Editor’s Note: Today’s post comes courtesy of Roland Smart, Vice President of Social and Community Marketing at Oracle. He joined Oracle as part of its acquisition of Involver, a social technology platform and an early Facebook Marketing Developer. Follow Roland on Twitter @rsmartly.
- How did the hashtag become a foundational symbol on Twitter?
- How does user experience design explain the adoption of certain social idioms and slang (i.e. the use of "Throwback Thursday" on Instagram)?
- How do you adjust the voice of your brand to fit the conversational norms of different social networks?
I'll be answering these questions among others during a SXSW Interactive presentation this Sunday, March 9th.
(In Austin? Join our discussion in person and RSVP here.)
These questions are all related to the same phenomenon: social technologies are changing the language habits and behaviors of marketers and their customers. That might seem like a self-evident claim, but I think it merits some further discussion. Let me focus on one related point in particular:
As they evolve, social technologies will expand our definition of the universal customer profile. Many businesses are already learning from their customers’ Digital Body Language; improvements in social analytics will only accelerate this trend.
Today, interpreting Digital Body Language involves the tracking of certain overt signals. For instance: let’s say an email list subscriber opens your drip campaign message, and immediately clicks on the “Share This on Facebook” button therein. You might take this as a definite endorsement of your content. Also, while you aren’t 100% sure, the customer’s action implies that they spend a non-trivial amount of time on Facebook: perhaps then you should reengage with them via a targeted Facebook Custom Audiences campaign.
Ultimately, I predict that such “foreground data” will constitute just one part of a more complete customer record. In addition, expect the development of marketing technologies that help us analyze what we might call background social data.
Imagine this: your customer is wearing an iWatch or Galaxy Gear smartwatch, with built-in temperature, humidity, heart rate, and location sensors. During the first week of March 2014, the device senses that your customer is both 1) attending a very rainy SXSW, and 2) constantly sprinting from venue to SXSW venue. On top of this, imagine that this person lamented on Twitter about "only having 15 mins to pack my suitcase for Austin."
Now, picture an analytics platform that has access to these data. Reading between the lines, the platform concludes: it’s very likely that this SXSW attendee has been frantically running outside in the heavy rain – and by all accounts, they probably forgot their umbrella at home. In turn, this informs a tongue-in-cheek subject line that you use in your next marketing email to this person: "Stay dry at SXSW: visit our welcome tent + enjoy 2 free drinks on us."
Is this level of customer knowledge too far-fetched? While there are a lot of serious privacy- and data access-related considerations that would need to be resolved, I think the full promise of instant personalization and predictive analytics will be realized sooner rather than later.
Here, I’m reminded of the rumor that Amazon has begun experimenting with a systems process called “anticipatory shipping”: the company analyzes social media cues, product browsing behavior, purchase history, etc. in order to accurately predict the items that a customer will buy – and this allows Amazon to ship these items BEFORE the customer actually puts them in their shopping cart.
It’s exciting to ponder an analogous evolution in the universal customer profile. What if social technologies are one day able to predict the majority of our interactions with buyers, prospects, and brand advocates? As a marketer, how would you use this head start to strengthen your relationships with customers?