Marketers have moved beyond the carpet bombing approach that typified early practice in digital channels and now typically focus on customer experience in a targeted way. But the myriad of technology used to deliver it is still causing headaches and some of it at the bleeding edge is threatening to send marketing backwards, according to Matthew Nolan, Director of Product Marketing at Pegasystems.
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Speaking with Which-50 at the Pegasystems user conference in Las Vegas this week, Nolan argued artificial intelligence could help reduce some of the marketing complexity. But without “guide rails” it risks sending digital marketing back to its spray and pray roots.
“For years I did the push [marketing] stuff and I thought there’s no way this is ever going to change. We all knew it was broken we were all embarrassed about our jobs. Then you started to see it shift. People just aren’t sure how to get there yet but you can see that they want to.”
Organisations have woken up to the fact that bombarding consumers is not only ineffective it potentially damages the brand, Nolan said. It means organisations are “reshaping” themselves around customer outcomes, giving more stock to retention, nurturing and loyalty measures. But with limited customer “mindshare” these messages often come at the expense of traditional sales offers, which means not all stakeholders are happy.
“It’s hard. Especially if you’ve got teams that were built around this for 20 years.”
It is a positive trend overall, Nolan says, notwithstanding the complex challenges of a burgeoning martech market and convoluted internal stacks.
“If you go into a big bank, they’ll have 30 different pieces of the martech stack and if you start to look at operationally in customer service, other places, it gets much bigger.”
“How do you keep all that stuff connected and actually make it an experience something that [a customer] desires? Or at least doesn’t hate.”
The rapid evolution of artificial intelligence could provide martech solutions and help with the evolution of marketing, making advanced messaging decisions in real time. But it could also be used bluntly to deliver more messages at a creepier level. That outcome is an “absolute certainty” if AI isn’t controlled, Nolan said.
Proponents of the AI argue marketers could use the technology to analyse and generate customer insights, then deploy them at scale with one-to-one personalisation. The key to achieving that outcome, Nolan says, will be self-control and not necessarily taking advantage of the scale opportunities AI presents.
“Just because you have the opportunity to talk to someone doesn’t mean you have to pitch them something … If it’s an 0.002 per cent chance [of a customer accepting] why are you putting it in front of them? You’re just wasting mindshare.
“And I think that’s where the AI needs guide rails to actually say what’s the best practice for this?”
Pegasystems already uses an AI engine to power it’s marketing and process automation products. Using AI in that decisioning role to assist humans is where the early value of is but more advanced marketing use cases for AI, where the technology is making sophisticated decisions, aren’t yet common, Nolan said.
“We tend to look at it more like are they actually trying to balance what the customer needs versus what the business needs in real time? That’s, AI. That’s where the rubber meets the road. What’s good for you? What’s good for us? Let’s come up with a compromise. Very few folks are doing it, I’d say less than 10 per cent.”