4 Ways Analytics Are Changing Mobile Customer EngagementSeptember 11, 2013 By Lara Albert
For all of the hype around the fast-evolving space of mobile marketing, mass adoption and widespread success are still far off. Many brands, ranging from Fortune 500 companies to local retailers, have invested in the promise of mobile, yet few have managed to crack the nut when it comes to engaging customers in a way that drives value for both the customer and the business.
The clear advantage of the mobile channel is the ability to interact with each customer on an individual basis at any given time. It's not about achieving the broadest reach; it's about reaching the customers who have the highest propensity of driving value for your business.
This transition from a broad-swath marketing approach to one-to-one personalization requires a shift in not only your marketing strategy, but also your underlying data and analytics strategy. Success rests on the ability to understand and identify the right customers, and knowing when and how to engage them to drive the best results. It's about knowing your customers well enough to serve them, sell to them, nurture relationships with them, etc. And to do so, you must have the ability to act on data in a way that's quick enough and smart enough to ensure that you and your marketing are always relevant.
Here are a few proven tactics that brands are leveraging to advance their analytics capabilities in order increase the effectiveness of their customer engagement strategies:
1. How Do Your Customers Really Behave?
With traditional classification techniques, a marketer's understanding is limited to how a customer behaves at a given point in time and is often based on a subset of the available data. Mobile engagement requires a shift from traditional customer profiling based on derived averages or summaries of facts—i.e. light, medium, or heavy purchaser—to non-static behavioral profiles that reflect a constant flow of data. Dynamic profiling provides a multi-dimensional and timely understanding of behaviors, and highlights changes in behavior over time as they occur. This allows for more personalized, one-to-one marketing.
2. Monitor Dynamic Behavior
With a constant flow of data, marketers are able to recognize behavioral changes much more quickly than with traditional techniques. At the same time you can model, analyze and monitor specific behaviors that may otherwise be masked through traditional classification techniques. Dynamic monitoring identifies behavioral patterns, trends and abnormalities, as well as associated contexts, which enables marketers to act in a timelier manner. This helps to ensure that every communication—or in some cases, the decision not to communicate—is driven by an accurate reflection of the customer's current behaviors and needs.