E-commerce and click-and-mortar marketers are critically charged to gain customer knowledge for personalizing the online shopping experience in order to maximize conversion, shopping-cart size, and frequency of purchase while minimizing cart abandonment.   To meet the charge, you of course have many data-driven sources at your disposal to try to “know the customer behind the transaction.”

Both click-and-mortar and pure-Internet retailers have traditionally relied in part on purchase transaction data as indicators of customer interests and intent.  While they provide some level of indication, they alone can be misleading.  Purchase history tells you little about what’s driving customers to buy what they do, and it can’t distinguish between purchases made for themselves versus purchases for others.

As an example of where this can go wrong, I can tell you that my daughter-in-law is always buying gifts.  In fact, she recently purchased a foot massager for her elderly uncle’s birthday on her favorite e-commerce Site.  The next time she went online, she was targeted with offers from the site for skin exfoliators, senior vitamin supplements, and age spot removers. 

My daughter-in-law is 25.

The same can be said of other traditional data sources.  Web browsing behavior data, for example, only tells you that someone on a browser is looking around.  This person may be a serious shopper or simply a “want-it-but-can’t-afford-it” browser or even the child of the device’s owner. 

So how can mobile apps help improve e-commerce personalization?  It’s all about lifestyle context                                                                                                                                                                  

Let’s start with what makes mobile apps so powerful for customizing content and offers.  When connected directly to a location-based behavioral analytics platform, your mobile app, with opt-in location services turned on, becomes a privacy-friendly source for gathering behavioral insights on not only where your customers go, but what they do offline in their daily lives.  These platforms contain geo-fenced commercial and public venue and event data—as your customers physically visit these venues and events, anonymous records are gathered, even if the app is closed.  

Thus configured, your app can give you the insight to know your customers’ lifestyles—what they’re interested in and care about—personally—where they shop and dine, and what events and activities they frequently attend.  E-commerce marketers can use these to package and present custom content tailored to their personal affinities.  They can even help click and brands recover lost sales from cart abandonment by sending customers offers for what they’ve already shown interest in, directly to their mobile device as they come near a local store.

Here’s how it can applied  

Let’s look at how a major e-commerce brand can use this insight.  An Internet-based, multi-product retailer can learn for example, that a large percentage of its mobile customers frequently attend fashion events and run in 5K and 10K races.  With this insight, they know what these customers are personally passionate about (in addition to what they buy), and can package and present fashion and sporting apparel content, customized to their affinities.

That same Internet retailer can learn that another significant number of its mobile customers frequently visit kitchen specialty stores and farmers markets and take cooking classes. With this insight, in addition to purchase history, they can know that these customers are personally interested in culinary activities (versus buying for others), and can package and present relevant food and cooking-related content.

And these powerful insights aren’t limited to targeting within your mobile app—they provide actionable cross-channel value.  By appending this behavioral lifestyle data to your CRM/loyalty records, doing look-alike modeling and onboarding them to a data management platform, e-commerce marketers can present personalized content within the app, on their desktop and mobile sites and through audience targeting platforms.

While m-commerce as a stand-alone remains a small piece of the overall e-commerce pie (reaching $31.6 billion in the U.S. in 2014 versus $236.9 billion for desktop-based e-commerce, according to L2 Research), it’s growing at more than twice the rate of desktop e-commerce.  As shopping habits and device usage continue to shift, one thing remains constant—e-commerce marketers need to harness the power of mobile behavioral insights to deliver individualized personalization across all channels, to cultivate long-term loyalty with their customers. 

Gravy is a mobile app that provides users with suggestions of things to do based on the mood they say they’re in.

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