There’s an interesting and high-stakes battle taking place right now in the world of customer service: What will be the dominant text-based channel for B2C communications? SMS remains the most ubiquitous channel, but least flexible. Competing against it are the big corporate-owned messaging platforms: Messenger and WhatsApp (both from Facebook), Apple’s Business Chat, and Google’s offering called (for now) Google My Business Chat.
The Battle is also an Opportunity
Since no channel is a clear winner, companies are, wisely, supporting multiple channels for delivering customer service. This, in turn, is an opportunity for other companies to create abstraction layers to allow these multiple bets to be made more efficiently. SparkCentral and Smooch are great examples of this. (We covered Zendesk’s acquisition of Smooch here: “Acquisitions Point to Messaging’s Future in Customer Service.”)
One of the jobs of these abstraction layers is to provide a unified view of sessions. That’s especially tricky for SMS which has the most simplistic messaging model – there is no intrinsic concept of a thread, session, or conversation with SMS. The big CPaaS players are also providing ways to target multiple channels at once: Twilio with Conversations; Nexmo with Dispatch; Amazon with Pinpoint. Although these products, in theory, equalize the different channels, they don’t do anything to solve the “discoverability” problem.
Discoverability and Messaging On-Ramps
Discoverability is about answering this question: “How does a customer find out that messaging is an option with a particular company?” This is where Apple, Google, and Facebook are each working to create “on ramps” as in the figure below. In a way, this is the real battlefront.
Beware False Scorecards
It would be great if we had clear stats that would track the success of the various channels, such as “total unique conversations per month” or “unique active customers.” But, for now, such data is not being shared publicly.
The temptation to find a scorecard is strong, so beware of stats being cited that seem to fill that role but, on closer inspection, do not. The first of these is monthly active users (MAU) for a messaging platform. This is primarily measuring P2P messaging behaviour, which has no real connection to B2C behaviour. I’m not saying this data is wrong or misleading, but it shouldn’t be used for the wrong purpose.
Related to this is the “heatmap” of platforms by country. There is strong regional preference for different platforms, but again, this is not separating P2P from B2C messaging. Furthermore, most brands are not going to pick a channel based on how many countries it dominates. It’s better to have a channel that functions well even if it is, say, second-most popular in the countries you care about.
Finally, beware the “cohort study.” This is a long-running favorite of those writing about changing behavior patterns, especially vendors that have a stake in channels popular with younger folks. The lesson told by this data, they say, is that the preferences we see with the youth will inevitably become the preferences of the young-adults and then the middle-aged, so this is a glimpse into the future. But there is no guarantee that a 15 year-old’s preferences are locked in place.
The differences shown by the chart could well be driven by the pressures and privileges people feel at different ages. A 15 year-old values his time and money differently than a 50 year-old. He also has a different set of company interactions to manage. On top of that, the strengths and weaknesses of the different channels change over time as well.
Again, I assume this data was collected in good faith and with proper methods, and yet it illuminates very little about the future.
By the way, I am fully guilty of falling into these exact traps. In fact, all of the above images have been used in my own blog posts over the years. mea culpa!
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