Digital data are more than just numbers. They are the digital footprints of your customers. By investigating where they came from and where they went, you can learn more about what your customers need and how to help them be more successful. Digital analytics is even more important now as the value of the brand decreases, the importance of direct customer relationships increases.
When modern marketing platforms, CRMs and digital analytics tools are linked together, you can segment your customers in more meaningful ways such as separating your most valuable brand loyalists from those who are more likely to purchase from a competitor. Leaders know that exploring behavioral differences, marketing preferences and messaging resonance can help focus your energy and budget.
In our experience, working with medium and large brands such as Nike, GSK, Seagate and more, the first stage of data instrumentation and digital tracking takes about 2 years. It does not matter if you are using Google Analytics or Adobe Analytics, the time is based on culture change, not technical speed. Getting to meaningful and actionable insights is a journey. See how digital analytics has changed.
Do you trust the data? If the answer is no, then it cannot be relied on to make critical decisions. Poor data quality is likely costing your company millions. As the number of modern analytics tools beyond Google Analytics and Adobe Analytics multiplies, this problems only gets more complex. It is easy to get data, but it takes thought, planning and experience to collect the right data. Here are some questions to probe the quality of your data:
Are you missing digital tracking to answer common business questions?
Has tracking been maintained as your digital strategy evolved?
Are there critical gaps between marketing tools such as email and analytics?
Answering these questions can be daunting, but Ambition Data can quickly help you whip it into shape and rebuild the trust so you can move on to produce greater insights.
Dashboards provide a snapshot of the current state of your digital program. They provide a simple way to keep your finger on the pulse and quickly identify issues that need to be researched further. While there are a lot of options for digital dashboards, many are designed to be one size fits all. As a result, they are often produced, but rarely reviewed or acted upon. There are three metrics that serve up satisfying reports as well as some common analytics benchmarks. Truly valuable dashboards get used. They answer meaningful questions your stakeholders have and speak in their user’s language. Creating great dashboards requires subject matter expertise, design skills and an understanding of the target audience to resonate with stakeholders. See some examples from our team below.
When digital analytics data is used in aggregate it cannot tell a story. For example, if you know time on site increased by 30 seconds this month, is that good or bad? Are visitors engaged or confused? We like to call these junk food metrics because they sound great but they contain very little nutrition to drive the business.
The best way to crack open data insights is to segment around the customer. However, not everyone has customer data especially in the beginning. When you have a lot of anonymous audience data, you should use an analysis strategy called use case segmentation.
Use case segmentation developed by Gary Angel simply in "Measuring the Digital World" asks “who is coming” to my site and “what are they trying to do” when they arrive? It’s based on the idea that every visit has a primary focus so people who beeline to the deals page are more likely to be deal seekers than job seekers. Here’s a more advanced example using mobile geographic context.
As previously mentioned, your digital data is your customers’ footprints. Analysts are “trackers” who read the signs, make sense of it and unpack the insights. Whether it’s a landscape analysis used for benchmarking, or a deep dive focused on optimizing your UX or conversion process, there is a lot to be learned. Even experienced analysts can have trouble making these analyses come to life. Here are 7 tips for analytics professionals.
What story are your customers trying to tell you?