Today we continue our Customer Analytics discussion with a quick checklist for your customer data analysis.
Three Steps to Customer Data Analysis
1. Identify the Key Performance Indicators (KPIs) that you will track and make sure you are capturing the relevant data.
This step is a combination of the knowledge from Parts I and II of our Customer Analytics discussion. With the wide ranging types of data that can be captured and the many comparison options to put the data in context, it is important to identify the key indicators of health and growth for your company.
This means looking at your company’s goals to decide which data sets and trends are most important to track. There are so many ways to track customer engagement that you can end up spreading your resources thin by trying to gather everything. Instead, prioritize the most relevant data and make sure you have the tools to get what you want.
Avoid ending up with a mass of random numbers by having a clear plan and a manageable list of benchmarks.
2. Integrate your customer data into a single comparison tool and convert data into comparable units.
The next step is putting all your data together. If you are using different analytics tools to keep track of email engagements, A/B tests or survey results, you need a centralized repository that can blend your data. This means thinking through software integrations; do you have CRM software that will integrate all your analytics and how will you add external data?
Centralized data also needs to be standardized for comparison. You will want a central analytics tool that will let you transform data into standard units, allowing you to gauge and compare customer engagement and satisfaction from purchases as well as customer service calls. Pulling real-time comparisons requires software that allows you to set a standardization plan.
3. Create a dashboard that lets you visualize your analysis.
Once your system is set up to load and compare all your data, you need a plan for converting the raw numbers into an easy-to-read format.
⋅ Use charts & graphs in conjunction with in-depth reports. Set up real-time-updating trend visualization in your analytics software. Use charts and graphs that reflect your core KPIs (hopefully a manageable number) and promote instant comprehension of your data. Also make in-depth reports on the underlying data easy to generate, so that you can easily dive deeper when you see changes.
⋅ Set up alerts for important comparison points and benchmarks. Identifying the small number of benchmarks that require the most awareness additionally helps narrow your focus. Setting alerts based on these benchmarks will give you the best chance to respond rapidly.
Now that we have mapped the steps for analyzing data, we’ll look more closely at how to conduct some of the relevant comparisons. Come back to the blog as we continue to unpack customer data.