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• Adding A New System To The Game Music Website

  1er août 2012, par Multimedia Mike — General

  At first, I was planning to just make a little website where users could install a Chrome browser extension and play music from old 8-bit NES games. But, like many software projects, the goal sort of ballooned. I created a website where users can easily play old video game music. It doesn’t cover too many systems yet, but I have had individual requests to add just about every system you can think of.

  The craziest part is that I know it’s possible to represent most of the systems. Eventually, it would be great to reach Chipamp parity (a combination plugin for Winamp that packages together plugins for many of these chiptunes). But there is a process to all of this. I have taken to defining a number of phases that are required to get a new system covered.

  Phase 0 informally involves marveling at the obscurity of some of the console systems for which chiptune collections have evolved. WonderSwan ? Sharp X68000 ? PC-88 ? I may be viewing this through a terribly Ameri-centric lens. I’ve at least heard of the ZX Spectrum and the Amstrad CPC even if I’ve never seen either.

  No matter. The goal is to get all their chiptunes cataloged and playable.

  Phase 1 : Finding A Player
  The first step is to find a bit of open source code that can play a particular format. If it’s a library that can handle many formats, like Game Music Emu or Audio Overload SDK, even better (probably). The specific open source license isn’t a big concern for me. I’m almost certain that some of the libraries that SaltyGME currently mixes are somehow incompatible, license-wise. I’ll worry about it when I encounter someone who A) cares, and B) is in a position to do something about it. Historical preservation comes first, and these software libraries aren’t getting any younger (I’m finding some that haven’t been touched in a decade).

  Phase 2 : Test Program
  The next phase is to create a basic test bench program that sends a music file into the library, generates a buffer of audio, and shoves it out to the speakers via PulseAudio’s simple API (people like to rip on PulseAudio, but its simple API really lives up to its name and requires pages less boilerplate code to play a few samples than ALSA).

  Phase 3 : Plug Into Web Player
  After successfully creating the test bench and understanding exactly which source files need to be built, the next phase is to hook it up to the main SaltyGME program via the ad-hoc plugin API I developed. This API requires that a player backend can, at the very least, initialize itself based on a buffer of bytes and generate audio samples into an array of 16-bit numbers. The API also provides functions for managing files with multiple tracks and toggling individual voices/channels if the library supports such a feature. Having the test bench application written beforehand usually smooths out this step.

  But really, I’m just getting started.

  Phase 4 : Collecting A Song Corpus
  Then there is the matter of staging a collection of songs for a given system. It seems like it would just be a matter of finding a large collection of songs for a given format, downloading them in bulk, and mirroring them. Honestly, that’s the easy part. People who are interested in this stuff have been lovingly curating massive collections of these songs for years (see SNESmusic.org for one of the best examples, and they also host a torrent of all their music for really quick and easy hoarding).
  
  In my drive to make this game music website more useful for normal people, the goal is to extract as much metadata as possible to make searching better, and to package the data so that it’s as convenient as possible for users. Whenever I seek to add a new format to the collection, this is the phase where I invariably find that I have to fundamentally modify some of the assumptions I originally made in the player.

  First, there were the NES Sound Format (NSF) files, the original format I wanted to play. These are files that have any number of songs packed into a single file. Playback libraries expose APIs to jump to individual tracks. So the player was designed around that. Game Boy GBS files also fall into this category but present a different challenge vis-à-vis metadata, addressed in the next phase.

  Then, there were the SPC files. Each SPC file is its own song and multiple SPC files are commonly bundled as RAR files. Not wanting to deal with RAR, or any format where I interacted with a general compression API to pull a few files out, I created a custom resource format (inspired by so many I have studied and documented) and compressed it with a simpler compression API. I also had to modify some of the player’s assumptions to deal with this archive format. Genesis VGMs, bundled either in .zip or .7z, followed the same model as SPC in RAR.

  Then it was suggested that I attempt to bring SaltyGME closer to feature parity with Chipamp, rather than just being a Chrome browser frontend for Game Music Emu. When I studied the Portable Sound Format (PSF), I realized it didn’t fit into the player model I already had. PSF uses a sort of shared library model for code execution and I developed another resource archive format to cope with it. So that covers quite a few formats.

  One more architecture challenge arose when I started to study one of the prevailing metadata formats, explained in the next phase.

  Phase 5 : Metadata
  Finally, for the collections to really be useful, I need to harvest that juicy metadata for search and presentation.

  I have created a series of programs and scripts to scrape metadata out of these music files and store it all in a database that drives the website and search engine. I recognize that it’s no good to have a large corpus of songs with minimal metadata and while importing bulk quantities of music, the scripts harshly reject songs that have too little metadata.

  Again, challenges abound. One of the biggest challenges I’m facing is the peculiar quasi-freeform metadata format that emerged as .m3u that takes a form similar to :

  #################################################################
  #
  # GRADIUS2
  # (c) KONAMI  by Furukawa Motoaki, IKACHAN
  #
  #################################################################
  nemesis2.kss::KSS,62,[Nemesis2] (Opening),2:23,,0
  
  nemesis2.kss::KSS,61,[Nemesis2] (Start),7,,0
  
  nemesis2.kss::KSS,43,[Nemesis2] (Air Battle),34,0-
  
  nemesis2.kss::KSS,44,[Nemesis2] (1st. BGM),51,0-
  
  [...]
  

  A lot of file formats (including Game Boy GBS mentioned earlier) store their metadata separately using this format. I have some ideas about tools I can use to help me process this data but I’m pretty sure each one will require some manual intervention.

  As alluded to in phase 4, .m3u presents another architectural challenge : Notice the second field in the CSV .m3u data. That’s a track number. A player can’t expect every track in a bundled chiptune file to be valid, nor to be in any particular order. Thus, I needed to alter the architecture once more to take this into account. However, instead of modifying the SaltyGME player, I simply extended the metadata database to include a playback order which, by default, is the same as the track order but can also accommodate this new issue. This also has the bonus of providing a facility to exclude playback of certain tracks. This comes in handy for many PSF archives which tend to include files that only provide support for other files and aren’t meant to be played on their own.

  Bright Side
  The reward for all of this effort is that the data lands in a proper database in the end. None of it goes back into the chiptune files themselves. This makes further modification easier as all of the data that is indexed and presented on the site comes from the database. Somewhere down the road, I should probably create an API for accessing this metadata.

• How to Implement Cross-Channel Analytics : A Guide for Marketers

  17 avril 2024, par Erin

  Every modern marketer knows they have to connect with consumers across several channels. But do you know how well Instagram works alongside organic traffic or your email list ? Are you even tracking the impacts of these channels in one place ?

  You need a cross-channel analytics solution if you answered no to either of these questions. 

  In this article, we’ll explain cross-channel analytics, why your company probably needs it and how to set up a cross-channel analytics solution as quickly and easily as possible.

  What is cross-channel analytics ? 

  Cross-channel analytics is a form of marketing analytics that collects and analyses data from every channel and campaign you use.

  The result is a comprehensive view of your customer’s journey and each channel’s role in converting customers. 

  Cross-channel analytics lets you track every channel you use to convert customers, including :

  • Your website
  • Social media profiles
  • Email
  • Paid search
  • E-commerce
  • Retargeting campaigns

  Cross-channel analytics solves one of the most significant issues of cross-channel or multi-channel marketing efforts : measurement. 

  Research shows that only 16% of marketing tech stacks allow for accurate measurement of multi-channel initiatives across channels. 

  That’s a problem, given the staggering number of touchpoints in a typical buyer’s conversion path. However, it can be fixed using a cross-channel analytics approach that lets you measure the performance of every channel and assign a dollar value to its role in every conversion. 

  The difference between cross-channel analytics and multi-channel analytics

  Cross-channel analytics and multi-channel analytics sound very similar, but there’s one key difference you need to know. Multi-channel analytics measures the performance of several channels, but not necessarily all of them, nor the extent to which they work together to drive conversions. Conversely, cross-channel analytics measures the performance of all your marketing channels and how they work together. 

  What are the benefits of cross-channel analytics 

  Cross-channel analytics offers a lot of marketing and business benefits. Here are the ones marketing managers love most.

  Get a complete view of the customer journey

  Implementing a cross-channel analytics solution is the only way to get a complete view of your customer journey. 

  Cross-channel marketing analytics lets you see your customer journey in high definition, allowing you to build comprehensive customer profiles using data from multiple sources across every touchpoint. 

  

  The result ? You get to understand how every customer behaves at every point of the customer journey, why they convert or leave your funnel, and which channels play the biggest role. 

  In short, you get to see why customers convert so you can learn how to convert more of them.

  Personalise the customer experience

  According to a McKinsey study, customers demand personalisation, and brands that excel at it generate 40% more revenue. Deliver the personalisation they desire and reap the benefits with cross-channel analytics. 

  When you understand the customer journey in detail, it becomes much easier to personalise your website and marketing efforts to their preferences and behaviours.

  Identify your most effective marketing channels

  Cross-channel marketing helps you understand your marketing efforts to see how every channel impacts conversions. 

  Take a look at the screenshot from Matomo below. Cross-channel analytics lets you get incredibly granular — we can see the number of conversions of organic search drives and the performance of individual search engines. 

  

  This makes it easy to identify your most effective marketing channels and allocate your resources appropriately. It also allows you to ask (and answer) which channels are the most effective.

  Try Matomo for Free

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

  Start for free

  No credit card required

  Attribute conversions accurately 

  An attribution model decides how you assign credit for each customer conversion to different touchpoints on the customer journey. Without a cross-channel analytics solution, you’re stuck using a standard attribution model like first or last click. 

  These models will show you how customers first found your brand or which channel finally convinced them to convert, but it doesn’t help you understand the role all your channels played in the conversion. 

  Cross-channel analytics solves this attribution problem. Rather than attributing a conversion to the touchpoint that directly led to the sale, cross-channel data gives you the real picture and allows you to use multi-touch attribution to understand which touchpoints generate the most revenue.

  How to set up cross-channel analytics

  Now that you know what cross-channel analytics is and why you should use it, here’s how to set up your solution. 

  1. Determine your objectives

  Defining your marketing goals will help you build a more relevant and actionable cross-channel analytics solution. 

  If you want to improve marketing attribution, for example, you can choose a platform with that feature built-in. If you care about personalisation, you could choose a platform with A/B testing capabilities to measure the impact of your personalisation efforts. 

  1. Set relevant KPIs

  You’ll want to track relevant KPIs to measure the marketing effectiveness of each channel. Put top-of-the-funnel metrics aside and focus on conversion metrics. 

  These include :

  • Conversion rate
  • Average visit duration
  • Bounce rate

  1. Implement tracking and analytics tools

  Gathering customer data from every channel and centralising it in a single location is one of the biggest challenges of cross-channel analytics. Still, it’s made easier with the right tracking tool or analytics platform. 

  The trick is to choose a platform that lets you measure as many of your channels as possible in a single platform. With Matomo, for example, you can track search, paid search, social and email campaigns and your website analytics.

  1. Set up a multi-touch attribution model

  Now that you have all of your data in one place, you can set up a multi-touch attribution model that lets you understand the extent to which each marketing channel contributes to your overall success. 

  There are several attribution models to choose from, including :

  

  Each model has benefits and drawbacks, so choosing the right model for your organisation can be tricky. Rather than take a wild guess, evaluate each model against your marketing objectives, sales length cycle and data availability.

  For example, if you want to focus on optimising customer acquisition costs, a model that prioritises earlier touchpoints will be better. If you care about conversions, you might try a time decay model. 

  1. Turn data into insights with reports

  One of the big benefits of choosing a tool like Matomo, which consolidates data in one place, is that it significantly speeds up and simplifies reporting.

  When all the data is stored in one platform, you don’t need to spend hours combing through your social media platforms and copying and pasting analytics data into a spreadsheet. It’s all there and ready for you to run reports.

  Try Matomo for Free

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

  Start for free

  No credit card required

  1. Take action

  There’s no point implementing a cross-channel analytics system if you aren’t going to take action. 

  But where should you start ?

  Optimising your budgets and prioritising marketing spend is a great starting point. Use your cross-channel insights to find your most effective marketing channels (they’re the ones that convert the most customers or have the highest ROI) and allocate more of your budget to them. 

  You can also optimise the channels that aren’t pulling their weight if social media is letting you down ; for example, experiment with tactics like social commerce that could drive more conversions. Alternatively, you could choose to stop investing entirely in these channels.

  Cross-channel analytics best practices

  If you already have a cross-channel analytics solution, take things to the next level with the following best practices. 

  Use a centralised solution to track everything

  Centralising your data in one analytics tool can streamline your marketing efforts and help you stay on top of your data. It won’t just save you from tabbing between different browsers or copying and pasting everything into a spreadsheet, but it can also make it easier to create reports. 

  Think about consumer privacy 

  If you are looking at a new cross-channel analytics tool, consider how it accounts for data privacy regulations in your area. 

  You’re going to be collecting a lot of data, so it’s important to respect their privacy wishes. 

  It’s best to choose a platform like Matomo that complies with the strictest privacy laws (CCPA, GDPR, etc.).

  Monitor data in real time

  So, you’ve got a holistic view of your marketing efforts by integrating all your channels into a single tool ?

  Great, now go further by monitoring the impact of your marketing efforts in real time.

  

  With a web analytics platform like Matomo, you can see who visits your site, what they do, and where they come from through features like the visits log report, which even lets you view individual user sessions. This lets you measure the impact of posting on a particular social channel or launching a new offer. 

  Try Matomo for Free

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

  Start for free

  No credit card required

  Reallocate marketing budgets based on performance

  When you track every channel, you can use a multi-touch attribution model like position-based or time-decay to give every channel the credit it deserves. But don’t just credit each channel ; turn your valuable insights into action. 

  Use cross-channel attribution analytics data to reallocate your marketing budget to the most profitable channels or spend time optimising the channels that aren’t pulling their weight. 

  Cross-channel analytics platforms to get started with 

  The marketing analytics market is huge. Mordor Intelligence valued it at $6.31 billion in 2024 and expects it to reach $11.54 billion by 2029. Many of these platforms offer cross-channel analytics, but few can track the impact of multiple marketing channels in one place. 

  So, rather than force you to trawl through confusing product pages, we’ve shortlisted three of the best cross-channel analytics solutions. 

  Matomo

  

  Matomo is a web analytics platform that lets you collect and centralise your marketing data while giving you 100% accurate data. That includes search, social, e-commerce, campaign tracking data and comprehensive website analytics.

  Better still, you get the necessary tools to turn those insights into action. Custom reporting lets you track and visualise the metrics that matter, while conversion optimisation tools like built-in A/B testing, heatmaps, session recordings and more let you test your theories. 

  Google Analytics

  

  Google Analytics is the most popular and widely used tool on the market. The level of analysis and customisation you can do with it is impressive for a free tool. That includes tracking just about any event and creating reports from scratch. 

  Google Analytics provides some cross-channel marketing features and lets you track the impact of various channels, such as social and search, but there are a couple of drawbacks. 

  Privacy can be a concern because Google Analytics collects data from your customers for its own remarketing purposes. 

  It also uses data sampling to generate wider insights from a small subset of your data. This lack of accurate data reporting can cause you to generate false insights.

  With Google Analytics, you’ll also need to subscribe to additional tools to gain advanced insights into the user experience. So, consider that while this tool is free, you’ll need to pay for heatmaps, session recording and A/B testing tools to optimise effectively.

  Improvado

  

  Improvado is an analytics tool for sales and marketing teams that extracts thousands of metrics from hundreds of sources. It centralises data in data warehouses, from which you can create a range of marketing dashboards.

  While Improvado does have analytics capabilities, it is primarily an ETL (extraction, transform, load) tool for organisations that want to centralise all their data. That means marketers who aren’t familiar with data transformations may struggle to get their heads around the complexity of the platform.

  Make the most of cross-channel analytics with Matomo

  Cross-channel analytics is the only way to get a comprehensive view of your customer journey and understand how your channels work together to drive conversions.

  Then you’re dealing with so many channels and data ; keeping things as simple as possible is the key to success. That’s why over 1 million websites choose Matomo. 

  Our all-in-one analytics solution measures traditional web analytics, behavioural analytics, attribution and SEO, so you have 100% accurate data in one place. 

  Try it free for 21 days. No credit card required.

  Try Matomo for Free

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• Revision 28933 : on bouge

  31 mai 2009, par ben.spip@… — Log

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