"The better we know our customer, the more effectively we can market to them." This has been true since cavemen traded animal skins for berries. But it was with the advent of the Internet that marketers suddenly had the tools to truly understand their consumers in real time. First it was websites and email marketing, followed by social media marketing. More recently, marketers have turned to inbound marketing, in which they gently "prod" customers with valued content, until the customer signals they are ready to engage.
Now there’s "context marketing." Context marketing, in the words of one marketing firm, “uses technology to glean insight on the person behind your persona, and deliver customized messages in a way that most appeals to that individual.” But what do we mean by context?
What is Context?
Anind K. Dey, associate professor at Carnegie Mellon University’s Human-Computer Interaction Institute explains that when humans talk with humans, they are able to use implicit situational information, or context, to increase the richness of their interactions. But transferring the understanding of situational information to a world where people interact with computers has been very difficult.
This is now changing. The technologies built into smartphones and tablets, social networking sites and commercial cloud services are generating a goldmine of marketing data. These data can be then mined to achieve new levels of situational awareness. But what exactly are the technologies behind context marketing?
The Technologies Behind Context Marketing
Four new technologies are providing the ingredients necessary to understand situational awareness; they are:
- Cloud services – consumer services like search (e.g. Google, Bing), news and music (e.g. Flipboard, iTunes), shopping assistants (e.g. Amazon, Red Laser), and even productivity tools (e.g. Evernote, Microsoft Office Online) accumulate a wealth of user-related data that can be mined to understand users’ behavior, preferences, and habits.
- Mobile devices – sensors in cellphones and tablets log data about the users’ movements, including how long they spend in each location. A 2008 study showed that even a small sample of mobile phone GPS records allow researchers to make highly accurate predictions about subscribers’ future whereabouts. When coupled with geo-data like store locations, marketers can infer much about what people are doing during the day.
- Social networks – patterns of friend connections on Facebook, WhatsApp, LinkedIn, Twitter, SnapChat and other social networks provide insights about influence dynamics between friends and colleagues. When coupled with understanding the content being shared and discussed, marketers can obtain a rich view of a user’s persona.
- Big data analytics – each of the previous three technologies provide the building blocks for marketers to craft a consumer profile from data. But putting the pieces together is a daunting task and one that new "big data" analytics tools are only now addressing. While many forms of context can be understood from simple interpretation of user data (see the next section), it is only when marketers will be able to cross-reference data supplied by many sources that the full promise context marketing will be realized.
By themselves, each one of these technologies can provide a particular snapshot of consumer behavior and preference. Used together, the technologies allow marketers to piece together a highly-accurate 360 view of each and every one of us. To date, combining information from multiple sources has been challenging, since each vendor collected data independently across each channel. But this is changing.
Mega-vendors are successfully capturing user data across multiple channels. Google is able to cross-reference search history with the geo-location provided by mobile phones to push highly targeted ads to mobile users. The Facebook Phone was an attempt to do much the same, as was Microsoft "Windows Mobile First" strategy.
And vendors don’t need to directly capture user data on each channel to build context. Growing ecosystems are enabling vendors to cross-reference users’ online activities across multiple channels. Facebook, LinkedIn, Google, Yahoo, Microsoft and others now host ecosystems through which partners can participate to gain additional exposure, while supplying the host with additional user data.
The four technologies listed in the previous section are the building blocks for uncovering the situational awareness that defines context. Here are some of the ways that context is used by marketers to create highly-effective encounters with prospects and customers:
- Location — display mobile ads based on the signal provided by a mobile phone’s geo-location, or offer in-store ads based on a person’s location within a store.
- Time — generate ads based on time of day. Knowing when a person eats for example, allows advertisers to target a worker prior to their lunch hour.
- Social Interactions — offer informational content to prospects based on their connections on social networks and Twitter follows. Marketers have long understood the adage "tell me who your friends are and I’ll tell you who you are."
- Interest in topics — provide ads based on historical activity. Ever notice that after searching for something, you start to see ads for that item on many of the sites you later visit? You have Google "remarketing" ads to thank for that.
- Sensors — send offers based on data supplied by apps providing sensor data to marketers. For example, an exercise app accessing sensor data such as distance traveled and heart rate, can provide information about a person’s exercise regimen, indicating interest in specific products or services. In the future Internet of Things, context signals provided by sensors will represent a major source of personal information.
- Image Recognition — send an e-book or infographic based on images captured on a mobile device. For example, marketers can send a product catalog to a mobile subscriber, based on the identification of product logos captured in the subscriber’s Facebook photos.
- Emotion and Sentiment — offer information about a product or service based on a user’s recent online posts, including their views expressed in blog posts, article comments, Facebook posts, tweets, pictures and videos.
An example of combining information to form a rich context is demonstrated by Red Laser, a shopping assistant app, which uses a mobile phone’s image recognition capabilities to read a product’s bar code. It then applies the phone’s geo-location to generate a list of competitive price information for the product in nearby stores. Red Laser also has an ecosystem that allows partners to supply product and pricing information, which can then be used by advertisers to better target users through the app.
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