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Six Best Amplitude Alternatives
10 décembre 2024, par Daniel CroughProduct analytics is big business. Gone are the days when we could only guess what customers were doing with our products or services. Now, we can track, visualise, and analyse how they interact with them and, with that, constantly improve and optimise.
The problem is that many product analytics tools are expensive and complicated — especially for smaller businesses. They’re also packed with functionality more attuned to the needs of massive companies.
Amplitude is such a tool. It’s brilliant and it has all the bells and whistles that you’ll probably never need. Fortunately, there are alternatives. In this guide, we’ll explore the best of those alternatives and, along the way, provide the insight you’ll need to select the best analytics tool for your organisation.
Amplitude : a brief overview
To set the stage, it makes sense to understand exactly what Amplitude offers. It’s a real-time data analytics tool for tracking user actions and gaining insight into engagement, retention, and revenue drivers. It helps you analyse that data and find answers to questions about what happened, why it happened, and what to do next.
However, as good as Amplitude is, it has some significant disadvantages. While it does offer data export functionality, that seems deliberately restricted. It allows data exports for specific events, but it’s not possible to export complete data sets to manipulate or format in another tool. Even pulling it into a CSV file has a 10,000-row limit. There is an API, but not many third-party integration options.
Getting data in can also be a problem. Amplitude requires manual tags on events that must be tracked for analysis, which can leave holes in the data if every possible subsequent action isn’t tagged. That’s a time-consuming exercise, and it’s made worse because those tags will have to be updated every time the website or app is updated.
As good as it is, it can also be overwhelming because it’s stacked with features that can create confusion for novice or inexperienced analysts. It’s also expensive. There is a freemium plan that limits functionality and events. Still, when an organisation wants to upgrade for additional functionality or to analyse more events, the step up to the paid plan is massive.
Lastly, Amplitude has made some strides towards being a web analytics option, but it lacks some basic functionality that may frustrate people who are trying to see the full picture from web to app.
Snapshot of Amplitude alternatives
So, in place of Amplitude, what product analytics tools are available that won’t break the bank and still provide the functionality needed to improve your product ? The good news is that there are literally hundreds of alternatives, and we’ve picked out six of the best.
- Matomo – Best privacy-focused web and mobile analytics
- Mixpanel – Best for product analytics
- Google Analytics – Best free option
- Adobe Analytics – Best for predictive analytics
- Umami – Best lightweight tool for product analytics
- Heap – Best for automatic user data capture
A more detailed analysis of the Amplitude alternatives
Now, let’s dive deeper into each of the six Amplitude alternatives. We’ll cover standout features, integrations, pricing, use cases and community critiques. By the end, you’ll know which analytics tool can help optimise website and app performance to grow your business.
1. Matomo – Best privacy-friendly web and app analytics
Privacy is a big concern these days, especially for organisations with a presence in the European Union (EU). Unlike other analytics tools, Matomo ensures you comply with privacy laws and regulations, like the General Data Protection Regulation (GDPR) and California’s Consumer Privacy Act (CCPA).
Matomo helps businesses get the insights they need without compromising user privacy. It’s also one of the few self-hosted tools, ensuring data never has to leave your site.
Matomo is open-source, which is also rare in this class of tools. That means it’s available for anyone to adapt and customise as they wish. Everything you need to build custom APIs is there.
The Locations page in Matomo shows the countries, continents, regions, and cities where website traffic originates. Its most useful capabilities include visitor logs and session recordings to trace the entire customer journey, spot drop-off points, and fine-tune sales funnels. The platform also comes with heatmaps and A/B testing tools. Heatmaps provide a useful visual representation of your data, while A/B testing allows for more informed, data-driven decisions.
Despite its range of features, many reviewers laud Matomo’s user interface for its simplicity and user-friendliness.
Why Matomo : Matomo is an excellent alternative because it fills in the gaps where Amplitude comes up short, like with cookieless tracking. Also, while Amplitude focuses mainly on behavioural analytics, Matomo offers both behavioural and traditional analytics, which allows more profound insight into your data. Furthermore, Matomo fully complies with the strictest privacy regulations worldwide, including GDPR, LGPD, and HIPAA.
Standout features include multi-touch attribution, visits log, content engagement, ecommerce, customer segments, event tracking, goal tracking, custom dimensions, custom reports, automated email reports, tag manager, sessions recordings, roll-up reporting that can pull data from multiple websites or mobile apps, Google Analytics importer, Matomo tag manager, comprehensive visitor tracking, heatmaps, and more.
Integrations with 100+ technologies, including Cloudflare, WordPress, Magento, Google Ads, Drupal, WooCommerce, Vue, SharePoint and Wix.
Pricing is free for Matomo On-Premise and $23 per month for Matomo Cloud, which comes with a 21-day free trial (no credit card required).
Strengths
- Privacy focused
- Cookieless consent banners
- 100% accurate, unsampled data
- Open-source code
- Complete data ownership (no sharing with third parties)
- Self-hosting and cloud-based options
- Built-in GDPR Manager
- Custom alerts, white labelling, dashboards and reports
Community critiques
- Premium features are expensive and proprietary
- Learning curve for non-technical users
2. Mixpanel – Best for product analytics
Mixpanel is a dedicated product analytics tool. It tracks and analyses customer interactions with a product across different platforms and helps optimise digital products to improve the user experience. It works with real-time data and can provide answers from customer and revenue data in seconds.
It also presents data visualisations to show how customers interact with products.
Mixpanel allows you to play around filters and views to reveal and chart some useful customer trends. (Image source)
Why Mixpanel : One of the strengths of this platform is the ability to test hypotheses. Need to test an ambitious idea ? Mixpanel data can do it with real user analytics. That allows you to make data-driven decisions to find the best path forward.
Standout features include automatic funnel segment analysis, behavioural segmentation, cohort segmentation, collaboration support, customisable dashboards, data pipelines, filtered data views, SQL queries, warehouse connectors and a wide range of pre-built integrations.
Integrations available include Appcues, AppsFlyer, AWS, Databox, Figma, Google Cloud, Hotjar, HubSpot, Intercom, Integromat, MailChimp, Microsoft Azure, Segment, Slack, Statsig, VWO, Userpilot, WebEngage, Zapier, ZOH) and dozens of others.
Pricing starts with a freemium plan valid for up to 20 million events per month. The growth plan is affordable at $25 per month and adds features like no-code data transformations and data pipeline add-ons. The enterprise version runs at a monthly cost of $833 and provides the full suite of features and services and premium support.
There’s a caveat. Those prices only allow up to 1,000 Monthly Tracked Users (MTUs), calculated based on the number of visitors that perform a qualifying event each month. Beyond that, MTU plans start at $20,000 per year.
Strengths
- User behaviour and interaction tracking
- Unlimited cohort segmentation capabilities
- Drop-off analysis showing where users get stuck
- A/B testing capabilities
Community critiques
- Expensive enterprise features
- Extensive setup and configuration requirements
3. Google Analytics 4 – Best free web analytics tool
The first thing to know about Google Analytics 4 is that it’s a web analytics tool. In other words, it tracks sessions, not user behaviours in app environments. It can provide details on how people found your website and how they go there, but it doesn’t offer much detail on how people use your product.
There is also an enterprise version, Google Analytics 360, which is not free. We’ve broken down the differences between the two versions elsewhere.
GA4’s audience overview shows visitors, sessions, session lengths, bounce rates, and user engagement data. (Image source)
Why Google Analytics : It’s great for gauging the effectiveness of marketing campaigns, tracking goal completions (purchases, cart additions, etc.) and spotting trends and patterns in user engagement.
Standout features include built-in automation, customisable conversion goals, data drill-down functionality, detailed web acquisition metrics, media spend ROI calculations and out-of-the-box web analytics reporting.
Integrations include all major CRM platforms, CallRail, DoubleClick DCM, Facebook, Hootsuite, Marketo, Shopify, VWO, WordPress, Zapier and Zendesk, among many others.
Pricing is free for the basic version (Google Analytics 4) and scales based on features and data volume. The advanced features (in Google Analytics 360) are pitched at enterprises, and pricing is custom.
Strengths
- Free to start
- Multiple website management
- Traffic source details
- Up-to-date traffic data
Community critiques
- Steep learning curve
- Data sampling
4. Adobe Analytics – Best for predictive analytics
A fully configured Adobe Analytics implementation is the Swiss army knife of analytics tools. It begins with web analytics, adds product analytics, and then wraps it up nicely with predictive analytics.
Unlike all the Amplitude alternatives here, there’s no free version. Adobe Analytics has a complicated pricing matrix with options like website analytics, marketing analytics, attribution, and predictive analytics. It also has a wide range of customisation options that will appeal to large businesses. But for smaller organisations, it may all be a bit too much.
Mixpanel allows you to play around filters and views to reveal and chart some useful customer trends. (Image source)
Adobe Analytics’ cross-channel attribution ties actions from different channels into a single customer journey. (Image source)
Why Adobe Analytics : For current Adobe customers, this is a logical next step. Either way, Adobe Analytics can combine, evaluate, and analyse data from any part of the customer journey. It analyses that data with predictive intelligence to provide insights to enhance customer experiences.
Standout features include AI-powered prediction analysis, attribution analysis, multi-channel data collection, segmentation and detailed customer journey analytics, product analytics and web analytics.
Integrations are available through the Adobe Experience Cloud Exchange. Adobe Analytics also supports data exchange with brands such as BrightEdge, Branch.io, Google Ads, Hootsuite, Invoca, Salesforce and over 200 other integrations.
Pricing starts at $500 monthly, but prospective customers are encouraged to contact the company for a needs-based quotation.
Strengths
- Drag-and-drop interface
- Flexible segmentation
- Easy-to-create conversion funnels
- Threshold-based alerts and notifications
Community critiques
- No free version
- Lack of technical support
- Steep learning curve
5. Umami – Best lightweight tool for web analytics
The second of our open-source analytics solutions is Umami, a favourite in the software development community. Like Matomo, it’s a powerful and privacy-focused alternative that offers complete data control and respects user privacy. It’s also available as a cloud-based freemium plan or as a self-hosted solution.
Umami’s dashboard reveals the busiest times of day and which pages are visited when.(Image source)
Why Umami : Unami has a clear and simple user interface (UI) that lets you measure important metrics such as page visits, referrers, and user agents. It also features event tracking, although some reviewers complain that it’s quite limited.
Standout features can be summed up in five words : privacy, simplicity, lightweight, real-time, and open-source. Unami’s UI is clean, intuitive and modern, and it doesn’t slow down your website.
Integrations include plugins for VuePress, Gatsby, Craft CMS, Docusaurus, WordPress and Publii, and a module for Nuxt. Unami’s API communicates with Javascript, PHP Laravel and Python.
Pricing is free for up to 100k monthly events and three websites, but with limited support and data retention restrictions. The Pro plan costs $20 a month and gives you unlimited websites and team members, a million events (plus $0.00002 for each event over that), five years of data and email support. Their Enterprise plan is priced custom.
Strengths
- Freemium plan
- Open-source
- Lightweight
Community critiques
- Limited support options
- Data retention restrictions
- No funnel functionality
6. Heap – Best for automatic data capture
Product analytics with a twist is a good description of Heap. It features event auto-capture to track user interactions across all touchpoints in the user journey. This lets you fully understand how and why customers engage with your product and website.
Using a single Javascript snippet, Heap automatically collects data on everything users do, including how they got to your website. It also helps identify how different cohorts engage with your product, providing the critical insights teams need to boost conversion rates.
Heap’s journeys feature combines funnel and path analysis. (Image source)
Why Heap : The auto-capture functionality solves a major shortcoming of many product analytics tools — manual tracking. Instead of having to set up manual tags on events, Heap automatically captures all data on user activity from the start.
Standout features include event auto-capture, session replay, heatmaps, segments (or cohorts) and journeys, the last of which combines the functions of funnel and path analysis tools into a single feature.
Integrations include AWS, Google, Microsoft Azure, major CRM platforms, Snowflake and many other data manipulation platforms.
Pricing is quote-based across all payment tiers. There is also a free plan and a 14-day free trial.
Strengths
- Session replay
- Heatmaps
- User segmentation
- Simple setup
- Event auto-capture
Community critiques
- No A/B testing functionality
- No GDPR compliance support
Choosing the best solution for your team
When selecting a tool, it’s crucial to understand how product analytics and web analytics solutions differ.
Product analytics tools track users or accounts and record the features they use, the funnels they move through, and the cohorts they’re part of. Web analytics tools focus more on sessions than users because they’re interested in data that can help improve website usage.
Some tools combine product and web analytics to do both of these jobs.
Area of focus
Product analytics tools track user behaviour within SaaS- or app-based products. They’re helpful for analysing features, user journeys, engagement metrics, product development and iteration.
Web analytics tools analyse web traffic, user demographics, and traffic sources. They’re most often used for marketing and SEO insights.
Level of detail
Product analytics tools provide in-depth tracking and analysis of user interactions, feature usage, and cohort analysis.
Web analytics tools provide broader data on page views, bounce rates, and conversion tracking to analyse overall site performance.
Whatever tools you try, your first step should be to search for reviews online to see what people who’ve used them think about them. There are some great review sites you can try. See what people are saying on Capterra, G2, Gartner Peer Insights, or TrustRadius.
Use Matomo to power your web and app analytics
Web and product analytics is a competitive field, and there are many other tools worth considering. This list is a small cross-section of what’s available.
That said, if you have concerns about privacy and costs, consider choosing Matomo. Start your 21-day free trial today.
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A Beginner’s Guide to Omnichannel Analytics
14 avril 2024, par ErinLinear customer journeys are as obsolete as dial-up internet and floppy disks. As a marketing manager, you know better than anyone that customers interact with your brand hundreds of times across dozens of channels before purchasing. That can make tracking them a nightmare unless you build an omnichannel analytics solution.
Alas, if only it were that simple.
Unfortunately, it’s not enough to collect data on your customers’ complex journeys just by buying an omnichannel platform. You need to generate actionable insights by using marketing attribution to tie channels to conversions.
This article will explain how to build a useful omnichannel analytics solution that lets you understand and improve the customer journey.
What is omnichannel analytics ?
Omnichannel analytics collects and analyses customer data from every touchpoint and device. The goal is to collect all this omnichannel data in one place, creating a single, real-time, unified view of your customer’s journey.
Unfortunately, most businesses haven’t achieved this yet. As Karen Lellouche Tordjman and Marco Bertini say :
“Despite all the buzz around the concept of omnichannel, most companies still view customer journeys as a linear sequence of standardised touchpoints within a given channel. But the future of customer engagement transforms touchpoints from nodes along a predefined distribution path to full-blown portals that can serve as points of sale or pathways to many other digital and virtual interactions. They link to chatbots, kiosks, robo-advisors, and other tools that customers — especially younger ones — want to engage with.”
However, doing so is more important than ever — especially when consumers have over 300 digital touchpoints, and the average number of touchpoints in the B2B buyer journey is 27.
Not only that, but customers expect personalised experiences across every platform — that’s the kind you can only create when you have access to omnichannel data.
What might omnichannel analytics look like in practice for an e-commerce store ?
An online store would integrate data from channels like its website, mobile app, social media accounts, Google Ads and customer service records. This would show how customers find its brand, how they use each channel to interact with it and which channels convert the most customers.
This would allow the e-commerce store to tailor marketing channels to customers’ needs. For instance, they could focus social media use on product discovery and customer support. Google Ads campaigns could target the best-converting products. While all this is happening, the store could also ensure every channel looks the same and delivers the same experience.
What are the benefits of omnichannel analytics ?
Why go to all the trouble of creating a comprehensive view of the customer’s experience ? Because you stand to gain some pretty significant benefits when implementing omnichannel analytics.
Understand the customer journey
You want to understand how your customers behave, right ? No other method will allow you to fully understand your customer journey the way omnichannel analytics does.
It doesn’t matter how customers engage with your brand — whether that’s your website, app, social media profiles or physical stores — omnichannel analytics capture every interaction.
With this 360-degree view of your customers, it’s easy to understand how they move between channels, where they encounter issues and what bottlenecks prevent them from converting.
Deliver better personalisation
We don’t have to tell you that personalisation matters. But do you know just how important it is ? Since 56% of customers will become repeat buyers after a personalised experience, delivering them as often as possible is critical.
Omnichannel analytics helps in your quest for personalisation by highlighting the individual preferences of customer segments. For example, e-commerce stores can use omnichannel analytics to understand how shoppers behave across different devices and tailor their offers accordingly.
Upgrade the customer experience
Omnichannel analytics gives you the insights to improve every aspect of the customer experience.
For starters, you can ensure a consistent brand experience across all your top channels by making sure they look and behave the same.
Then, you can use omnichannel insights to tailor each channel to your customers’ requirements. For example, most people interacting with your brand on social media may seek support. Knowing that you can create dedicated support accounts to assist users.
Improve marketing campaigns
Which marketing campaigns or traffic sources convert the most customers ? How can you improve these campaigns ? Omnichannel analytics has the answers.
When you implement omnichannel analytics you automatically track the performance of every marketing channel by attributing each conversion to one or more traffic sources. This lets you see whether Google Ads bring in more customers than your SEO efforts. Or whether social media ads are the most profitable acquisition channel.
Armed with this information, you can improve your marketing efforts — either by focusing on your profitable channels or rectifying problems that stop less profitable channels from converting.
What are the challenges of omnichannel analytics ?
There are three challenges when implementing an omnichannel analytics solution :
- Complex customer journeys : Customer journeys aren’t linear and can be incredibly difficult to track.
- Regulatory and privacy issues : When you start gathering customer data, you quickly come up against consumer privacy laws.
- No underlying goal : There has to be a reason to go to all this effort, but brands don’t always have goals in mind before they start.
You can’t do anything about the first challenge.
After all, your customer journey will almost never be linear. And isn’t the point of implementing an omnichannel solution to understand these complex journeys in the first place ? Once you set up omnichannel analytics, these journeys will be much easier to decipher.
As for the other two :
Using the right software that respects user privacy and complies with all major privacy laws will avoid regulatory issues. Take Matomo, for instance. Our software was designed with privacy in mind and is configured to follow the strictest privacy laws, such as GDPR.
Tying omnichannel analytics to marketing attribution will solve the final challenge by giving your omnichannel efforts a goal. When you tie omnichannel analytics to your marketing efforts, you aren’t just getting a 360-degree view of your customer journey for the sake of it. You are getting that view to improve your marketing efforts and increase sales.
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How to set up an omnichannel analytics solution
Want to set up a seamless analytical environment that incorporates data from every possible source ? Follow these five steps :
Choose one or more analytics providers
You can use several tools to build an omnichannel analytics solution. These include web and app analytics tools, customer data platforms that centralise first-party data and business intelligence tools (typically used for visualisation).
Which tools you use will depend on your goals and your budget — the loftier your ambitions and the higher your budget, the more tools you can use.
Ideally, you should use as few tools as possible to capture your data. Most teams won’t need business intelligence platforms, for example. However, you may or may not need both an analytics platform and a customer data platform. Your decision will depend on how many channels your customers use and how well your analytics tool tracks everything.
If it can capture web and app usage while integrating with third-party platforms like your back-end e-commerce platform, then it’s probably enough.
Collect accurate data at every touchpoint
Your omnichannel analytics efforts hinge on the quantity and quality of data you can collect. You want to gather data from every touchpoint possible and store that data in as few places as possible. That’s why choosing as few tools as possible in the step above is so important.
So, where should you start ? Common data sources include :
- Your website
- Apps (iOS and Android)
- Social media profiles
- ERPs
- PoS systems
At the same time, make sure you’re tracking all relevant metrics. Revenue, customer engagement and conversion-focused metrics like conversion rate, dwell time, cart abandonment rate and churn rate are particularly important.
Set up marketing attribution
Setting up marketing attribution (also known as multi-touch attribution) is essential to tie omnichannel data to business goals. It’s the only way to know exactly how valuable each marketing channel is and where each customer comes from.
You’ll want to use multi-touch attribution, given you have data from across the customer journey.
Multi-touch attribution models can include (but are not limited to) :
- Linear : where each touchpoint is given equal weighting
- Time decay : where touchpoints are more valuable the nearer they are to conversion
- Position-based : where the first and last touch points are more valuable than all the others.
You don’t have to use just one of the models above, however. One of the benefits of using a web analytics tool like Matomo is that you can choose between different attribution models and compare them.
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Create reports that help you visualise data
Dashboards are your friend here. They’ll let you see KPIs at a glance, allowing you to keep track of day-to-day changes in your customer journey. Ideally, you’ll want a platform that lets you customise dashboard widgets so only relevant KPIs are shown.
Setting up standard and custom reports is also important. Custom reports allow you to choose metrics and dimensions that align with your goals. They will also allow you to present your data most meaningfully to your team, increasing the likelihood they act upon insights.
Analyse data and take action
Now that you have customer journey data at your fingertips, it’s time to analyse it. After all, there’s no point in implementing an omnichannel analytics solution if you aren’t going to take action.
If you’re unsure where to start, re-read the benefits we listed at the start of this article. You could use your omnichannel insights to improve your marketing campaigns by doubling down on the channels that bring in the best customers.
Or you could identify (and fix) bottlenecks in the customer journey so customers are less likely to fall out of your funnel between certain channels.
Just make sure you take action based on your data alone.
Make the most of omnichannel analytics with Matomo
A comprehensive web and app analytics platform is vital to any omnichannel analytics strategy.
But not just any solution will do. When privacy regulations impede an omnichannel analytics solution, you need a platform to capture accurate data without breaking privacy laws or your users’ trust.
That’s where Matomo comes in. Our privacy-friendly web analytics platform ensures accurate tracking of web traffic while keeping you compliant with even the strictest regulations. Moreover, our range of APIs and SDKs makes it easy to track interactions from all your digital products (website, apps, e-commerce back-ends, etc.) in one place.
Try Matomo for free for 21 days. No credit card required.
Try Matomo for Free
21 day free trial. No credit card required.
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What Is Incrementality & Why Is It Important in Marketing ?
26 mars 2024, par ErinImagine this : you just launched your latest campaign and it was a major success.
You blew last month’s results out of the water.
You combined a variety of tactics, channels and ad creatives to make it work.
Now, it’s time to build the next campaign.
The only issue ?
You don’t know what made it successful or how much your recent efforts impacted the results.
You’ve been building your brand for years. You’ve built up a variety of marketing pillars that are working for you. So, how do you know how much of your campaign is from years of effort or a new tactic you just implemented ?
The key is incrementality.
This is a way to properly attribute the right weight to your marketing tactics.
In this article, we break down what incrementality is in marketing, how it differs from traditional attribution and how you can calculate and track it to grow your business.
What is incrementality in marketing ?
Incrementality in marketing is growth that can be directly credited to a marketing effort above and beyond the success of the branding.
It looks at how much a specific tactic positively impacted a campaign on top of overall branding and marketing strategies.
For example, this could be how much a specific tactic, campaign or channel helped increase conversions, email sign-ups or organic traffic.
The primary purpose of incrementally in marketing is to more accurately determine the impact a single marketing variable had on the success of a project.
It removes every other factor and isolates the specific method to help marketers double down on that strategy or move on to new tactics.
With Matomo, you can track conversions simply. With our last non-direct channel attribution system, you’ll be able to quickly see what channels are converting (and which aren’t) so you can gain insights into incrementality.
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How incrementality differs from attribution
In marketing and advertising, it’s crucial to understand what tactics and activities drive growth.
Incrementality and attribution help marketers and business owners understand what efforts impact their results.
But they’re not the same.
Here’s how they differ :
Incrementality explained
Incrementality measures how much a specific marketing campaign or activity drives additional sales or growth.
Simply put, it’s analysing the difference between having never implemented the campaign (or tactic or channel) in the first place versus the impact of the activity.
In other words, how much revenue would you have generated this month without campaign A ?
And how much additional revenue did you generate directly due to campaign A ?
The reality is that dozens of factors impact revenue and growth.
You aren’t just pouring your marketing into one specific channel or campaign at a time.
Chances are, you’ve got your hands on several marketing initiatives like SEO, PPC, organic social media, paid search, email marketing and more.
Beyond that, you’ve built a brand with a not-so-tangible impact on your recurring revenue.
So, the question is, if you took away your new campaign, would you still be generating the same amount of revenue ?
And, if you add in that campaign, how much additional revenue and growth did it directly create ?
That is incrementality. It’s how much a campaign went above and beyond to add new revenue that wouldn’t have been there otherwise.
So, how does attribution play into all of this ?
Attribution explained
Attribution is simply the process of assigning credit for a conversion to a particular marketing touchpoint.
While incrementality is about narrowing down the overall revenue impact from a particular campaign, attribution seeks to point to a specific channel to attribute a sale.
For example, in any given marketing campaign, you have a few marketing tactics.
Let’s say you’re launching a limited-time product.
You might have :
- Paid ads via Facebook and Instagram
- A blog post sharing how the product works
- Organic social media posts on Instagram and TikTok
- Email waitlist campaign building excitement around the upcoming product
- SMS campaigns to share a limited-time discount
So, when the time comes for the sale launch, and you generate $30,000 in revenue, what channel gets the credit ?
Do you give credit to the paid ads on Facebook ? What about Instagram ? They got people to follow you and got them on the email waitlist.
Do you give credit to email for reminding people of the upcoming sale ? What about your social media posts that reminded people there ?
Or do you credit your SMS campaign that shared a limited-time discount ?
Which channel is responsible for the sale ?
This is what attribution is all about.
It’s about giving credit where credit is due.
The reason you want to attribute credit ? So you know what’s working and can double down your efforts on the high-impact marketing activities and channels.
Leveraging incrementality and attribution together
Incrementality and attribution aren’t competing methods of analysing what’s working.
They’re complementary to one another and go hand in hand.
You can (and should) use attribution and incrementality in your marketing to help understand what activities, campaigns and channels are making the biggest incremental impact on your business growth.
Why it’s important to measure incrementality
Incrementality is crucial to measure if you want to pour your time, money and effort into the right marketing channels and tactics.
Here are a few reasons why you need to measure incrementality if you want to be successful with your marketing and grow your business :
1. Accurate data
If you want to be an effective marketer, you need to be accurate.
You can’t blindly start marketing campaigns in hopes that you will sell many products or services.
That’s not how it works.
Sure, you’ll probably make some sales here and there. But to truly be effective with your work, you must measure your activities and channels correctly.
Incrementality helps you see how each channel, tactic or campaign made a difference in your marketing.
Matomo gives you 100% accurate data on your website activities. Unlike Google Analytics, we don’t use data sampling which limits how much data is analysed.
2. Helps you to best determine the right tactics for success
How can you plan your marketing strategy if you don’t know what’s working ?
Think about it.
You’ll be blindly sailing the seas without a compass telling you where to go.
Measuring incrementality in your marketing tactics and channels helps you understand the best tactics.
It shows you what’s moving the needle (and what’s not).
Once you can see the most impactful tactics and channels, you can forge future campaigns that you know will work.
3. Allows you to get the most out of your marketing budget
Since incrementality sheds light on what’s moving your business forward, you can confidently implement your efforts on the right tactics and channels.
Guess what happens when you start doubling down on the most impactful activities ?
You start increasing revenue, decreasing ad spend and getting a higher return on investment.
The result is that you will get more out of your marketing budget.
Not only will you boost revenue, but you’ll also be able to boost profit margins since you’re not wasting money on ineffective tactics.
4. Increase traffic
When you see what’s truly working in your business, you can figure out what channels and tactics you should be working.
Incrementality helps you understand not only what your best revenue tactics are but also what channels and campaigns are bringing in the most traffic.
When you can increase traffic, you can increase your overall marketing impact.
5. Increase revenue
Finally, with increased traffic, the inevitable result is more conversions.
More conversions mean more revenue.
Incrementality gives you a vision of the tactics and channels that are converting the best.
If you can see that your SMS campaigns are driving the best ROI, then you know that you’ll grow your revenue by pouring more into acquiring SMS leads.
By calculating incrementality regularly, you can rest assured that you’re only investing time and money into the most impactful activities in terms of revenue generation.
How to calculate and test incrementality in marketing
Now that you understand how incrementality works and why it’s important to calculate, the question is :
How do you calculate and conduct incrementality tests ?
Given the ever-changing marketing landscape, it’s crucial to understand how to calculate and test incrementally in your business.
If you’re not sure how incrementality testing works, then follow these simple steps :
Your first step to get an incrementality measurement is to conduct what’s referred to as a “holdout test.”
It’s not a robust test, but it’s an easy way to get the ball rolling with incrementality.
Here’s how it works :
- Choose your target audience.
With Matomo’s segmentation feature, you can get pretty specific with your target audience, such as :
- Visitors from the UK
- Returning visitors
- Mobile users
- Visitors who clicked on a specific ad
- Split your audience into two groups :
- Control group (60% of the segment)
- Test group (40% of the segment)
- Target the control group with your marketing tactic (the simpler the tactic, the better).
- Target the test group with a different marketing tactic.
- Analyse the results. The difference between the control and test groups is the incremental lift in results. The new marketing tactic is either more effective or not.
- Repeat the test with a new control group (with an updated tactic) and a new test group (with a new tactic).
Matomo can help you analyse the results of your campaigns in our Goals feature. Set up business objectives so you can easily track different goals like conversions.
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Here’s an example of how this incrementality testing could look in real life.
Imagine a fitness retailer wants to start showing Facebook ads in their marketing mix.
The marketing manager decided to conduct a holdout test. If we match our example below with the steps above, this is how the holdout test might look.
- They choose people who’ve purchased free weights in the past as their target audience (see how that segmentation works ?).
- They split this segment into a control group and a test group.
- For this test, they direct their regular marketing campaign to the control group (60% of the segment). The campaign includes promoting a 20% off sale on organic social media posts, email marketing, and SMS.
- They direct their regular marketing campaign plus Facebook ads to the test group (40% of the segment).
- They ran the campaign for three weeks with the goal for sale conversions and noticed :
- The control group had a 1.5% conversion rate.
- The test group (with Facebook ads) had a 2.1% conversion rate.
- In this scenario, they could see the group who saw the Facebook ads convert better.
- They created the following formula to measure the incremental lift of the Facebook ads :
- Here’s how the calculation works out : (2.1% – 1.5%) / 1.5% = 40%
The Facebook ads had a positive 40% incremental lift in conversions during the sale.
Incrementality testing isn’t a one-and-done process, though.
While this first test is a great sign for the marketing manager, it doesn’t mean they should immediately throw all their money into Facebook ads.
They should continue conducting tests to verify the initial test.
Use Matomo to track incrementality today
Incrementality can give you insights into exactly what’s working in your marketing (and what’s not) so you can design proven strategies to grow your business.
If you want more help tracking your marketing efforts, try Matomo today.
Our web analytics and behaviour analytics platform gives you firsthand data on your website visitors you can use to craft effective marketing strategies.
Matomo provides 100% accurate data. Unlike other major web analytics platforms, we don’t do data sampling. What you see is what’s really going on in your website. That way, you can make more informed decisions for better results.
At Matomo, we take privacy very seriously and include several advanced privacy protections to ensure you are in full control.
As a fully compliant web analytics solution, we’re fully compliant with some of the world’s strictest privacy regulations like GDPR. With Matomo, you get peace of mind knowing you can make data-driven decisions while also being compliant.
If you’re ready to launch a data-driven marketing strategy today and grow your business, get started with our 21-day free trial now. No credit card required.
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21 day free trial. No credit card required.
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