The title gives it away.
In summer 2020, we moved a large telco client from our chat technology to a pure business messaging platform. The goal, of course, was to drive efficiencies and I’m happy to say, as you may have surmised, it’s been a spectacular success.
There are two main reasons for that. First is the business messaging platform itself. Its impact, described in detail below, is clear, irrefutable, and dramatic.
The second is the value of 7.ai optimization services. However wonderful a technology, such as conversational messaging, it’s still just a tool—so the more expert the practitioner wielding it, the stronger the results. We worked closely with our client to analyze its business, determine the best use of conversational messaging technology, identify efficiency targets, measure performance, and finetune operations over time.
First let’s look at those results.
In the four months since our client deployed the 7.ai business messaging platform, in June, its “cost per resolved contact” dropped by 28 percent, and its overall conversation volume shrank by 23 percent.
It’s worth noting “cost per resolved contact” includes the cost of repeat contacts inherent in traditional chat. Business messaging customers typically resolve their issues in a single, contiguous conversation (even if it plays out over days or weeks). With chat, that's not the case: The session ends and customers, if not satisfied, need to start again. So to do this comparison appropriately, we've added in repeat contacts from chat channel.
I’ll peer deeper into these numbers in the sections below.
When companies adopt business messaging, they usually want to blend their agents’ responsibilities across the legacy chat channel as well as the new business messaging platform.
As our client learned, this is a mistake: Using blended agents costs money.
To fully reap business messaging’s advantages, you need to field a substantial number of dedicated messaging agents. Our efficiency metrics reveal that, compared to blended agents, dedicated business messaging agents deliver:
AHT in the business messaging channel is both much lower, and much more predictable, than in the chat channel—which lowers costs and simplifies staffing over time.
Chat AHT fluctuates quite a bit for two reasons. First, chat is inefficient; if you're not staffing chat appropriately—overstaffed in some months or areas and understaffed in others—your numbers will quickly go through the roof.
Second, mishandled chat staffing means you’ll have more recontacts later, which amplifies that chat variability. Business messaging, on the other hand, resolves issues in one conversation so … no recontacts.
That’s why the key AHT metric you need to consider is time to resolve a contact, not simply time spent on a contact. In the business messaging channel, handling time to resolve a contact is consistent—and much quicker.
Dedicated business messaging agents have 38 percent more conversations per hour—not merely interactions—compared to traditional chat agents. This per-hour measurement closely mirrors resolution rates because messaging conversations are much more likely to end only when the customer is satisfied.
With chat, some conversations end but aren’t resolved, which, of course, drives more conversations. With messaging, the customer controls when and whether to end a conversation, so a much higher percentage are resolved.
Business messaging performance is just that much better—both in terms of sheer numbers of conversations per hour, and the percentage resolved.
And, in fact, that’s also what we find when our clients ask customers “Did we resolve your issue?” Customers say messaging resolves their issues 15 percent more frequently, on average, than does chat. The key reason: Business messaging requires fewer contacts to resolve the same query.
This story is not just about business messaging’s awesomeness; it's also about how 7.ai enables our clients to get the most out of the technology.
Don’t get me wrong. Conversational messaging technology really is a CX game changer. But only when it’s used correctly.
Before we rolled out the business messaging platform and ported our client over to it, we made sure we understood their business and their goals, and then we optimized the conversational messaging technology for that. We established agreed-upon efficiency targets and set up systems to track metrics and gauge performance. Then we jointly assessed the results, which I’ve been describing over much of this blog.
Those results wouldn’t have been possible with messaging technology alone.
7.ai has the experience, expertise, technology, and tools to help you take advantage of everything asynchronous business messaging has to offer.
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