Digital Customer Service Is Becoming A Fully Realized Marketing Channel
Predictive analytics, self-service knowledge bases and personalization are turning the reactive interaction into a marketing opportunity.
Traditionally, customer service has been reactive.
You have a question/problem about the product you might buy or have already bought. You walk into a physical store, present your need, get a response to that inquiry or exchange and leave.
But marketing technology is now helping customer service evolve into the online equivalent of a bartender who knows just what you want to drink, as you sit down, before you say a word.
This application of predictive analytics and other marketing technologies to one of the oldest realms of customer interaction doesn’t only mean the process will be faster. It also turns customer service into a more fully realized marketing channel.
When marketers and vendors list digital marketing channels — email, mobile apps, mobile web, websites, social media and others — they don’t often include online customer service. But that’s what customer service is becoming.
“Support technologies, digitally deployed, have two roles,” AnswerDash CEO Bill Colleran told me. They can be used to answer questions, and they provide “the opportunity for upselling.”
His company offers one example of how marketing tech can intelligently guess a customer’s real needs and possible related interests. AnswerDash offers contextual answers that predict what other info the customer might want, in order to cut down on email and other kinds of support. Not coincidentally, it provides upselling and cross-selling opportunities.
Simple, frequently asked questions can have simple, looked-up answers provided by the platform, Colleran noted, as well as related questions that are also frequently asked. If a customer inquires about the colors a sweater comes in, for instance, the response can be that we have it in these colors and these sizes, and cotton, as well as wool.
“CRM Customer Service”
But “questions that are more complicated, and are not amenable to a canned response,” he said, “typically end up in a [live] chat, where there are more [marketing] opportunities.”
And user profiles, purchase histories and a record of previous inquiries can help a trained contact agent anticipate the customer’s needs, just as they can better shape how platform software might respond.
A report released last month from Forrester Research, “Trends 2016: The Future of Customer Service [purchase required],” describes this merging of customer knowledge with support as “CRM [customer relationship management] customer service.”
The report also points to the missed opportunities:
“Many organizations use a combination of rules and analytics to present personalized cross-sell and upsell offers to customers — all tactical uses of decisioning. But organizations fall short on leveraging the true power of analytics. They often don’t understand customer segments, typical customer journeys, the events that triggered a service interaction, and the best resolution to these issues.”
Forrester predicts that this year, many organizations will begin to utilize analytics to better map out what the customer is really looking for and who/what can best help her.
Similarly, the report points out, we are moving into a era of truly predictive customer service, where always-connected devices — like connected Tesla cars that automatically download their software updates — can offer support before you know it is needed.
Although there are many examples where connected sensors in virtually everything — the evolving Internet of Things — could get downright creepy, pre-emptive customer service might actually be something we need. If we can control the privacy issues, having the manufacturer remotely diagnose and service an issue on my refrigerator before I have to call for a repair could be a time-saver.
And it means the maker can offer me services or products I didn’t know I needed. A faster ice-maker for the one about to die in the refrigerator, perhaps?
But if someone is going to predict what the inquiring customer really wants, why not let it be the customer?
“The challenge has been that support has the info but it’s not easy to get at and deliver,” AnswerDash’s Colleran said. When implemented toward the aim of self-discovery, the info can be made easy to get and retrieve by the inquiring customer.
Katy Keim, chief marketing officer and GM for Lithium Social Web at social community provider Lithium, pointed out that customer service “is not push [marketing],” but — assuming it’s you making the inquiry and not your car being queried remotely — it’s an inbound activity. The customer comes to you, instead of marketing reaching out to the customer.
An inquiring customer can be a powerful engine. Lithium harnesses that power with its social communities, where answers can be offered and curated by the community, as well as by the business.
Here again, previous examples of the same question have made it easier for the community or the business to offer the related answers, as well as the targeted one. I might be looking for an answer about how my new Roku streaming device needs to be set up, for instance, but I also explore related threads on new streaming services I can add. Feels so much more comfortable when I’m the one pitching myself.
Whether enlarging an initial inquiry by self-discovery, predictive analytics or personalization built on knowledge about the customer, perhaps we need some different terms for how digitally aided businesses are helping the customer. To the existing customer self-service, perhaps we should add a predictive customer pre-service, or, when really personalized, a service for one.
Opinions expressed in this article are those of the guest author and not necessarily MarTech Today. Staff authors are listed here.
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