The current marketing technology landscape is growing fast and now includes more than 3,700 marketing technology providers; that total has doubled in the past year. This tech glut has muddied the waters for buyers, as unproven startups or market cross-overs toss their hats into the ring with existing enterprise providers. With everyone touting a message that sounds and feels similar, it’s difficult to get a read on what’s real and where the value is. As vendors create new software to meet demand, they spend less time integrating that software back into the stack, so every new piece of tech tends to make things more complicated, and harder to monetize.
Marketers need to get their mojo back. They need to feel empowered. They need to regain control, and they need technology that actually makes it easier for them to do their jobs. The following are the mission-critical capabilities that will help do that; if these aren’t part of a deal, marketing decision-makers should move along and find what they need elsewhere:
A central source of customer intelligence
This was considered marketing speak just 10 years ago, but it’s actually very achievable today. Marketers leverage tons of customer data — everything from transactions and social handles, to mobile device signals and web interaction history. That data fuels their programs, but to make the most out of it, they need one place to collect, link, and store that data; one method to access it when they need it (as fast as real-time); and one place to manage the customer strategies that act upon it. This is often referred to as a Customer Decision Hub — it becomes the organization’s customer brain, governing all of their customer interactions across marketing, sales, and service channels.
This hub technology is now available and in heavy use today at huge scale. For example, organizations like Sprint, the Royal Bank of Scotland, and British Gas — each with tens of millions of customers that interact with them billions of total times each year — are using a decision hub to personalize and orchestrate all of their customer experiences across channels. They want to ensure that every customer interaction is the best interaction possible — both for their customer and for their business.
Purpose-fit analytics —built into the software
Analytics used to be an offline activity, performed exclusively by statisticians. But as people came to realize the value of it and wanted to increase the number of “things” they predicted — including journey stages, channel responses, product interests, content selections, and churn scores — they realized it couldn’t scale to meet demand. There simply weren’t enough resources to make that happen. But today’s marketing technology has automated the process to make it simple and quick to action the results. A good solution must be able to produce analytics in real time that score for purchase propensity, customer churn and customer lifetime value, and then combine those to determine the appropriate next-best action for each customer and each interaction. That action isn’t always an offer. Sometimes it’s a retention plan, a service action or filtering out offers based on someone’s finances or credit. But in the end, it balances the needs of the customer against the objectives of the business.
Machine learning — analytics that adapt with the customer
Artificial intelligence is a hot topic with a million potential use cases, but in the short term, it takes the form of self-learning software that progressively gets smarter and makes better decisions. The common use-case is for the system to reassess its own algorithms (predictive models) on a regular basis as it collects data, then rebuild those algorithms using the intelligence collected. It becomes simple to spin up or scale predictive analytics in a system like this — the marketer identifies what they want to predict, the system gathers the data and handles each decision from there. This takes a significant burden off of the marketing team, as the fundamental activities of data prep and model building become something that the software simply handles so they don’t have to allocate people to do it.
Journey management — orchestrating and optimizing the customer journey
Journey management is another hot topic, with as many approaches as there are practitioners. The current trend is for businesses to focus on optimizing micro-journeys — identifying and mapping out problematic or high-value customer scenarios, then using the software capabilities to improve them with the
goal of building the most seamless experience possible for the customer.
In a journey context, the software must enable the marketer to:
• Define journey conditions so they can be tracked, including customer entry and exit criteria, and what the assumed end-goal of the journey is.
• Visualize common purchase paths by graphing and displaying the interactions that happen most commonly in each stage — usually channel touches and offer responses.
• Attribute customer interactions with value by using analytics to show the relationship between a marketing touch and success, such as a customer purchase or move to a new stage.
• Orchestrate customer interactions, across channels by using next-best action analytics to surface your message appropriately via the best combination of channel, offer and treatment — exactly when it’s needed, sometimes in more than one channel at a time. The system must constantly learn from the data it collects so each subsequent interaction will be more informed than the last.
The capabilities above are only a starting point, but will allow the marketer to act more efficiently and become more agile and responsive. New techniques such as guided strategy building and advanced AI are right around the corner. But for now, a strategic combination of smarter analytics, system integration, process automation and simplification of the user experience will put marketers firmly back in the driver’s seat.
Matt Nolan is director of product marketing at Pegasystems, which develops strategic applications for sales, marketing, service and operations that streamline critical business operations, connect enterprises to their customers seamlessly in real-time across channels, and adapt to meet rapidly changing requirements.
