For anyone who works regularly with mobile or web solutions, you understand the necessity of data for almost all digital functions. Without the right data, systems run dry and are useless until replenished. Mobile analytics tools work the same way. Unless you are actively tracking user engagement metrics on a daily basis, your stream will run dry. Although, this time it won’t be data you are missing, but customers.
In today’s day and age, marketers and business owners need to understand how mobile analytics tools function in order to stay ahead of their customers. In this article, we are going to take a look at how to use these analytics tools for success, both when capturing data and using it for analysis. Without taking up any more time, let’s get into it.
Sometimes referred to as “data mining,” the act of collected mobile analytics should begin as soon as possible. The more information that you are able to collect, the better your analysis of your customers will be. Start by taking a look at your latest customer retention techniques and how they worked, this can give you a good insight into where you should focus.
When trying to track mobile users, analytics tools can come in a few different variations. For example, a mobile app is easy to track as you have complete control over the entire situation. Whereas something like a mass text marketing campaign can offer you analytics like click-through rate and conversions, but not the whole story.
Our advice is start mining early and collected as much data as you can.
Capture all data
One of the biggest mistakes made by first time users of analytics tools is to try and predict which data will be useful and which will not. Not only is this an unwise approach, but without all the data available, your reports will be skewed and unreliable. Instead, capture all possible data from as many sources as possible.
Thankfully, a lot of this sort of capturing can be done with marketing automation today. However, we recommend spending a good amount of time setting up the process before you begin in order to make sure you are getting the most out of it. When you are capturing all of that data, creating an understandable filing system will save you a lot of headache later. You may not even need all of this data, but you should capture it anyway and have a system for finding it, should you need it.
Quality over quantity
Now, it is going to seem as if this next step counteracts the previous one, but that is not the case. When we say that you should use quality data over a large amount of data when running your analytics tools, we mean that you should use only relevant data. Despite that fact that we just told you to collect all data from mobile app analytics to user time management habits, that doesn’t mean you will actually need to use all it.
Instead, you should select the information that is pertinent to what you are working on and use your analytics tools to discover the true story. While you should absolutely avoid making assumptions about your audience (more on that in a minute), you should at least know which data is relevant to your current situation. Then, use that to make decisions, not the irrelevant data.
Another common pitfall made when using analytics tools is to come into things with a certain viewpoint and then make assumptions about your customers based on what you have assumed about them. Not only is this unproductive, but it will lead to poor analytics results as well. Instead, try to approach each new look at the data with an open mind, there may be something you missed before due to unintended bias.
It is also worth saying that you should make decisions based off past experience and data from your analytics tools. This is different from simply assuming things about your customers without the proper follow-through. However, if you have already done the analytics and understand the context before making a decision, that is by all means a wise and thoughtful approach.
Avoid unnecessary risk
When you are focused on reducing churn rate and retaining more customers, it can be difficult to approach all decisions with such a clear, thoughtful mind. This is another area where those using analytics tools fall short and end up taking unnecessary risks for the sake of collecting data. While it may have been that you used to have to bed your customers for their feedback on your product or service, analytics tools have taken over.
Now, your customers should never have to perform an extra step or invest additional time to give you the data you need. If you are able to follow these best practices for using analytics tools, you should be able to collect everything you need without any interruptions to your or your processes. Not only will this help you avoid customers who can grow aggravated from repeat prodding, but it will create a better process overall.
Remember the full picture
Out last piece of advice when it comes to using analytics tools is to remember the full, overall picture of your customer retention marketing campaign. It can be easy to get bogged down by stats and analytics tools, so it is important to keep an optimistic mindset and remember why you are doing the things that you are.
For example, it may seem tedious when you are creating your marketing automations and putting together your campaign, but once you see the customers start to roll in based off your smart, data-based marketing decisions, the whole thing will feel worth it. You should also begin to see that the data you collect has an effect on your mind and the way you approach other issues.
By remembering the full picture, you can prepare yourself for anything while being ready for everything. We hope that you are able to use both these best practices and analytics tools to create a better experience for both you and your customers. Now, get to mining!
Co-Founder, Gleantap & Mastera