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• Conversion Funnel Optimisation : 10 Ways to Convert More

  24 janvier 2024, par Erin

  Converting leads into happy customers is the ultimate goal of any sales and marketing team. But there are many steps in between those two events, or in other words, funnel stages. 

  Your sales funnel includes all the steps you take to make your audience aware of your product or services and convince them to purchase. Conversion funnel optimisation strategies can help you move users through the stages of your sales funnel. 

  This article will show you how to optimise your conversion funnel and boost sales — no matter how your funnel looks. We’ll go over practical tips you can implement and how you can analyse and measure results.

  Let’s get started.

  What is conversion funnel optimisation ? 

  Conversion funnel optimisation is the strategic and ongoing process of refining and improving the different stages of a sales or marketing funnel to increase the rate at which users complete desired actions.

  A sales funnel represents the stages a potential customer goes through before purchasing. 

  The typical stages of a sales funnel include :

  • Awareness : At the top of the funnel, potential customers become aware of your product or service. 
  • Consideration : In this stage, prospects evaluate the product or service against alternatives. They may compare features, prices and customer reviews to make an informed decision.
  • Conversion : The prospect completes the transaction and becomes an actual customer by purchasing.
  • Loyalty : You can turn one-time buyers into repeat customers and brand advocates. 

  It’s called a “funnel” because, similar to the shape of a funnel, the number of potential customers decreases as they progress through the various stages of the sales process — as you can see illustrated below.

  

  Sales funnels can vary across industries and business models, but the general concept remains the same. The goal is to guide potential customers through each funnel stage, addressing their needs and concerns at each step, ultimately leading to a successful conversion. 

  You can create and monitor a custom funnel for your site’s user journey with a web analytics solution like Matomo.

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  The importance of conversion funnel optimisation 

  At the heart of conversion funnel optimisation is the quest for higher conversion rates. 

  Refining the customer journey can increase the chances of turning visitors into customers who return repeatedly.

  Specifically, here’s how conversion funnel optimisation can benefit your business :

  • Increased conversions : Marketers can increase the likelihood of turning website visitors into customers by making the user journey more user-friendly and persuasive.
  • Higher revenue : Improved conversion rates aren’t just numbers on a chart ; they translate to tangible revenue. 
  • Increased ROI (return on investment) : By optimising the conversion funnel, you can get more value from your marketing and sales efforts. 
  • Improved customer satisfaction : When customers find it easy and enjoyable to interact with a website or service, it positively influences their satisfaction and likelihood of returning.
  • Data-driven decision-making : Businesses can make informed decisions on budgets and resources based on user behaviour and performance metrics by analysing and optimising conversion funnels.

  ​​Ultimately, conversion funnel optimisation efforts align the entire funnel with overarching business goals.

  10 ways to optimise your conversion funnel 

  Here are 10 ways to optimise your conversion funnel.

  1. Identify and segment your target audience

  The key to a successful conversion funnel begins with a deep understanding of your target audience. 

  Identifying and segmenting your audience lets you speak directly to their pain points, desires and motivations.

  One effective way to know your audience better is by creating detailed buyer personas. These are fictional representations of your ideal customers based on thorough market research and real data. Dive into demographics and behavioural patterns to craft personas that resonate with your audience.

  

  Note that consumer preferences are not static. They evolve, influenced by trends, technological advancements and shifts in societal values. Staying attuned to these changes is crucial as part of optimising your conversion funnel.

  Thus, you must regularly update your buyer personas and adjust your marketing strategies accordingly.

  2. Create content for every stage of the funnel

  Each funnel stage represents a different mindset and needs for your potential customers. Tailoring your content ensures you deliver the right message at the right time to the right audience. 

  Here’s how to tailor your content to fit prospective customers at every conversion funnel stage.

  Awareness-stage content

  Prospects here are seeking information. Your content should be educational and focused on addressing their pain points. Create blog posts, infographics and videos introducing them to your industry, product or service.

  This video we created at Matomo is a prime example of awareness-stage content, grabbing attention and educating viewers about Matomo.

  Consideration-stage content

  Prospects are evaluating their options. Provide content highlighting your product’s unique selling points, such as case studies, product demonstrations and customer testimonials.

  Here’s how we use a versus landing page at Matomo to persuade prospects at this funnel stage.

  

  Conversion-stage content

  This is the final push. Ensure a smooth transition to conversion with content like promotional offers, limited-time discounts and clear calls to action (CTA).

  Loyalty-stage content

  In this stage, you might express gratitude for the purchase through personalised thank-you emails. Follow up with additional resources, tips or exclusive offers to reinforce a positive post-purchase experience. This also positions your brand as a helpful resource beyond the initial sale.

  Reward customer loyalty with exclusive offers, discounts or membership in a loyalty program.

  3. Capture leads

  Lead magnets are incentives offered to potential customers in exchange for their contact information, typically their email addresses. 

  Examples of lead magnets include :

  • Ebooks and whitepapers : In-depth resources that delve into specific topics of interest to your target audience.
  • Webinars and workshops : Live or recorded sessions that offer valuable insights, training or demonstrations.
  • Free trials and demos : Opportunities for potential customers to experience your product or service firsthand.
  • Checklists and templates : Practical tools that help your audience solve specific challenges.
  • Exclusive offers and discounts : Special promotions are available to those who subscribe or provide their contact information.

  For instance, here’s how HubSpot uses templates as lead magnets.

  

  Similarly, you can incorporate your lead magnets into relevant articles or social media posts, email campaigns and other marketing channels.

  4. Optimise your landing pages

  Understanding how visitors interact with your landing pages is a game-changer. So, the first step in optimising your landing pages is to analyse them.

  Enter Matomo’s heatmaps — the secret weapon in landing page optimisation. They visually represent how users interact with your pages, revealing where they linger, what catches their attention and where they may encounter friction. 

  

  Here are a few landing page elements you should pay attention to :

  • Strategic visual elements : Integrate high-quality images, videos and graphics that support your message and guide visitors through the content.
  • Compelling copy : Develop concise and persuasive copy that emphasises the benefits of your offering, addressing user pain points.
  • Effective CTA : Ensure your CTA is prominently displayed, using compelling language and colours that stand out.
  • Mobile responsiveness : Optimise your landing pages for various devices, especially considering the prevalence of mobile users.
  • Minimal form fields : Reduce friction by keeping form fields to a minimum, requesting only essential information.
  • ​​Leverage social proof : Integrate testimonials, reviews and trust badges to build trust and credibility.
  • A/B testing : Experiment with variations in design, copy and CTAs through A/B testing, allowing data to guide your decisions.

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  5. ​​Use compelling Calls to Action (CTAs)

  Crafting compelling CTAs is an art that involves a careful balance of persuasion, clarity and relevance.

  Here are a few tips you can implement to write CTAs that support your goals :

  • Use language that compels action. Instead of generic phrases like “Click Here,” opt for more persuasive alternatives such as “Unlock Exclusive Access” or “Start Your Free Trial.”
  • Make sure your CTAs are clear and straightforward. Visitors should instantly understand what action you want them to take. 
  • Tailor CTAs to the specific content on the page. Whether it’s a blog post, landing page or email, the CTA should seamlessly connect with the surrounding context.
  • Position your CTAs strategically. They should be prominently displayed and easily noticeable, guiding visitors without intruding.
  • Create a sense of urgency. Encourage immediate action by incorporating language that instils a sense of urgency. Phrases like “Limited Time Offer” or “Act Now” can prompt quicker responses.

  6. Have an active social presence

  Social media platforms are bustling hubs of activity where your target audience spends a significant portion of their online time. Cultivating a social media presence allows you to meet your audience where they are, fostering a direct line of communication.

  Moreover, the integration of shopping features directly into social media platforms transforms them into seamless shopping experiences. Nearly half of Instagram users shop weekly through the platform. 

  Also, the US social commerce sales continue to grow each year and are expected to reach $79.64 billion by 2025.

  

  7. Build a brand community

  Four in five customers consider communities important to how engaged they are with a brand.

  A strong community fosters a sense of belonging and loyalty among members. When customers feel connected to your brand and each other, they are more likely to remain loyal over the long term. 

  Also, satisfied community members often share their positive experiences with others, expanding your brand’s reach without additional marketing efforts.

  For example, Nike’s community for runners is a digital space where individuals share their running journeys, accomplishments and challenges. 

  

  By strategically building and nurturing a community, you not only enhance retention and spur referrals but also create a space where your brand becomes an integral part of your customers’ lives. 

  8. Conduct A/B tests

  A/B testing systematically compares two versions of a webpage, email or other content to determine which performs better.

  Examples of elements to A/B test :

  • CTAs : The language, colour, size and placement of CTAs can significantly impact user engagement. A/B testing allows you to discover which variations prompt the desired actions.
  • Headlines : Crafting compelling headlines is an art. Test different versions to identify which headlines resonate best with your audience, whether they are more drawn to clarity, humour, urgency or curiosity.
  • Images : Test different images to understand your audience’s visual preferences. This could include product images, lifestyle shots or graphics.

  

  With Matomo’s A/B testing feature, you can test various elements to see which is successful in converting visitors or moving them to the next stage of the conversion funnel.

  9. Leverage social proof

  In an era where consumers are inundated with choices, the opinions, reviews and endorsements of others serve as beacons, guiding potential customers through the decision-making process. 

  Simply put — when people see that others have had positive experiences with your brand, it instils trust and confidence.

  

  You can proactively gather social proof and display it prominently across your marketing channels. Here are some examples of social proof you can leverage :

  • Customer reviews : Positive reviews and testimonials from satisfied customers serve as authentic endorsements of your products or services. 
  • Case studies : In-depth case studies that showcase successful collaborations or solutions provided to clients offer a detailed narrative of your brand’s capabilities. These are particularly effective in B2B scenarios or for complex products and services.
  • User-generated content : Encourage customers to share their experiences. This could include photos, videos or posts on social media platforms, providing a dynamic and genuine portrayal of your brand.
  • Influencer endorsements : Collaborating with influencers in your industry or niche can amplify your social proof. When influencers vouch for your products or services, their followers are more likely to take notice.

  10. Measure and analyse performance

  This is a continuous loop of refinement, where you should use analysis and data-driven insights to guide your conversion funnel optimisation efforts.

  Here’s a systematic approach you can take :

  1. Identify the path users take on your site using a feature like Users Flow.
  2. Map the customer journey using a Funnels feature like the one in Matomo. 
  3. Identify the metrics that align with your conversion goals at each stage of the funnel, such as website traffic, conversion rates, click-through rates and customer acquisition costs.
  4. Assess conversion rates at different stages of the funnel. Identify areas with significant drop-offs and investigate factors that might contribute to the decline.
  5. Use heatmaps and session recordings to see first-hand how users interact with your site.
  6. Create an experiment to test and improve a specific area within your funnel using insights from the heatmaps and session recordings.
  7. A/B test, analyse the results to understand which variations performed better. Use this data to refine elements within your funnel.

  See how Concrete CMS 3x their leads with conversion optimisation.

  Conclusion 

  The customer journey is not linear. However, it involves a few specific stages your audience will go through — from first learning about your product or services to considering whether to try it. The goal is to turn them into happy and loyal customers.

  In this article, we went over strategies and practical tips you can use to guide customers through the conversion funnel. From segmenting your audience to capturing leads, optimising landing pages and running A/B tests, there are steps you can take to ensure your audience will move to the next stage.

  And of course, you have to continuously measure and analyse your performance. That’s how you know whether you’re heading in the right direction and, if not, where to correct your course. 

  For that, you need a robust web analytics solution with conversion optimisation features. Try Matomo free for 21 days and start optimising your conversion funnel—no credit card required. 

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• A Complete Guide to Metrics in Google Analytics

  11 janvier 2024, par Erin

  There’s no denying that Google Analytics is the most popular web analytics solution today. Many marketers choose it to understand user behaviour. But when it offers so many different types of metrics, it can be overwhelming to choose which ones to focus on. In this article, we’ll dive into how metrics work in Google Analytics 4 and how to decide which metrics may be most useful to you, depending on your analytics needs.

  However, there are alternative web analytics solutions that can provide more accurate data and supplement GA’s existing features. Keep reading to learn how to overcome Google Analytics limitations so you can get the more out of your web analytics.

  What is a metric in Google Analytics ?

  In Google Analytics, a metric is a quantitative measurement or numerical data that provides insights into specific aspects of user behaviour. Metrics represent the counts or sums of user interactions, events or other data points. You can use GA metrics to better understand how people engage with a website or mobile app. 

  Unlike the previous Universal Analytics (the previous version of GA), GA4 is event-centric and has automated and simplified the event tracking process. Compared to Universal Analytics, GA4 is more user-centric and lets you hone in on individual user journeys. Some examples of common key metrics in GA4 are : 

  • Sessions : A group of user interactions on your website that occur within a specific time period. A session concludes when there is no user activity for 30 minutes.
  • Total Users : The cumulative count of individuals who accessed your site within a specified date range.
  • Engagement Rate : The percentage of visits to your website or app that included engagement (e.g., one more pageview, one or more conversion, etc.), determined by dividing engaged sessions by sessions.

  

  Metrics are invaluable when it comes to website and conversion optimisation. Whether you’re on the marketing team, creating content or designing web pages, understanding how your users interact with your digital platforms is essential.

  GA4 metrics vs. dimensions

  GA4 uses metrics to discuss quantitative measurements and dimensions as qualitative descriptors that provide additional context to metrics. To make things crystal clear, here are some examples of how metrics and dimensions are used together : 

  • “Session duration” = metric, “device type” = dimension 
    • In this situation, the dimension can segment the data by device type so you can optimise the user experience for different devices.
  • “Bounce rate” = metric, “traffic source/medium” = dimension 
    • Here, the dimension helps you segment by traffic source to understand how different acquisition channels are performing. 
  • “Conversion rate” = metric, “Landing page” = dimension 
    • When the conversion rate data is segmented by landing page, you can better see the most effective landing pages. 

  You can get into the nitty gritty of granular analysis by combining metrics and dimensions to better understand specific user interactions.

  How do Google Analytics metrics work ?

  Before diving into the most important metrics you should track, let’s review how metrics in GA4 work. 

  

  1. Tracking code implementation

  The process begins with implementing Google Analytics 4 tracking code into the HTML of web pages. This tracking code is JavaScript added to each website page — it collects data related to user interactions, events and other important tidbits.

  2. Data collection

  As users interact with the website or app, the Google Analytics 4 tracking code captures various data points (i.e., page views, clicks, form submissions, custom events, etc.). This raw data is compiled and sent to Google Analytics servers for processing.

  3. Data processing algorithms

  When the data reaches Google Analytics servers, data processing algorithms come into play. These algorithms analyse the incoming raw data to identify the dataset’s trends, relationships and patterns. This part of the process involves cleaning and organising the data.

  4. Segmentation and customisation

  As discussed in the previous section, Google Analytics 4 allows for segmentation and customisation of data with dimensions. To analyse specific data groups, you can define segments based on various dimensions (e.g., traffic source, device type). Custom events and user properties can also be defined to tailor the tracking to the unique needs of your website or app.

  5. Report generation

  Google Analytics 4 can make comprehensive reports and dashboards based on the processed and segmented data. These reports, often in the form of graphs and charts, help identify patterns and trends in the data.

  What are the most important Google Analytics metrics to track ? 

  In this section, we’ll identify and define key metrics for marketing teams to track in Google Analytics 4. 

  

  1. Pageviews are the total number of times a specific page or screen on your website or app is viewed by visitors. Pageviews are calculated each time a web page is loaded or reloaded in a browser. You can use this metric to measure the popularity of certain content on your website and what users are interested in. 
  2. Event tracking monitors user interactions with content on a website or app (i.e., clicks, downloads, video views, etc.). Event tracking provides detailed insights into user engagement so you can better understand how users interact with dynamic content. 
  3. Retention rate can be analysed with a pre-made overview report that Google Analytics 4 provides. This user metric measures the percentage of visitors who return to your website or app after their first visit within a specific time period. Retention rate = (users with subsequent visits / total users in the initial cohort) x 100. Use this information to understand how relevant or effective your content, user experience and marketing efforts are in retaining visitors. You probably have more loyal/returning buyers if you have a high retention rate. 
  4. Average session duration calculates the average time users spend on your website or app per session. Average session duration = total duration of all sessions / # of sessions. A high average session duration indicates how interested and engaged users are with your content. 
  5. Site searches and search queries on your website are automatically tracked by Google Analytics 4. These metrics include search terms, number of searches and user engagement post-search. You can use site search metrics to better understand user intent and refine content based on users’ searches. 
  6. Entrance and exit pages show where users first enter and leave your site. This metric is calculated by the percentage of sessions that start or end on a specific page. Knowing where users are entering and leaving your site can help identify places for content optimisation. 
  7. Device and browser info includes data about which devices and browsers websites or apps visitors use. This is another metric that Google Analytics 4 automatically collects and categorises during user sessions. You can use this data to improve the user experience on relevant devices and browsers. 
  8. Bounce rate is the percentage of single-page sessions where users leave your site or app without interacting further. Bounce rate = (# of single-page sessions / total # of sessions) x 100. Bounce rate is useful for determining how effective your landing pages are — pages with high bounce rates can be tweaked and optimised to enhance user engagement.

  Examples of how Matomo can elevate your web analytics

  Although Google Analytics is a powerful tool for understanding user behaviour, it also has privacy concerns, limitations and a list of issues. Another web analytics solution like Matomo can help fill those gaps so you can get the most out of your analytics.

  

  1. Cross-verify and validate your observations from Google Analytics by comparing data from Matomo’s Heatmaps and Session Recordings for the same pages. This process grants you access to these advanced features that GA4 does not offer.

  

  1. Matomo provides you with greater accuracy thanks to its privacy-friendly design. Unlike GA4, Matomo can be configured to operate without cookies. This means increased accuracy without intrusive cookie consent screens interrupting the user experience. It’s a win for you and for your users. Matomo also doesn’t apply data sampling so you can rest assured that the data you see is 100% accurate.

  3. Unlike GA4, Matomo offers direct access to customer support so you can save time sifting through community forum threads and online documentation. Gain personalised assistance and guidance for your analytics questions, and resolve issues efficiently.

  

  4. Matomo’s Form Analytics and Media Analytics extend your analytics capabilities beyond just pageviews and event tracking.

     Tracking user interactions with forms can tell you which fields users struggle with, common drop-off points, in addition to which parts of the form successfully guide visitors towards submission.

     See first-hand how Concrete CMS 3x their leads using Matomo’s Form Analytics.

     Media Analytics can provide insight into how users interact with image, video, or audio content on your website. You can use this feature to assess the relevance and popularity of specific content by knowing what your audience is engaged by.

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  Final thoughts

  Although Google Analytics is a powerful tool on its own, Matomo can elevate your web analytics by offering advanced features, data accuracy and a privacy-friendly design. Don’t play a guessing game with your data — Matomo provides 100% accurate data so you don’t have to rely on AI or machine learning to fill in the gaps. Matomo can be configured cookieless which also provides you with more accurate data and a better user experience. 

  Lastly, Matomo is fully compliant with some of the world’s strictest privacy regulations like GPDR. You won’t have to sacrifice compliance for accurate, high quality data. 

  Start your 21-day free trial of Matomo — no credit card required.

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• Python-FFMPEG Corruption Problems

  11 juillet 2023, par Gabriel Ruben Guzman

  I'm repurposing some python code to generate gifs/mp4s showcasing nba player movements dot form. (With the 'frames' used in the gifs being generated by matplotlib).

  


  The repo comes with two different functions for generating the gifs, watch_play and animate_play. Both of which use python command line functionalities to run ffmpeg and generate the mp4s.
I've been able to use the watch_play succesfully, bot every time I try using animate_play, which according to the documention is meant to be significantly faster than watch play, I run into the error showcased here.(I printed the cmd string being passed into the pipe, in the hopes it would make debugging easier)

  


  I've tried generating gifs/mp4s of various size and added a decent bit of code to lessen the volume of data being processed. (I'm essentially repurposing the code just to generate clips, so I've been able to remove a lot of the pbp/tracking data logs to speed up the run time) But no matter what I've done, gotten some variation of the screenshotted error.

  


  pipe: : corrupt input packet in stream 0&#xA;[rawvideo @ 0x55ccc0e2bb80] Invalid buffer size, packet size 691200 < expected frame_size 921600&#xA;Error while decoding stream #0:0 : Invalid argument

  &#xA;

  The code for animate_play

  &#xA;

  def animate_play(self, game_time=None, length=None, highlight_player=None,
                 commentary=True, show_spacing=None):
    """
    Method for animating plays in game.
    Outputs video file of play in {cwd}/temp.
    Individual frames are streamed directly to ffmpeg without writing them
    to the disk, which is a great speed improvement over watch_play

    Args:
        game_time (int): time in game to start video
            (seconds into the game).
            Currently game_time can also be an tuple of length two
            with (starting_frame, ending_frame)if you want to
            watch a play using frames instead of game time.
        length (int): length of play to watch (seconds)
        highlight_player (str): If not None, video will highlight
            the circle of the inputed player for easy tracking.
        commentary (bool): Whether to include play-by-play commentary in
            the animation
        show_spacing (str) in ['home', 'away']: show convex hull
            spacing of home or away team.
            If None, does not show spacing.

    Returns: an instance of self, and outputs video file of play
    """
    if type(game_time) == tuple:
        starting_frame = game_time[0]
        ending_frame = game_time[1]
    else:
        game_time= self.start +(self.quarter*720)
        end_time= self.end +(self.quarter*720)
        length = end_time-game_time
        # Get starting and ending frame from requested 
        # game_time and length
        print('hit')
        print(len(self.moments))
        print(game_time)
        print(end_time)
        print(length)
        print(game_time+length)
        
        print(self.moments.game_time.min())
        print(self.moments.game_time.max())

        sys.exit()
        starting_frame = self.moments[self.moments.game_time.round() ==
                                      game_time].index.values[0]
        ending_frame = self.moments[self.moments.game_time.round() ==
                                    game_time + length].index.values[0]

    # Make video of each frame
    filename = "./temp/{game_time}.mp4".format(game_time=game_time)
    if commentary:
        size = (960, 960)
    else:
        size = (480, 480)
    cmdstring = ('ffmpeg',
                 '-y', '-r', '20',  # fps
                 '-s', '%dx%d' % size,  # size of image string
                 '-pix_fmt', 'argb',  # Stream argb data from matplotlib
                 '-f', 'rawvideo','-i', '-',
                 '-vcodec', 'libx264', filename)
    #print(pipe)
    #print(cmdstring)
    
    

    # Stream plots to pipe
    pipe = Popen(cmdstring, stdin=PIPE)
    print(cmdstring)
    for frame in range(starting_frame, ending_frame):
        print(frame)
        self.plot_frame(frame, highlight_player=highlight_player,
                        commentary=commentary, show_spacing=show_spacing,
                        pipe=pipe)
    print(cmdstring)
    pipe.stdin.close()
    pipe.wait()
    return self


  &#xA;

  The code for watch play

  &#xA;

  def watch_play(self, game_time=None, length=None, highlight_player=None,
               commentary=True, show_spacing=None):

    """
    DEPRECIATED.  See animate_play() for similar (fastere) method

    Method for viewing plays in game.
    Outputs video file of play in {cwd}/temp

    Args:
        game_time (int): time in game to start video
            (seconds into the game).
            Currently game_time can also be an tuple of length
            two with (starting_frame, ending_frame) if you want
            to watch a play using frames instead of game time.
        length (int): length of play to watch (seconds)
        highlight_player (str): If not None, video will highlight
            the circle of the inputed player for easy tracking.
        commentary (bool): Whether to include play-by-play
            commentary underneath video
        show_spacing (str in ['home', 'away']): show convex hull
            of home or away team.
            if None, does not display any convex hull

    Returns: an instance of self, and outputs video file of play
    """
    print('hit this point ')
    warnings.warn(("watch_play is extremely slow. "
                   "Use animate_play for similar functionality, "
                   "but greater efficiency"))

    if type(game_time) == tuple:
        starting_frame = game_time[0]
        ending_frame = game_time[1]
    else:
        # Get starting and ending frame from requested game_time and length
        game_time= self.start +(self.quarter*720)
        end_time= self.end +(self.quarter*720)
        length = end_time-game_time


        starting_frame = self.moments[self.moments.game_time.round() ==
                                      game_time].index.values[0]
        ending_frame = self.moments[self.moments.game_time.round() ==
                                    game_time + length].index.values[0]
    #print(self.moments.head(2))
    #print(starting_frame)
    #print(ending_frame)
    print(len(self.moments))
    # Make video of each frame
    title = str(starting_frame)+'-'+str(ending_frame)
    for frame in range(starting_frame, ending_frame):
        print(frame)
        self.plot_frame(frame, highlight_player=highlight_player,
                        commentary=commentary, show_spacing=show_spacing)
    command = ('ffmpeg -framerate 20 -start_number {starting_frame} '
               '-i %d.png -c:v libx264 -r 30 -pix_fmt yuv420p -vf '
               '"scale=trunc(iw/2)*2:trunc(ih/2)*2" {title}'
               '.mp4').format(starting_frame=starting_frame,title=title)
    os.chdir('temp')
    os.system(command)
    os.chdir('..')

    # Delete images
    for file in os.listdir('./temp'):
        if os.path.splitext(file)[1] == '.png':
            os.remove('./temp/{file}'.format(file=file))

    return self'


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