

  
  Your information will be used to create an account on our cloud service. For more information please consult our privacy policy.
  
  
  

  Start improving your websites now