The art and science behind creating magic mobile moments166 views
by Michael Della Penna
As mobile tech continues to advance, marketers can use algorithms for dark data to drive micro-moments, ultimately improving the customer journey by catering to users’ immediate needs.
Last month, I introduced the concept of creating magic moments. To create this “magic,” the recipe calls for capturing thousands of micro-moments across a customer journey and combining it with the knowledge you have about that customer, through the addition of location, proximity, context, and predictive analytics.
But creating magic moments is not easy. Customers feel valued when relevance, timing, and frequency converge in the right way within the context of their experience. This requires a new set of sense and response skills that are difficult to master. Marketers need to not only identify what to send, but also when to send it and through what channel. Getting this done to scale across your customer base adds another level of complexity.
The first wave of mobile customer engagement has tried to set up triggered, canned messages based on geo-fences and beacon signals.
However, setting up basic location-based triggered messaging doesn’t “auto-magically” deliver great customer experiences. Many of these programs result in overly frequent messaging and disregard context, thus only irritating your customers. Instead, marketers must use mobile signals and movements to sense and respond to customer needs in the moment.
At a high level, here’s what data and science are required in the next generation stack, to create magic moments:
Mobile signal informed data
Earlier this month, my ClickZ colleague Anna Bager wrote a great column, How to Use Mobile as a Bridge Between Digital and Physical. Bager states the importance of moving beyond location and geo-fencing, and presses marketers to look at location as more than just a targeting attribute.
In fact, the real value of location and movement data is beyond just one point in time. The value lies in the dark data; the implicit relationships within the data that, in turn, exerts influence.
By using algorithms with dark data, marketers can create a foundation to drive the insights behind a marketer’s ability to sense and respond to customers’ needs within a micro-moment.
First and third-party data
To provide additional context around the customers’ journey, marketers can enhance the data set with data from internal and external sources. Examples of this data include, but are not limited to:
- First-party CRM data
- Behavioral data
- Psychographic data
- Life event data
- Loyalty and channel preference data
- Third-party demographic data
Brands can also overlay information from stores and properties – such as planograms – that detail specific placement of products, which brings powerful context to observed movements. These data sets enable marketers to create dynamic audiences – like sports fans, foodies, and so on – and provides additional context for making decisions on how to tailor experiences that create more value for customers.
As critical components of data science and predictive analytics, algorithms underpin a marketer’s ability to create magic moments that can scale. It’s essential to graph similarities and index users, create clusters and classifications, and even leverage the power of collaborative filtering to infer future purchase intent or product interest.
Algorithms are an art and when done well, they can dramatically boost a brand’s ability to delight customers and differentiate itself from competitors that rely on traditional location-based triggers with canned messages.
When working together, these three essential elements help marketers determine what to send, when to send it, and where to send it to at any given micro-moment. This is where the data and science foundational blocks which are required to create “magic moments” fit together.
Today’s consumer have a “you better know me” attitude and marketers looking to survive and grow in our cross-channel world need to up their game. To do so will require a real commitment to the data and technology needed to sense and respond to customers in real-time.