Putting the Context in Mobile Content and E-Commerce

This article was originally published on CMSWire.

Mobile is a lifestyle, not a channel. So the value of mobile devices will emerge most strongly by engaging users in the context of their day-to-day activities. Engaging with users in order to develop an ongoing relationship is about serving them when they have a specific need, as opposed to pushing content and offers out to them.

This is a fundamental shift in the mindset of marketers.  They have now been sensitized to the need for understanding user needs and contexts and serving up appropriate content.  The challenge lies in integrating content marketing into merchandizing and brand management functions. 

Mobile devices add another level of context and complexity.  While traditional marketing consists of offers in search of customers, mobile marketing enables customers to search for offers in more nuanced circumstances.  This search process provides many indicators of customer interest. The businesses that can sense and interpret the customer signals and provide offers that meet their needs will engage most effectively. 

It is important to remember that engagement is just the first step in the process of executing a transaction.  Customers now purchase only after a longer cycle of research, and engagement is about building a relationship so that when the need arises, the customer will more naturally transact with the company that has that relationship.  Engagement is not about having a perfect mobile app or a slick user experience.  It is about understanding context – contextual awareness – and being event driven, that is, changing context when something happens.

Many ecommerce sites focus too much on the transaction itself, trying to optimize the user experience in order to complete the transaction.  However, a good user experience is now a given. The more important aspect of the user experience is the quality of the relationship.  The nature of the rest of the interactions and value, utility, and sheer pleasure of using the application or interacting with the web site, strengthens the relationship and leads to longer term value.

What are the characteristics of a good relationship?  A valued relationship – in any context – is about meeting needs.  The challenge is that needs vary depending on circumstance.   If I am at home I will have different needs than when I am in the car.  At work, my context is different than at the gym.  It also varies with my goal.  If I need something to assist me in doing my job, that is one goal set, looking for a gift for my spouse, another

Mobile technology has the ability to understand more signals about a user‘s context than any other technology.  Mobile phones are sensors that capture information about users and their activities.

Understanding those signals and responding to them in order to better meet the user’s needs therefore strengthens the relationship.  Sensing and responding to “signals” – user behaviors and context – becomes part of a conversation.  Like any conversation, people are more engaged when the conversation is about them.  “Enough about me, let’s talk about you…  what do you think of me?”  With mobile technology, businesses now have many more ways to tune into and meet user needs.

Mobile Content and Ecommerce: Leveraging Analytics

Aggregate behaviors on web sites, mobile-optimized sites, and mobile applications can be measured in many different ways.  The challenge is to link those metrics to context.  We may understand positive predictors such as popular content, social sources, organic search traffic terms, top selling products, length of session and revenue per user, as well as negative indicators such as high bounce rates and cart abandonments.   

In order to leverage metrics to strengthen the relationship, we need to understand the changing context of the user, react and respond to that change in context, and measure whether that response is valued by the user.  A change in context may or may not be meaningful. The user may or may not be receptive to an offer when their context changes.

A good example of changing context is entering or leaving a geo-fenced area. A resort might welcome a user with a notification and offer.  If that user enters and leaves several times per day, continual messages will become tiresome at best and annoying and damaging to the relationship at worst.  The same concept applies to a physical store.  If the user has a loyalty app, the store can leverage existing account data and create more targeted offers as customers enter the store. 

Several mechanisms can be used to identify a user’s physical location: GPS, assisted GPS, synthetic GPS, cell ID, Wi-Fi, inertial sensors, near field communication and beacons[i]. These geospatial awareness mechanisms allow more granular understanding of a customer’s context and therefore enable targeted offers and messaging for different geographic locations.  The offers can be targeted at various levels, from regions to cities to sections of a city down to neighborhoods, blocks, store level, and in store offers. For example, the use of in-store beacon technology can triangulate the exact location of users and monitor physical context in relationship to physical merchandising. 

We may know something about where the user is - which is one signal.  That needs to be correlated with additional data in order to meaningfully respond with an offer.  The ability to send targeted messaging to users depends on having some relationship with them.  We can’t just push things to user phones unless they have responded to an offer or downloaded an app.  Even then, we may not know enough about them to target an offer.  There are a couple of ways to address this lack of intelligence about the user. 

If we are lucky enough to have access to account information for an existing customer, more detailed characteristics of the customer can be inferred from past history data and correlated with location or demographic details.  If there is no access to account data and little known about the specific user, targeted offers can still be developed based on anonymized and aggregated data (available from third-party data brokers) that predict the makeup of foot traffic in a particular location throughout the day that is used to infer statistically meaningful characteristics of user populations.  It is also possible to identify changes in context. Mobile devices provide data about whether a user is standing still, walking, running or in a car. 

In each of these circumstances, the understanding of user context from aggregate data is really just an informed guess.  We don’t know the exact details of a particular user and even if we did, we cannot read their minds and know exactly what they want.

This is where traditional engagement metrics enters the picture.  In each of these contexts we can leverage a range of metrics:

  • Interaction metrics: Measure pathway through content and utilization (impressions, time on page), identify high-value and missing content, usability issues
  • Search analysis: Identify improvements for search curation (thesaurus, auto-completes, best bets, etc.), identify missing content
  • Impact analysis: Correlate content interactions to value drivers such as conversion, registration, purchase, identify action plans to improve content, search, or other programs
  • Content analysis: Measure compliance with editorial and tagging guidelines, remediate issues

By understanding the power of mobile context, it is possible to target and engage users in ways that strengthen the relationship and improve engagement.  Content and search metrics allow assumptions about the needs of users to be validated, and provide ways for ecommerce content owners, marketers and merchandizers to continually improve the quality of the conversation.  Ultimately, better, more valuable content will lead to better engagement and lead to more valuable commercial relationships. 

Seth Earley

Seth Earley is the Founder & CEO of Earley Information Science and the author of the award winning book The AI-Powered Enterprise: Harness the Power of Ontologies to Make Your Business Smarter, Faster, and More Profitable. An expert with 20+ years experience in Knowledge Strategy, Data and Information Architecture, Search-based Applications and Information Findability solutions. He has worked with a diverse roster of Fortune 1000 companies helping them to achieve higher levels of operating performance.