Context: Today’s customer-centric businesses can’t get enough of it.

If you look at this press release from Aspect Software, you’ll understand why. People are taking command of how they carry out commerce through their smartphones and PCs, starting with search and culminating with queries and transactions that involve a company’s automated systems (voice response or chat) or live agents. Their common complaint is that they should not have to repeat themselves every time they move from one channel to another or when their conversation is transferred (or “escalated” to use popular parlance) to a more appropriate resource.

Maybe it’s subliminal; more probably, it’s based on personal experience. Whether shopping or searching, people know that almost every interaction they have with their bank, airline or online retailer is informed by data or metadata that has been “aggregated,” “ingested,” or otherwise obtained directly from them or from the community of credit agencies (like Experian, TransUnion, LexisNexis, etc) or “data brokers,” like Acxiom, Corelogic, Datalogix, eBureau, ID Analytics, Intelius, PeekYou, Rapleaf (now TowerData) and Recorded Future, who were called out in a recent FTC report calling for more transparency, accountability and user control).

By the FTC’s estimation, the firms mentioned and their cohort generated in excess of $200 billion in revenues in 2014. This figure may serve as a proxy for the financial value of reselling the personal information industry; but, in doing so, it greatly understates the intrinsic value to individuals who can use it to take command of their digital lives or the companies with whom they choose to do business, who can apply it toward making every experience or “touch point” more effortless and productive.

Believe me, this post is not a jeremiad against privacy invasion or a rail against involuntarily “harvesting” of everything from voiceprints to transaction histories. I’m aiming to raise awareness of the fact that both the individuals who originate the data and metadata and the companies that put these data to use can benefit from putting customers, rather than advertisers, first. Then, as a direct result of building personalized services, raise both satisfaction and loyalty. The next step in the chain of causality will be that companies (or “brands” if you prefer) meet their own key success indicators, including operational efficiencies (reduced cost), loyalty (customer retention) and upselling (revenue enhancement).

That’s the virtuous cycle. Individuals knowingly provide context (both explicitly and implicitly) that results in better, more personal digital experience.

Here in the real world, however, the balance too often swings away from customer experience and empowerment in favor of well-understood (and measured) enterprise performance indicators, specifically targeted advertising objectives. Not to single out Big Blue, but I want to use IBM’s $2 billion Watson investment as an example. In January 2014 I posted the observation that IBM Watson was destined to be “a boon to Conversational Commerce.” Indeed, IBM has done a fantastic job of raising awareness of “Cognitive Computing” and teaming with large enterprises and small developer groups, alike, to show how its special combination of deep neural networking, natural language understanding, analytics, and question answering applies to healthcare, travel and hospitality and even cooking.

As the old song about Woodstock goes, “Maybe it’s the time of year or maybe it’s the time of Man,” but few of the initiatives to improve healthcare, travel and transportation, or generating recipes have gotten the attention garnered by the work of IBM Analytics to makes sense of the Twitter firehose or, more recently, work done with Facebook to use the analytics embedded in its marketing cloud to “supercharge” targeting of its advertising messages. While the initiative involves Watson only indirectly, it exemplifies the antithesis of Intelligent Assistance because it involves aggregation of an individual’s activities and posts (arguably “public information” on Facebook) for use by third-parties as metadata to target their advertising efforts.

That’s the Context Conundrum: How can we ensure that personal data or metadata is used to our benefit?

Advertisers treat metadata as context for delivering targeted (and often mistargeted ads). Rather than benefiting customers, these are often regarded as intrusive or, at least, annoying. It is the antithesis of Intelligent Assistance. Indeed, the cause of IA will be given a big boost as individuals – realizing that they save time and effort by providing relevant “context” to their devices and preferred vendors as well as “friends” – take better control of their digital exhaust.

Categories: Intelligent Assistants, Articles

Tags: customer experience, Natural language processing, IBM Watson, Intelligent Assistance