Toward the end of last year, I was a guest on one of Paul Greenberg’s and Brent Leary’s shows on their new streaming network, PPN. There’s a lot of CRM content there, naturally, and I am always amazed at how they can coax executives from competing vendors to discuss big ideas and be nice to each other.
That was not always the case. I recall a dust-up between a startup CEO and one of the big CRM players on stage about 10 years ago. The CEO’s talents seemed a better fit for the political arena to which he decamped eventually. But I digress.
The importance of Paul and Brent’s show for this piece was something I mentioned and later mentioned here regarding AI and, in a larger sense, markets in general. I believe 2024 will be a year of consolidation in things related to AI because it is much easier to claim a territory than it is to settle it, and I think that’s where we are.
As it applies to CRM and AI, I truly believe we need to see some runs on the scoreboard, not simply base hits. By this, I mean we need to see some AI solutions running from vendor to customer to, ideally, money in the bank.
That’s not easy to do because money in the bank is a lagging indicator, and some CRM applications aren’t oriented that way. A case in point is customer service, where a vendor might not see an unambiguous monetary signal from implementing AI in customer service for quite a while.
Measuring AI Success
Maybe the best early indicator of AI success in customer service would be reduced customer attrition or improved retention as measured by customer renewals. The problem is not many vendors want to share their before pictures with the world — and you can’t blame them.
However, applying AI to customer service as a test case does have some advantages. Customers are different from sales prospects. A prospect can ghost you, but a customer has a need to make things work both product-wise and throughout the relationship.
Customers will give you the benefit of the doubt if they see that you are sincerely working on their behalf. That makes customer service a good target for a vendor trying to integrate AI into its CRM suite.
Right now, Salesforce looks like the vendor implementing a customer-service-first approach. It’s important to note that the company is working busily to apply AI to the rest of its suite, too. But in my experience with Salesforce, it seems the push is rising first in service. This perception that service is taking precedence could also be a mirage, which I am certainly susceptible to like anyone, but let’s assume not.
Salesforce, Apple Partnership
Interestingly, Salesforce is working with others to achieve its vision of AI-assisted service and thinking outside the box for the right application circumstances. In December, Apple and Salesforce announced a partnership to deliver AI service assistance through messaging, which makes a lot of sense.
The act of providing service has traversed an interesting path in the last 20 years or so. We’re way past the old break-fix model, though, of course, you can still do that. But as the Apple relationship shows, service is becoming more about getting into the little crevasses between break and fix.
Salesforce’s recent press release notes more than 2 billion Apple devices in the market, and the customer-preferred medium of interchange is messaging, including text, chat, and email among consumers 18 to 34 years old. That’s a big slice of the market; as it goes, so goes the future of service.
Two things stand out. First, Apple Messages uses Service Cloud to give customers connectivity with customer support; they can also get personalized shopping recommendations, schedule appointments, make purchases, and track deliveries — just as you’d expect with messaging.
That’s a new take on the service or support paradigm, and you might say just in time. A company as big as Apple, with over half the U.S. population using iPhones, needs the scale a solution like this provides, and the target demographic wants a support paradigm as frictionless as possible. Apple Messages for Service Cloud hits that saddle point.
ARKit for Field Service and Sales
I think of Apple Messages for Service Cloud as a micro-macro solution that has a micro footprint for a macro market. Apple’s ARKit seems to be a macro-micro solution.
Field technicians can use ARKit to create 3D renderings of large areas and map objects from simple images. Most customers won’t need this, but it is a fantastic timesaver for field service people or those planning big installations.
A moment ago, I was lamenting how slow service apps can be at putting money in the bank, but here, I think we can see that these apps don’t simply take service up a notch; they have the ability to bring elements of service into the sales process.
For instance, if you are selling an installation of some sort, Apple’s ARKit embedded in Salesforce Field Service and Sales Cloud can do a lot to sharpen the proverbial pencil during the proposal process.
Salesforce’s Strategic Growth
The significant benefits of this type of integration are what I mean when I say it takes more to settle than claim territory. It’s not simply about speeding up existing processes.
With AI-driven customer service, Salesforce is developing new service niches and, by doing that, abstracting itself from direct competition with vendors of traditional service process support.
Throughout its history, Salesforce has had terrific growth — in part due to this tactic of being first by inventing a niche or at least being early in a niche. Settling a territory may not be as sexy as claiming it, but depending on how you see it, it doesn’t have to be boring.