In this blog series, I’ll uncover the power of personalized omnichannel experiences. Due to its expansive subject matter, I’ve broken it down into three parts. I already went over part 2, how offering tailored mobile app content is crucial in your omnichannel success. For part 3, I’ll explain how to leveraging mobile data & analytics that supports exceptional omnichannel experiences. If businesses wish to succeed in the mobile revolution, they must manage and measure mobile data with the right metrics and processes.
Mobile data is a topic so big, it deserves its own category. Because of the wealth of information and different techniques to leverage data, I cannot cover all of it in one blog post. Therefore, I’ll introduce the highlights of mobile data you need to know about in this blog post. Then, I’ll conclude the post with a tip to help you leverage the data you already have.
The Problem with Mobile Data
Your mobile data is scattered. It’s siloed. Or maybe you don’t know how to connect the dots in the omnichannel customer journey. Resolving these issues starts by choosing the right metrics to measure. Then the next step is implementing the right mobile analytics platform and using the right techniques to leverage your data. Let’s get started!
A Few Metrics You Need to Measure:
- Location they registered (geographic town, city, country, etc.)
- Device type/operating system
- Online behavior (opens, last online, uninstall/deletion rate, specific screens opened, duration time spent via in-app beacons)
- Asset behavior (#views, opens, redeemed, expired)
Proximity Marketing (Location-based) Metrics:
- Which store your customer visited? When, how often and how long they stayed? Did they dwell in front of a certain shelf?
- Did the end-user pass a beacon range?
- Did your customer pass a geo-fenced range?
- Do they visit a competitor store more often?
- Loyalty data
- Web profile information (web content management)
- Point of Sale (POS) like commercial data, products purchased
- How many times your customer visits your store
- If your customer prefers chocolate ice cream over vanilla
- If your customer has children or not
- If your customer likes to shop on weekends or after 6 pm on weekdays
- Any other open-ended profile question you can ask via survey, push, registration onboarding, etc.
If you’d like further definitions about these metrics, I encourage you to download our Advanced Analytics sheet.
A Tip to Leverage Data – Split A/B Testing
If there are any gaps in your customer journey, use A/B testing to get a better sense of what works for users according to the channel. For example, if X amount of users abandon their app cart, does sending a voucher to a selected few persons to encourage them to buy.
Or perhaps you’re not sure why your customers stopped visiting your store. Therefore, you geo-fence your competitor’s shops which tell you that a number of your customers are shopping there. Hence, you send out the voucher to 1 persona group (variable) and leave another persona group alone (control). Let’s see if you can bring the variable group back to your store to use their voucher! Those are a few examples of split A/B tests.
By mapping out your customer journey and connecting the data points, you can better understand what your customer expects from you. Therefore, you can better understand how to create exceptional omnichannel experiences for your customers. And if you create exceptional experiences, you generate more revenue and increase loyalty. As long as it can be measured, it’s manageable.