Changing analytics platforms is difficult. Even when organizations don’t feel like they are getting value from their current analytics, they tend to keep it because switching to a new one often includes the following:
- Reimplementation – implementing a new analytics tool typically requires retagging your website or mobile app.
- Retraining – switching to a new digital analytics platform forces you to retrain your team on a new user interface.
- Loss of historical data – in some cases, you may not be able to import historical data, which can make it impossible to see year-over-year trends.
Taking into consideration that Google is sunsetting Universal Analytics (UA) in July 2023 to replace it with Google Analytics 4, many professionals who have used UA are faced with a choice. They can either learn analytics based on a completely different tracking logic, or look for a new platform based on familiar patterns.
Moving to a new platform is much more than just implementation and it is vital to plan your migration properly. To help you, we have prepared the ultimate guide to switching web analytics vendors.
Many variables come into play when making the transition and are important to ensure that the new tool is fit for the organization. Here are just a few:
- The size of your company
- Your analytics budget
- Who owns the current analytics tool in your organization
- What teams need to be involved
After your organization has identified a need to switch and the analytics platform it will use, a lot of work then goes into carrying it out. We hope you find this guide valuable for those of you that decided to make the switch or might be going through this process.
Before you switch analytics tools, take the time to evaluate your entire stack, not just the tool you’re changing. Determine if your stack is up-to-date and aligned with your current business needs. Migrating to a new analytics vendor almost always requires more people and more time than originally estimated.
Start by looking at which tools aren’t playing nicely with one another. Your tools should integrate easily with one another, if not out of the box or via automation platforms like Zapier. This transition can also help you remove redundant tools from your stack, and it might also allow you to integrate with new tools that can help you run your analytics and collect data more comprehensively. We will write about integrations in more detail later.
- How data is being collected and with what tools – for example, with Google Tag Manager, etc.
- The flow of data: Website > Tag Manager > Analytics platform.
- What data you want to collect: Standard user behavior, along with data related to KPIs and other website objectives.
- Where the data will be available: Within the analytics platform interface or elsewhere like in Tableau or a company database.
Evaluation of resources is often overlooked when it comes to web analytics implementations. Generally, a successful analytics implementation involves:
- a project owner – usually the manager or director of the marketing/analytics department
- the development or IT team
- the end users – analysts, the marketing team, dev/IT
The list above is slightly oversimplified, and your list will ultimately depend on many factors within the organization. However, once you have identified the project team, you can begin work on your web analytics migration project. The next step is to clean up your data.
Over time, data collection may get messy, and you find yourself tracking data that isn’t relevant to your business. This can cause mistakes in data collection. A migration gives you a chance to clean up your data taxonomy.
- Are all events aligned with your KPIs?
- Are any collection of events or user properties duplicating (a common example is naming mistakes (e.g., collecting an “email” and “e-mail” event property)?
- Are there any missing critical events or properties?
Ensure that your new tool allows you to use the same categories of data as the previous one. Pay particular attention to any data that should be collected automatically, such as location data (country, region, city) and device information (device type, browser).
Last but not least, make sure that your new tool will support the SDKs that you need. This is crucial if you’re using newer coding platforms such as React Native or Node.js. The next step is the implementation of a new analytics platform.
Now it’s time to implement your new analytics platform. This step involves setting up the tracking code that collects data about visitors to your website or app.
You should also add any modifications necessary. Remember to set up tags to gather more detailed data through events or connect third-party tools.
You could choose from a variety of integrations to combine with your platform. For example, when you use Piwik PRO Analytics, you can integrate it with other modules and external tools such as:
- Tag manager, allowing you to create and publish tags
- Consent manager, helping you collect, store and manage users’ consents for different data processing purposes
- Google products, like Google Ads, Google Search Console and Google Sheets
Don’t forget to:
Once you’re done implementing your new platform, you should run it parallel to your existing tool for a few months before finalizing the migration.
During this time, you can audit your new data and correct any errors. This way, you won’t lose your historical data, and at the same time you will be able to build new segments of historical data with the new platform.
You might be interested in: Data Gathering Platforms: Pros and Cons of DMPs, CDPs, DWs & CRMs
Training is necessary for all end users so that they understand how the platform works, how to get the data they need and how to build reports. This is an often overlooked step because it comes after the project has been completed.
First, you should identify how many people are really consistently using the current digital analytics platform, so you should know who requires training. Then you should grant proper permissions to selected people in your organization.
You can schedule reports to be sent to any stakeholder without needing to log in to the analytics system.
Also, you need someone on your team that’s an expert with the tool (and preferably has experience with running trainings). They need to be able to train other employees and answer any questions that might come up.
Remember to assess the learning curve. If you choose an analytics platform that has the same data model, it will be easier for your internal users to learn it.
You can read more about this in our article discussing the two data models that current analytics platforms are built on: Event-based web analytics: everything you need to know
After this step, you should be ready to fully migrate to your new platform. If you’re struggling through any of these steps, you should think about bringing in outside help. Keep in mind that some analytics vendors give you hands-on onboarding and user training, which speeds up product adoption.
Check out our analytics platforms comparisons, which present the essential features of all products. See how they differ in terms of data collection flexibility, reporting features, customer support, and more:
Changing your analytics vendor is a challenge. Hopefully, the tips we’ve provided will make it easier for you to switch to a new analytics platform.
Remember to download our tracking plan to keep data on your events, goals, and funnels organized and easy to follow!
We can also recommend further reading to expand your analytics skills:
- Analytics implementation: A 12-step guide
- Mobile analytics: A complete guide to optimizing the user journey inside your app
- What is customer journey analytics and why it’s important for your business
Even with all the tips and tricks presented above, you might still have some unanswered questions. Our team will be happy to resolve any of your doubts: