Five Steps to Take Before Kicking Off A Clickstream Data Initiative
With the ability to track every step of a user’s journey across a website or app, we can truly get a 360° view of a customer. Often, organizations gather this information via multiple analytics tools, each representing a different aspect of user behavior. Many of these rely on data generated from when a user does (or doesn’t) “click.” We call that clickstream data.
Clickstream is the tracking of all the events you want, which can then be broadcast to your data warehouse, CRM, marketing/sales analytics tool or any other destination in real-time. But if you’re interested in tracking new events (ie. beginning a clickstream initiative), here are the top 5 things to keep in mind before kicking it off:
Image from laboratory-manager.advanceweb.com
1. Ask the questions that are important to you.
Steven Covey said it best, “Begin with the end in mind.” In that same vein, start your data initiative with a set of unanswered questions to guide your efforts.
There are many great tools (e.g. Mixpanel and Amplitude) that answer a generic yet important set of questions like, “How can I get more subscribers?” or “How can I retain my users?” or “How can I get more shares?” These are key questions to leverage first and can be done by measuring page views, session length, sources of traffic and more.
But let’s say you have a few key customers you want to replicate. Or you just invested a significant amount of time and money to redesign your website and can’t figure out why your sales have decreased. To find answers to more sophisticated business questions, it’s important to dig deeper. When digging, though, keep in mind #2…
Image from newsreplica.com
2. Use data processing to make the data more understandable.
Raw data is like crude oil; it requires refining before it becomes truly useful.
What does “refining” look like in the data world? It’s data processing, and includes filtering, cleaning, enrichment and aggregation. In the clickstream space, one example is cohort analysis. Say you’ve got 100 active users. By grouping users by the day, week or month they signed up, you can discover whether 90 of those users remained active in a subsequent month … or only 10. Suddenly, you have a much clearer picture of those 100 active users. Especially when aggregated, summarized and combined with other data from earlier (ads, referrers, etc.) or later (activation, retention) in your customer lifecycle.
All data processing should directly tie into an effort to answer one of the questions important to you. In other words, don’t pre-optimize your data processing for “future needs.” Have a plan to mine the answers to your current questions. A little data processing can go a long way to making those answers accessible (and if you’re not sure where to start, one of our data analysts offers a few ideas in this post). But before you begin collecting clickstream data, let alone processing it, pause to consider #3…
3. Explore non-analytics uses of your clickstream data.
Clickstream data isn’t just for analytics:
- You can send user clickstream data to tools such as Facebook and Google Ads to help target ads more precisely.
- You can send data to customer interaction tools such as Intercom or Drift to send user identity information in order to augment the user experience of their platform.
- You can send data to Optimizely or Visual Website Optimizer to power your A/B tests.
If you’re going to initiate a new kind of clickstream data collection, don’t miss a key opportunity to gain additional value from it. Maximize your use of user event data from the get-go by exploring how it can make the non-analytics tools you use even more impactful. None of the prior steps matter, however, if you’re not ready for #4…
Image from wallpaperswide.com
4. Be poised for action.
All the analysis in the world is useless if it’s not driving actions and reactions. Strike a balance between the time you spend poring over data and the time you spend reacting to it. This can be formalized through a recurring process where numbers are reviewed, with two outputs:
- What actions or experiments should we conduct to improve the numbers?
- What changes do we need to make to our data collection, processing or visualization to have better information for the next review?
Of course, it’s hard to be ready to change without having some semblance of an idea how: new marketing strategy? Web redesign? Change course on the product roadmap? Anything goes. And instrumenting your website and app for clickstream is only worth it if you’re prepared to do what the data tells you. Which will almost certainly include #5…
Courtesy of Trong
5. Get ready to explore new technologies.
Once you get the basics up and running, keep in mind that machine learning and AI have emerged from academia into the real world and raised the bar for everyone in data. In fact, machine learning can be accessed through cloud services or through open-source tools such as TensorFlow and PredictionIO. There may be opportunities for you to gain a competitive advantage or breakthrough performance by innovating beyond simple data collection and linear mathematics.
Getting in on these technologies early could be the key to success for your organization — and amping up your current data analysis is the foundation for that next step into new territory.
Looking for a little help?
This may seem overwhelming, but you don’t have to go it alone. Connect with marketing and/or product managers at fast-growing companies near you and buy them lunch or coffee — you’ll likely discover a rich community of individuals who are all working on putting data to work for them, with similar challenges to you.
Jumpstart your journey by signing up for Astronomer today (the first 50K events per month are free). Our platform allows you to level up your clickstream game beyond raw data collection. We have dedicated support on standby if you need any help getting set up.
Originally published at wwww.astronomer.io.