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• Benefits and Shortcomings of Multi-Touch Attribution

  13 mars 2023, par Erin — Analytics Tips

  Few sales happen instantly. Consumers take their time to discover, evaluate and become convinced to go with your offer. 

  Multi-channel attribution (also known as multi-touch attribution or MTA) helps businesses better understand which marketing tactics impact consumers’ decisions at different stages of their buying journey. Then double down on what’s working to secure more sales. 

  Unlike standard analytics, multi-channel modelling combines data from various channels to determine their cumulative and independent impact on your conversion rates. 

  The main benefit of multi-touch attribution is obvious : See top-performing channels, as well as those involved in assisted conversions. The drawback of multi-touch attribution : It comes with a more complex setup process. 

  If you’re on the fence about getting started with multi-touch attribution, here’s a summary of the main arguments for and against it. 

  What Are the Benefits of Multi-Touch Attribution ?

  Remember an old parable of blind men and an elephant ?

  Each one touched the elephant and drew conclusions about how it might look. The group ended up with different perceptions of the animal and thought the others were lying…until they decided to work together on establishing the truth.

  Multi-channel analytics works in a similar way : It reconciles data from various channels and campaign types into one complete picture. So that you can get aligned on the efficacy of different campaign types and gain some other benefits too. 

  Better Understanding of Customer Journeys 

  On average, it takes 8 interactions with a prospect to generate a conversion. These interactions happen in three stages : 

  • Awareness : You need to introduce your company to the target buyers and pique their interest in your solution (top-of-the-funnel). 
  • Consideration : The next step is to channel this casual interest into deliberate research and evaluation of your offer (middle-of-the-funnel). 
  • Decision : Finally, you need to get the buyer to commit to your offer and close the deal (bottom-of-the-funnel). 

  You can analyse funnels using various attribution models — last-click, fist-click, position-based attribution, etc. Each model, however, will spotlight the different element(s) of your sales funnel. 

  For example, a single-touch attribution model like last-click zooms in on the bottom-of-the-funnel stage. You can evaluate which channels (or on-site elements) sealed the deal for the prospect. For example, a site visitor arrived from an affiliate link and started a free trial. In this case, the affiliate (referral traffic) gets 100% credit for the conversion. 

  This measurement tactic, however, doesn’t show which channels brought the customer to the very bottom of your funnel. For instance, they may have interacted with a social media post, your landing pages or a banner ad before that. 

  Multi-touch attribution modelling takes funnel analysis a notch further. In this case, you map more steps in the customer journey — actions, events, and pages that triggered a visitor’s decision to convert — in your website analytics tool.

  

  Then, select a multi-touch attribution model, which provides more backward visibility aka allows you to track more than one channel, preceding the conversion. 

  For example, a Position Based attribution model reports back on all interactions a site visitor had between their first visit and conversion. 

  A prospect first lands at your website via search results (Search traffic), which gets a 40% credit in this model. Two days later, the same person discovers a mention of your website on another blog and visits again (Referral traffic). This time, they save the page as a bookmark and revisit it again in two more days (Direct traffic). Each of these channels will get a 10% credit. A week later, the prospect lands again on your site via Twitter (Social) and makes a request for a demo. Social would then receive a 40% credit for this conversion. Last-click would have only credited social media and first-click — search engines. 

  The bottom line : Multi-channel attribution models show how different channels (and marketing tactics) contribute to conversions at different stages of the customer journey. Without it, you get an incomplete picture.

  Improved Budget Allocation 

  Understanding causal relationships between marketing activities and conversion rates can help you optimise your budgets.

  First-click/last-click attribution models emphasise the role of one channel. This can prompt you toward the wrong conclusions. 

  For instance, your Facebook ads campaigns do great according to a first-touch model. So you decide to increase the budget. What you might be missing though is that you could have an even higher conversion rate and revenue if you fix “funnel leaks” — address high drop-off rates during checkout, improve page layout and address other possible reasons for exiting the page.

  

  By knowing when and why people abandon their purchase journey, you can improve your marketing velocity (aka the speed of seeing the campaign results) and your marketing costs (aka the budgets you allocate toward different assets, touchpoints and campaign types). 

  Or as one of the godfathers of marketing technology, Dan McGaw, explained in a webinar :

  “Once you have a multi-touch attribution model, you [can] actually know the return on ad spend on a per-campaign basis. Sometimes, you can get it down to keywords. Sometimes, you can get down to all kinds of other information, but you start to realise, “Oh, this campaign sucks. I should shut this off.” And then really, that’s what it’s about. It’s seeing those campaigns that suck and turning them off and then taking that budget and putting it into the campaigns that are working”.

  More Accurate Measurements 

  The big boon of multi-channel marketing attribution is that you can zoom in on various elements of your funnel and gain granular data on the asset’s performance. 

  In other words : You get more accurate insights into the different elements involved in customer journeys. But for accurate analytics measurements, you must configure accurate tracking. 

  Define your objectives first : How do you want a multi-touch attribution tool to help you ? Multi-channel attribution analysis helps you answer important questions such as :

  • How many touchpoints are involved in the conversions ? 
  • How long does it take for a lead to convert on average ? 
  • When and where do different audience groups convert ? 
  • What is your average win rate for different types of campaigns ?

  Your objectives will dictate which multi-channel modelling approach will work best for your business — as well as the data you’ll need to collect. 

  At the highest level, you need to collect two data points :

  • Conversions : Desired actions from your prospects — a sale, a newsletter subscription, a form submission, etc. Record them as tracked Goals. 
  • Touchpoints : Specific interactions between your brand and targets — specific page visits, referral traffic from a particular marketing channel, etc. Record them as tracked Events. 

  Your attribution modelling software will then establish correlation patterns between actions (conversions) and assets (touchpoints), which triggered them. 

  The accuracy of these measurements, however, will depend on the quality of data and the type of attribution modelling used. 

  Data quality stands for your ability to procure accurate, complete and comprehensive information from various touchpoints. For instance, some data won’t be available if the user rejected a cookie consent banner (unless you’re using a privacy-focused web analytics tool like Matomo). 

  Different attribution modelling techniques come with inherent shortcomings too as they don’t accurately represent the average sales cycle length or track visitor-level data, which allows you to understand which customer segments convert best.

  Learn more about selecting the optimal multi-channel attribution model for your business.

  What Are the Limitations of Multi-Touch Attribution ?

  Overall, multi-touch attribution offers a more comprehensive view of the conversion paths. However, each attribution model (except for custom ones) comes with inherent assumptions about the contribution of different channels (e.g,. 25%-25%-25%-25% in linear attribution or 40%-10%-10%-40% in position-based attribution). These conversion credit allocations may not accurately represent the realities of your industry. 

  Also, most attribution models don’t reflect incremental revenue you gain from existing customers, which aren’t converting through analysed channels. For example, account upgrades to a higher tier, triggered via an in-app offer. Or warranty upsell, made via a marketing email. 

  In addition, you should keep in mind several other limitations of multi-touch attribution software.

  Limited Marketing Mix Analysis 

  Multi-touch attribution tools work in conjunction with your website analytics app (as they draw most data from it). Because of that, such models inherit the same visibility into your marketing mix — a combo of tactics you use to influence consumer decisions.

  Multi-touch attribution tools cannot evaluate the impact of :

  • Dark social channels 
  • Word-of-mouth 
  • Offline promotional events
  • TV or out-of-home ad campaigns 

  If you want to incorporate this data into your multi-attribution reporting, you’ll have to procure extra data from other systems — CRM, ad measurement partners, etc, — and create complex custom analytics models for its evaluation.

  Time-Based Constraints 

  Most analytics apps provide a maximum 90-day lookback window for attribution. This can be short for companies with longer sales cycles. 

  

  Marketing channels can be overlooked or underappreciated when your attribution window is too short. Because of that, you may curtail spending on brand awareness campaigns, which, in turn, will reduce the number of people entering the later stages of your funnel. 

  At the same time, many businesses would also want to track a look-forward window — the revenue you’ll get from one customer over their lifetime. In this case, not all tools may allow you to capture accurate information on repeat conversions — through re-purchases, account tier updates, add-ons, upsells, etc. 

  Again, to get an accurate picture you’ll need to understand how far into the future you should track conversions. Will you only record your first sales as a revenue number or monitor customer lifetime value (CLV) over 3, 6 or 12 months ? 

  The latter is more challenging to do. But CLV data can add another depth of dimension to your modelling accuracy. With Matomo, you set up this type of tracking by using our visitors’ tracking feature. We can help you track select visitors with known identifiers (e.g. name or email address) to discover their visiting patterns over time. 

  

  Limited Access to Raw Data 

  In web analytics, raw data stands for unprocessed website visitor information, stripped from any filters, segmentation or sampling applied. 

  Data sampling is a practice of analysing data subsets (instead of complete records) to extrapolate findings towards the entire data set. Google Analytics 4 applies data sampling once you hit over 500k sessions at the property level. So instead of accurate, real-life reporting, you receive approximations, generated by machine learning models. Data sampling is one of the main reasons behind Google Analytics’ accuracy issues. 

  In multi-channel attribution modelling, usage of sampled data creates further inconsistencies between the reports and the actual state of affairs. For instance, if your website generates 5 million page views, GA multi-touch analytical reports are based on the 500K sample size aka only 90% of the collected information. This hardly represents the real effect of all marketing channels and can lead to subpar decision-making. 

  With Matomo, the above is never an issue. We don’t apply data sampling to any websites (no matter the volume of traffic) and generate all the reports, including multi-channel attribution ones, based on 100% real user data. 

  AI Application 

  On the other hand, websites with smaller traffic volumes often have limited sampling datasets for building attribution models. Some tracking data may also be not available because the visitor rejected a cookie banner, for instance. On average, less than 50% of users in Australia, France, Germany, Denmark and the US among other countries always consent to all cookies. 

  To compensate for such scenarios, some multi-touch attribution solutions apply AI algorithms to “fill in the blanks”, which impacts the reporting accuracy. Once again, you get approximate data of what probably happened. However, Matomo is legally exempt from showing a cookie consent banner in most EU markets. Meaning you can collect 100% accurate data to make data-driven decisions.

  Difficult Technical Implementation 

  Ever since attribution modelling got traction in digital marketing, more and more tools started to emerge.

  

  Most web analytics apps include multi-touch attribution reports. Then there are standalone multi-channel attribution platforms, offering extra features for conversion rate optimization, offline channel tracking, data-driven custom modelling, etc. 

  Most advanced solutions aren’t available out of the box. Instead, you have to install several applications, configure integrations with requested data sources, and then use the provided interfaces to code together custom data models. Such solutions are great if you have a technical marketer or a data science team. But a steep learning curve and high setup costs make them less attractive for smaller teams. 

  Conclusion 

  Multi-touch attribution modelling lifts the curtain in more steps, involved in various customer journeys. By understanding which touchpoints contribute to conversions, you can better plan your campaign types and budget allocations. 

  That said, to benefit from multi-touch attribution modelling, marketers also need to do the preliminary work : Determine the key goals, set up event and conversion tracking, and then — select the optimal attribution model type and tool. 

  Matomo combines simplicity with sophistication. We provide marketers with familiar, intuitive interfaces for setting up conversion tracking across the funnel. Then generate attribution reports, based on 100% accurate data (without any sampling or “guesstimation” applied). You can also get access to raw analytics data to create custom attribution models or plug it into another tool ! 

  Start using accurate, easy-to-use multi-channel attribution with Matomo. Start your free 21-day trial now. No credit card requried. 

• What is White Label Analytics ? Everything You Need to Know

  6 février 2024, par Erin

  Reports are a core part of a marketing agency’s offering. It’s how you build trust with clients by highlighting your efforts and demonstrating your results. 

  But all too often, those reports deliver a jarring and incohesive experience. The culprit ? The logos, colours and names of third-party brands your agency uses to deliver work and create the reports. 

  Luckily, there’s a way to make sure your reports elevate your agency’s stature ; not undermine it. 

  By white labelling your tools, you can deliver a clear and cohesive brand experience — one that strengthens the client relationship rather than diminishing it. 

  In this article, we explain what white label analytics tools are, why it’s important to white label your analytics solution and how you can do it using Matomo. 

  What is white label analytics ?

  White labelling is the process of redesigning a product or service using your company’s brand. The term comes from the act of putting a white label on a product that covers the original branding and allows the reseller to personalise the product.

  White label analytics, then, is a way to customise your analytics software with your agency’s logo and colours. When you white label your analytics, you ensure your reports, dashboards and interface provide a consistent and familiar user experience.

  

  The alternative is to provide your clients with an analytics report containing the logo and branding of your analytics software provider — whether that’s Google Analytics, Matomo, or another tool. 

  For some clients, it can create a confusing experience that takes attention away from your agency’s results.

  Why white label analytics is important

  There are plenty of reasons to white label your analytics tool, from improving your client’s experience to generating additional revenue. Here are four of the most important benefits to know :

  

  Improve the client experience

  You want your clients to have a seamless user experience with your agency’s brand, whether they visit your website, log into their client portal, or read one of your reports. 

  By white labelling your analytics platform, you can give your clients a visually appealing experience that stays in line with the rest of your branding and doesn’t leave them confused about who they are interacting with or which company is providing the service they pay for. 

  This is especially important if your agency uses other third-party tools like a client portal or productivity platform that also allows for custom branding. 

  Strengthen client relationships

  When you use white labelling to remove solution providers’ logos, you ensure your brand gets all of the credit for the hard work you’ve been doing. This can strengthen the agency-client relationship and reaffirm the importance of your agency. 

  But, white labelling allows you to tell a better story through your reports and increases the perceived value you offer. There are no other brands, logos, or names to confuse the narrative or detract from your key points — or to stop the client from understanding just how much value you provide. 

  Save time and increase productivity 

  White labelling your analytics platform can save your team a significant amount of time when creating client reports. 

  There’s no need to carefully screenshot graphs to add them to your own branded report. You can simply email clients a report using your white labelled analytics platform, assuring them of a seamlessly branded experience.

  The upshot is that your team can spend more time on billable work, improving the value they deliver to existing clients or opening up capacity to take on even more work. 

  Increase monetisation opportunities

  Whether you are an agency or consultant, white labelling an analytics solution gives you the opportunity to package and sell analytics as part of your own services. This can open up new revenue streams, help you to diversify your income, and reach a wider audience.

  The beauty of a white label offering is that there is no allusion to the company providing the underlying service.

  The most important elements of an analytics platform to white label 

  A white label analytics solution should offer a broad range of customisation options that range from surface-level branding to functional elements like tracking codes. 

  Below we take a look at the top components you should be able to customise with your chosen platform. 

  Logo and Favicon

  The logo is the first thing clients will see when they open up their analytics platform or look at your reports. It should make your services instantly recognisable, which is why it’s so jarring when clients read a report with another company’s brand slapped on every chart. 

  This should be the very first thing you change since it will be on almost every page and report your client views. Don’t stop there, however. If you send clients web-based reports, you’ll also want to change the platform’s favicon — the small logo you see next to your website in a browser. 

  Customising both your logo and favicon is easy with Matomo. 

  Just head to Administration, then General Settings and click Use a custom Logo under Brand settings.

  

  Upload your brand, click Save, and it will automatically populate your brand in place of the Matomo logo across the platform, just like in the image above.

  Brand name

  Most analytics platforms will mention their brand names repeatedly across the site, so it’s important to change these, too.

  Otherwise, you risk clients reading your analytics reports in detail or playing around with your platform’s settings and getting confused when another seemingly unrelated name keeps popping up. 

  Again, this is easily done with Matomo’s White Label plugin. 

  Head to Administration, then General Settings. Scroll to the bottom of the page to find WhiteLabel settings.

  Enter your brand or product name in the first box and click Save. 

  

  Just like your logo, this will replace every instance of Matomo’s brand name with your own.

  Brand colours

  Changing your analytics platform’s colours to match your own is almost as important as swapping out the logo. 

  Failure to do so could mean the charts and graphs you add to your client reports could cause confusion. 

  You can also use Matomo’s WhiteLabel settings to change the platform’s background and font colours. 

  Just enter a new header background and font colour using hexadecimal values.

  

  This change will also apply to automated email reports. 

  Custom tracking

  Tracking requests and links are an overlooked element of analytics when it comes to white labelling. Most people wouldn’t think twice about them, but they are an easy way for someone in the know to identify which platform you are using. 

  With Matomo’s White Label plugin, it’s possible to customise every request Matomo makes to your clients’ websites. 

  If left unbranded, tracking requests contain the following references : matomo.js and matomo.php. 

  By clicking the Whitelabel tracking endpoint box on the WhiteLabel settings page, those references will be replaced with js/tracker.js and js/tracker.php

  You’ll need to update your tracking code to reflect these changes, otherwise, requests will still contain Matomo branding. 

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  Links

  Finally, you’ll want to remove any links to any additional content offered by the analytics company. These are usually included to improve the user experience, but they are best removed if you are letting clients access your platform. 

  With Matomo, you can remove all links by clicking the relevant box in WhiteLabel settings. 

  You can also use the Show Marketplace only to Super Users checkbox to limit the visibility of Matomo’s Marketplace to everyone bar Super Users.

  Can you white label Google Analytics ?

  In a word : no. 

  Google Analytics might be the most popular analytics platform, but it comes up short if you want to customise its appearance. 

  This can be a particular problem for agencies that need to stand out from competitors offering the same generic reports. You can add more context, detail and graphs to your analytics reports, of course. But you’ll never be able to create completely custom, brand-cohesive reports using Google Analytics. 

  3 analytics platforms you can white label

  While you can’t white label Google Analytics, there are several web analytics providers that do offer a white labelling service. Here are three of the best :

  Matomo

  As you’ve already seen, Matomo is the ideal web analytics platform if you want to let your own brand shine through. Matomo lets you personalise the entire dashboard and all of your reports. That includes :

  • Adding your brand logo and favicon
  • Changing the font and background colours 
  • Removing third-party links
  • Tracking using custom URLs 
  • Develop your own custom theme

  Matomo offers a 21-day free trial (no credit card required). If you want to get remove the Matomo branding, you need the White Label plugin, which starts at just $179 per year after a free trial.

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  Clicky

  Clicky is a simple, privacy-focused web analytics platform with a white label offering. Like Matomo, you can add your logo and change the platform’s colours. 

  Clicky offers a seven-day free trial and charges a $99 setup fee, with prices starting from $49 and rising to $399. 

  Plausible 

  Plausible is another privacy-focused Google Analytics alternative that offers white labelling. The difference here is that it’s pretty complex to set up. 

  Rather than customising Plausible’s platform, for instance, you need to embed its dashboard into your own user interface. If you want to create your own custom dashboard, you’ll need to use an API. 

  Plausible offers a 30-day free trial.

  Leverage white label analytics today with Matomo

  Don’t put up with confusing unbranded clients a moment longer. White label your analytics platform so the next time you sit down to share insights with your clients, they’ll only see one brand : yours.

  Matomo makes it quick and easy to customise the look of your analytics platform and all of the reports you generate. If you already use Matomo, try the White Label plugin free for 30 days.

  If not, try Matomo with a free 21-day trial. No credit card required. 

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• 7 Mixpanel alternatives to consider for better web and product analytics

  1er août, par Joe

  Mixpanel is a web and mobile analytics platform that brings together product and marketing data so teams can see the impact of their actions and understand the customer journey. 

  It’s a well-rounded tool with features that help product teams understand how customers navigate their website or app. It’s also straightforward to set up, GDPR compliant, and easy for non-technical folks to use, thanks to an intuitive UI and drag-and-drop reports. 

  However, Mixpanel is just one of many product and web analytics platforms. Some are cheaper, others are more secure, and a few have more advanced or specialist features.

  This article will explore the leading Mixpanel alternatives for product teams and marketers. We’ll cover their key features, what users love about them, and why they may (or may not) be the right pick for you. 

  Mixpanel : an overview

  Let’s start by giving Mixpanel its dues. The platform does a great job of arming product teams with an arsenal of tools to track the impact of their updates, find ways to boost engagement and track which features users love. 

  Marketing teams use the platform to track customers through the sales funnel, attribute marketing campaigns and find ways to optimise spend. 

  There’s plenty to like about Mixpanel, including : 

  • Easy setup and maintenance : Mixpanel’s onboarding flow allows you to build a tracking plan and choose the specific events to measure. When Mixpanel collects data, you’ll see an introductory “starter board.” 
  • Generous free plan : Mixpanel doesn’t limit freemium users like some platforms. Collect data on 20 million monthly events, use pre-built templates and access its Slack community. There are also no limits on collaborators or integrations.
  • Extensive privacy configurations : Mixpanel provides strong consent management configurations. Clients can let their users opt out of tracking, disable geolocation and anonymise their data. It also automatically deletes user data after five years and offers an EU Data Residency Program that can help customers meet GDPR regulations. 
  • Comprehensive features : Mixpanel gives marketers and product teams the tools and features they need to understand the customer, improve the product and increase conversions. 
  • Easy-to-use UI : The platform prioritises self-service data, meaning users don’t need to be technically minded to use Mixpanel. Drag-and-drop dashboards democratise access to data and let anyone on your team find answers to their questions.

  You wouldn’t be reading this page if Mixpanel offered everything, though. No platform is perfect, and there are several reasons people may want to look for a Mixpanel alternative :
  

  • No self-hosted option : You’ll never have complete control over your data with Mixpanel due to the lack of a self-hosted option. Data will always live on Mixpanel’s servers, meaning compliance with data regulations like GDPR isn’t a given.
  • Lack of customisation : Mixpanel doesn’t offer much flexibility when it comes to visualising data. While the platform’s in-built reports are accessible to everyone, you’ll need a developer to build custom reports. 
  • Not open source : Mixpanel’s proprietary software doesn’t provide the transparency, security and community that comes with using open-source software like Matomo. Proprietary software isn’t inherently wrong, but it could mean your analytics solution isn’t future-proof. 
  • Steep learning curve : The learning curve can be steep unless you’re a developer. While setting up the software is straightforward, Mixpanel’s reliance on manual tracking means teams must spend a lot of time creating and structuring events to collect the data they need.

  If any of those struck a chord, see if one of the following seven Mixpanel alternatives might better fulfil your needs. 

  The top 7 Mixpanel alternatives

  Now, let’s look at the alternatives.

  We’ll explain exactly how each platform differs from Mixpanel, its standout features, strengths, common community critiques, and when it may be (or may not be) the right choice. 

  1. Matomo

  Matomo is a privacy-focused, open-source web and mobile analytics platform. As a proponent of an ethical web, Matomo prioritises data ownership and privacy protection. 

  It’s a great Mixpanel alternative for those who care about data privacy. You own 100% of your data and will always comply with data regulations like GDPR when using the platform. 

  

  Main dashboard with visits log, visits over time, visitor map, combined keywords, and traffic sources
  (Image Source)

  Matomo isn’t short on features, either. Product teams and marketers can evaluate the entire user journey, capture detailed visitor profiles, combine web, mobile and app reports, and use custom reporting to generate the specific insides they need.

  Key features :

  • Complete app and web analytics : Matomo tracks performance metrics and KPIs across web, app and mobile. Understand which pages users visit, how long they stay and how they move between devices.
  • Marketing attribution : Built-in marketing attribution capabilities make it easy for marketers to pinpoint their most profitable campaigns and channels. 
  • User behaviour tracking : Generate in-depth user behaviour data thanks to heatmaps, form analytics and session recordings.

  Strengths

  • On-premise and cloud versions : Use Matomo for free on your servers or subscribe to Matomo Cloud for hosting and additional support. Either way, you remain in control of your data.
  • Exceptional customer support : On-premise and Matomo Cloud users get free access to the forum. Cloud customers get dedicated support, which is available at an additional cost for on-premise customers. 
  • Consent-free tracking : Matomo doesn’t ruin the user’s experience with cookie banners. 
  • Open-source software : Matomo’s software is free to use, modify, and distribute. Users get a more secure, reliable and transparent solution thanks to the community of developers and contributors working on the project. Matomo will never become proprietary software, so there’s no risk of vendor lock-in. You will always have access to the source code, raw data and APIs. 

  Common community critiques :

  • On-premise setup : The on-premise version requires some technical knowledge and a server.
  • App tracking features : Some features, like heatmaps, available on web analytics aren’t available in-app analytics. Features may also differ between Android SDK and iOS SDK.

  Price : 

  Matomo has three plans :

  • Free : on-premise analytics is free to use
  • Cloud : Hosted business plans start at €22 per month
  • Enterprise : custom-priced, cloud-hosted enterprise plan tailored to meet a business’s specific requirements.

  There’s a free 21-day trial for Matomo Cloud and a 30-day plugin trial for Matomo On-Premise.

  2. Adobe Analytics

  Adobe Analytics is an enterprise analytics platform part of the Adobe Experience Cloud. This makes it a great Mixpanel alternative for those already using other Adobe products. But, getting the most from the platform is challenging without the rest of the Adobe ecosystem. 

  

  Adobe Analytics Analysis Workspace training tutorial
  (Image Source)

  Adobe Analytics offers many marketing tools, but product teams may find their offer lacking. Small or inexperienced teams may also need help using this feature-heavy platform. 

  Key features :

  • Detailed web and marketing analytics : Adobe lets marketers draw in data from almost any source to get a comprehensive view of the customer journey. 
  • Marketing attribution : There’s a great deal of flexibility when crediting conversions. There are unlimited attribution models, too, including both paid and organic media channels.
  • Live Stream : This feature lets brands access raw data in near real time (with a 30- to 90-second delay) to assess the impact of marketing campaigns as soon as they launch. 

  Strengths :

  • Enterprise focus : Adobe Analytics’s wide range of advanced features makes It attractive to large companies with one or more high-traffic websites or apps. 
  • Integrations : Adobe Analytics integrates neatly with other Adobe products like Campaign and Experience Cloud). Access marketing, analytics and content management tools in one place. 
  • Customisation : The platform makes it easy for users to tailor reports and dashboards to their specific needs.

  Common community critiques :

  • Few product analytics features : While marketers will likely love Adobe, product teams may find it lacking. For example, the heatmap tool isn’t well developed. You’ll need to use Adobe Target to run A/B tests.
  • Complexity : The sheer number of advanced features can make Adobe Analytics a confusing experience for inexperienced or non-technically minded users. While a wealth of support documentation is available, it will take longer to generate value. 
  • Price : Adobe Analytics costs several thousand dollars monthly, making it suitable only for enterprise clients.

  Price : 

  Adobe offers three tiers : Select, Prime and Ultimate. Pricing is only available on request.

  3. Amplitude

  Amplitude is a product analytics and event-tracking platform. It is arguably the most like-for-like platform on this list, and there is a lot of overlap between Amploitduce’s and Mixpanel’s capabilities. 

  

  The Ask Amplitude™ feature helps build and analyse conversion funnel charts.
  (Image Source)

  The platform is an excellent choice for marketers who want to create a unified view of the customer by tracking them across different devices. This is possible with several other analytics platforms on this list (Matomo included), but Mixpanel doesn’t centralise data from web and app users in a signal report. 

  Amplitude also has advanced features Mixpanel doesn’t have, like feature management and AI, as well as better customisation. 

  Key features :

  • Product analytics : Amplitude comes packed with features product teams will use regularly, including customer journey analysis, session replays and heatmaps. 
  • AI : Amplitude AI can clean up data, generate insights and detect anomalies.
  • Feature management : Amplitude provides near-real-time feedback on feature usage and adoption rates so that product teams can analyse the impact of their work. Developers can also use the platform to manage progressive rollouts. 

  Strengths :

  • Self-serve reporting : The platform’s self-serve nature means employees of all levels and abilities can get the insights they need. That includes data teams that want to run detailed and complex analyses. 
  • Integrated web experimentation. Product teams or marketers don’t need a third-party tool to run A/B tests because Amplitude has a comprehensive feature that lets users set up tests, collect data and create reports. 
  • Extensive customer support : Amplitude records webinars, holds out-of-office sessions and runs a Slack community to help customers extract as much value as possible.

  Common community critiques :

  • Off-site tracking : While Amplitude has many features for tracking customer interaction across your product, it lacks ways to track customers once they are off-site. This is not great for marketing attribution, for example, or growing search traffic. 
  • Too complex : The sheer number of things Amplitude tracks can overwhelm inexperienced users who must spend time learning how to use the platform. 
  • Few templates : Few stock templates make getting started with Amplitude even harder. Users have to create reports from scratch rather than customise a stock graph. 

  Price : 

  • Starter : Free to track up to 50,000 users per month. 
  • Plus : $49 per month to track up to 300,000 users.
  • Growth : Custom pricing for no tracking limits
  • Enterprise : Custom pricing for dedicated account managers and predictive analytics
    

  4. Google Analytics

  Google Analytics is the most popular web analytics platform. It’s completely free to use and easy to install. Although there’s no customer support, the thousands of online how-to videos and articles go some way to making up for it. 

  

  GA dashboard showing acquisition, conversion and behaviour data across all channels 
  (Image Source)

  Most people are familiar with Google’s web analytics data, which makes it a great Mixpanel alternative for marketers. However, product teams may struggle to get the qualitative data they need.

  Key features :

  • User and conversion tracking : People don’t just use Google Analytics because it’s free. The platform boasts a competitive user engagement and conversion tracking offering, which lets businesses of any size understand how consumers navigate their sites and make purchases. 
  • Audience segmentation : Segment audiences based on time and event parameters.
  • Google Ads integration : Track users from the moment they interact with one of your ads. 

  Strengths :

  • It’s free : Web and product analytics platforms can cost hundreds of dollars monthly and put a sizable dent in a small business marketing budget. Google provides the basic tools most marketers need for free.
  • Cross-platform tracking : GA4 lets teams track mobile and web analytics in one place, which wasn’t possible in Universal Analytics.
  • A wealth of third-party support : There’s no shortage of Google Analytics tutorials on YouTube to help you set up and use the platform. 

  Common community critiques :

  • Data privacy concerns : There are concerns about Google’s lack of compliance with regulations like GDPR. The workaround is asking people for permission to collect their data, but that requires a consent pop-up that can disrupt the user experience. 
  • No CRO features : Google Analytics lacks the conversion optimisation features of other tools in this list, including Matomo. It can’t record sessions, track user interactions via a heatmap or run A/B tests. 
  • AI data sampling : Google generates insights using AI-powered data sampling rather than analysing your actual data, which may make your data inaccurate. 

  Price : 

  Google Analytics is free to use. Google also offers a premium version, GA 360, which starts at $50,000 per year. 

  5. Heap

  Heap is a digital insights and product analytics platform. It gives product managers and marketers the quantitative and qualitative data they need to improve conversion rates, improve product features, and reduce churn. 

  

  Heap marketing KPI dashboard
  (Image Source)

  The platform offers everything you’d expect from a product analytics perspective, including session replays, heatmaps and user journey analysis. It even has an AI tool that can answer your questions. 

  Key features :

  • Auto-capture : Unlike other analytics tools (Mixpanel and Google Analytics, for instance), you don’t need to manually code events. Heap’s auto-capture feature automatically collects every user interaction, allowing for retroactive analysis. 
  • Segmentation : Create distinct customer cohorts based on behaviour. Integrate other platforms like Marketo to use that information to personalise marketing campaigns. 
  • AI CoPilot : Heap has a generative AI tool, CoPilot, that answers questions like “How many people visited the About page last week ?” It can also handle follow-up questions and suggest what to search next. 

  Strengths :

  • Integrations : Heap’s integrations allow teams to centralise data from dozens of third-party applications. Popular integrations include Shopify and Salesforce. Heap can also connect to your data warehouse. 
  • Near real-time tracking : Heap has a live data feed that lets teams track user behaviour in near real-time (there’s a 15-second delay).
  • Collaboration : Heap facilitates cross-department collaboration via shared spaces and shared reports. You can also share session replays across teams.

  Common community critiques :

  • Struggles at scale : Heap’s auto-capture functionality can be more of a pain than a perk when working at scale. Sites with a million or more weekly visitors may need to limit data capture.
  • Data overload : Heap tracks so much data it can be hard to find the specific events you want to measure.
  • Poor-quality graphics : Heap’s visualisations are basic and may not appeal to non-technically minded users.

  Price : 

  Heap offers four plans with pricing available on request.

  • Free
  • Growth
  • Pro
  • Premier
    

  6. Hotjar

  Hotjar is a product experience insight tool that analyses why users behave as they do. The platform collects behavioural data using heatmaps, surveys and session recordings. 

  It’s a suitable alternative for product teams and marketers who care about collecting qualitative rather than quantitative data. 

  

  New heatmap feature in hotjar
  (Image Source)

  It’s not your typical analytics platform, however. Hotjar doesn’t track site visits or conversions, so teams use it alongside a web analytics platform like Google Analytics or Matomo.

  Key features :

  • Surveys : Product teams can place surveys on specific pages to capture quantitative and qualitative data. 
  • Heatmaps : Hotjar provides several heatmaps — click, scroll and interaction — that show how users behave when browsing your site. 
  • Session recordings : Support quantitative analytics data with videos of genuine user behaviour. It’s like watching someone browsing your site over their shoulder. 

  Strengths :

  • User-friendly interface : The tool is easy to navigate and accessible to all employees. Anyone can start using it quickly. 
  • Funnel analysis : Use Hotjar’s range of tools to analyse your entire funnel, identifying friction points and opportunities to improve the customer experience. 
  • Cross-platform tracking : Hotjar compares user behaviour across desktop, mobile and app. 

  Common community critiques :

  • Limited web analytics : While Hotjar is great for understanding customer behaviour, it doesn’t collect standard web analytics data. 
  • Data retention : Hotjar only retains data for one month to a year on some plans.
  • Impacts page speed : The tool’s code impacts your site’s performance, leading to slower load times. 

  Price : 

  • Free : Up to five thousand monthly sessions, including screen recordings and heatmaps
  • Growth : $49 per month for 7,000 to 10,000 monthly sessions
  • Pro : Custom pricing for up to 500 million monthly sessions
  • Enterprise : Custom pricing for up to 6 billion monthly sessions. 
    

  7. Kissmetrics

  Kissmetrics is a web and mobile analytics platform that aims to help teams generate more revenue and acquire more users through product-led growth. 

  As such, the platform offers more to marketers than product teams — particularly online store owners and SaaS businesses. 

  

  Kissmetrics funnel report 
  (Image Source)

  Kissmetrics provides a suite of behavioural analytics tools that analyse how customers move through your funnel, where they drop off and why. That’s great for marketers, but product teams will struggle to understand how customers actually use their product once they’ve converted.

  Key features :

  • User journey mapping : Follow individual customer journeys to learn how each customer finds and engages with your brand. 
  • Funnel analysis : Funnel reports help marketers track cart abandonments and other drop-offs along the customer journey. 
  • A/B testing : Kissmetrics’s A/B testing tool measures how customers respond to different page layouts

  Strengths :

  • Detailed revenue metrics : Kissmetrics makes measuring customer lifetime value, churn rate, and other revenue-focused KPIs easy. 
  • Stellar onboarding experience : Kissmetrics gives new users a detailed walkthrough and tutorial, which helps non-technical users get up to speed. 
  • Integrations : Integrate data from dozens of platforms and tools, such as Facebook, Instagram, Shopify, and Woocommerce, so all your data is in one place. 

  Common community critiques :

  • Predominantly web-based : Kissmetrics focuses on web-based traffic over app- or cross-platform tracking. It may be fine for some teams, but product managers or marketers who track users across apps and smartphones may want to look elsewhere. 
  • Slow to load large data sources : The platform can be slow to load, react to, and analyse large volumes of data, which could be an issue for enterprise clients. 
  • Price : Kissmetrics is significantly more expensive than Mixpanel. There is no freemium tier, meaning you’ll need to pay at least $199 monthly. 

  Price : 

  • Silver : $199 per month for up to 2 million monthly events
  • Gold : $499 per month for up to five million monthly events
  • Platinum : Custom pricing

  Switch from Mixpanel to Matomo

  When it comes to extracting deep insights from user data while balancing compliance and privacy protection, Mixpanel delivers mixed results. If you want a more straightforward alternative, more websites chose Matomo over Mixpanel for their analytics because of its :

  • Accurate web analytics collected in an ethical, GDPR-compliant manner
  • Behavioural analytics (like heatmaps and session recordings) to understand how users engage with your site
  • Rolled-up cross-platform reporting for mobile and apps
  • Flexibility and customisation with 250+ settings, plentiful plugins and integrations, APIs, raw data access
  • Open-source code to create plugins to fit your specific business needs
  • 100% data ownership with Matomo On-Premise and Matomo Cloud

  Over one million websites in 190+ countries use Matomo’s powerful web analytics platform. Join them today by starting a free 21-day trial — no credit card required.