Putting “Context” in UC
Like most of the UCStrategies crew I’m freshly back from the fifth “almost annual” (we missed one year) UC Summit. The Summit is a truly unique event where we bring together leading vendors, solutions integrators (our name for “VARs”) and consultants in the UC space to exchange ideas about what’s going on in UC and where we think it will go next. So I’m still suffering from a “contact high” having spent three intense days with some of the real “thinkers” in UC.
While I enjoyed all of the sessions, one in particular struck me as it dealt in a topic area where UC overlaps with mobility. The session was Avaya’s keynote, delivered by CTO, David Chavez, who gave a wide-ranging presentation dealing with many of the challenges facing vendors in taking UC to the next level. The one that particularly engaged me is “context.” There are some contextual elements incorporated in UC products today, but capitalizing on context can be key to integrating UC more seamlessly in the way people work, and delivering the type of communications/collaboration infrastructure that can support the new modes of distributed, collaborative work.
Many UC products now have enhanced the communications “history” to include all exchanges with a particular correspondent including calls, videos, audio conferences, emails, and texts. Unfortunately, if I’ve been working on a number different projects with that person, I still need to subcategorize those communications by the projects they relate to; that’s not easy if we often talk about two or three different projects on the same communication.
Context is also a big topic in mobility, though (like most things mobile) it has been focused on B2C interactions. When we use the term “context,” it refers to the sum total of what the customer has told us along with what we can glean from other sources to optimize the user experience. Those elements could include transaction history, time, speed (e.g. stationary, walking, in a vehicle), and most importantly, location. We could potentially draw on other sources like social media entries, and the types of transactions or information that user has engaged in before.
Interactive Intelligence (In-In) has incorporated some of that in their Interactive Mobilizer, a mobile development platform focused on customer service. If a user encounters a problem, they can place a trouble request in the In-In application, the request is placed in a virtual queue, and the system will send back a time when an agent will contact them – no more “music on hold.” The user has the ability to reschedule the appointment to a more convenient time if they want. The app also sends the agent the full history of what the user had been doing up to the screen they were on when they placed the trouble request so the agent has the whole context of the issue before they call.
From a UC standpoint, location is a key metric, though as with consumer applications, privacy is a major concern. If we’re tracking users’ locations, we can track it through GPS (if they are running our application and have requested it) or anonymously using the Wi-Fi capabilities in their smartphones (unless the Wi-Fi is turned “off”); the smartphone periodically sends a Probe message, which will include the MAC address of the smartphone.
While some WLAN vendors look to implement shopper tracking in a very granular fashion using a location server that can pinpoint the phone’s location within a few feet, there are also “crude but simple” implementations that can still yield a wealth of information. WLAN vendor Aerohive has partnered with cloud-based Euclid Analytics to offer such a solution using Aerohive’s APs. Using simple received signal strength, the solution can track customers passing by the store versus those who enter; if the user enters, they can track how long they stay.
According to Tash Hepting, Aerohive’s Director of Technical Marketing, the system captures the MAC address but then hashes it and discards the MAC address, so they can identify the fact that “Customer XYZ” has visited before, but they have no way of knowing who “Customer XYZ” actually is. He goes on to say the solution can allow a retailer to do things like measure the impact of a promotion by knowing approximately how store traffic has changed during the promotion and whether it attracted new or existing customers (or ones who had only “passed by” previously).
Those types of gross metrics may be useful in retail, but UC applications will need to be granular to the individual by necessity. I have long decried the fact that UC vendors have not done a better job at incorporating location as a key metric for presence. Again, user expectations of privacy must be respected, but if the user’s calendar says they’re in a meeting, they are not typing on their desktop, and the location places them in a conference room, we can pretty well guess they’re really in a meeting – even if that meeting runs longer than what the calendar says it would.
Thus far the only UC vendors I’ve seen making any use of location are Mitel, ShoreTel, and AVST. The primary applications are setting presence status, and more typically, selecting user device preferences. So if the system recognizes you’re at home, it can switch your device preference to your home office phone. AVST is using presence information in its soon-to-be-released ATOM personal assistant.
The key idea to recognize is these sorts of contextual associations are already appearing in consumer services. We all seem to recognize that the consumer offerings are more advanced in many of these areas, so the competition among the UC vendors may come down to whose implementation comes closest to delivering that consumer-like experience, while offering the types of efficient collaborative work functions enterprises will need.