With the rise of artificial intelligence (AI), traditional marketing is wading into troubled waters – and you don’t need a data scientist to feel a major shift coming. We keep pounding consumers with messaging, as we’ve done for years – campaigns and segments, retargeting, real-time media buys, mobile push messages, personalized email – all the time knowing that the average campaign response rate is less than 1 percent. That means on average, 99 percent of the messages we send are basically irrelevant.
As marketers, we’re in a tough spot: Our programs are less impactful, and at the same time we’re getting pressure from new competition. Adjacent companies are moving sideways and vying for our space in the market, and it’s adapt or perish, so we constantly look to do more, talk more, and engage in more places. But, the math doesn’t lie - we just end up with lower response rates, as a result.
Relevance and timing are critically important to modern marketing, and traditional push campaigns can’t meet the timing needs of a connected customer.
In traditional campaigns, you’re pushing messages out on your timeframe, not the customer’s. But in real life, your customer’s context is constantly changing. With all the planning cycles and lag involved in executing a large campaign, there’s only a small chance that you’ll hit the right window of opportunity to capture an individual customer’s attention – let’s say a 1 percent chance – so the other 99 percent of what you pushed out gets ignored. You can’t wait days, weeks, or even months to fill a customer’s needs once you know about them – consumers are driven by instant gratification, and opportunities disappear in hours or minutes, rather than days or weeks. If you can’t adapt your messaging almost instantly, they’ll seek out service from a competitor that “doesn’t make everything so hard.”
Think about it. Aside from all the effort involved in creating a complex campaign (and that’s a significant amount of research and planning), why are you batching everything up and waiting for specific time slots to launch all that activity?
We need full control over every message, on every channel - in real time, every time.
We know how small the window of opportunity is… wouldn’t it be smarter and more profitable to align what we’re saying with what the customer actually needs in that moment? Wouldn’t it provide a better experience if what we said was actually relevant for them, right now? Or if we avoided talking when they’re weren’t ready to listen? Instead of investing 90 percent of our time building megalithic campaigns to expose a new offer (“Look at what I want to sell!”), wouldn’t it be far more effective to simply activate that offer and let the AI/ decision engine read the coverage – and figure out when it’s relevant to present for any customer and context across any channel?
Let’s really consider this for a minute – we know that our campaigns are so poorly accepted, that they’re going to interrupt, distract, and maybe even irritate our customers to the point where we actually have to set company rules so we don’t spam the customer right back into the 19th century. Is that the best we can really do? Is that how the modern marketer is going to define success?
We need to move from scheduled push campaigns, to an always-on model that continuously engages customers during their “moments of need.”
With always-on, one-to-one marketing, you don’t have to wait for campaign execution to reach out. If it’s relevant and profitable to engage with a customer about an offer or any other potential action, and it’s the recommended next best action, simply send a personalized outbound message when it’s appropriate. Next-best-action (NBA) is an approach that targets individual customers, rather than segments – their unique needs, preferences, and context. It works to make every interaction relevant and meaningful, connecting your customer’s conversations regardless of channel.
We need a single decision authority that helps keeps our conversations connected.
The key to an effective always-on, one-to-one approach is having one central decisioning component that analyzes the customer’s history and current context, then applies predictive and adaptive analytics to suggest the next best action. This architecture makes it possible to constantly read the environment, re-assess, and trigger new types of engagement – and is always aware of new information or context clues from the customer, because it is actually always on. This keeps the conversation relevant, allowing you to make decisions in the moment that are best for the customer and your KPIs.
We need to realize that companies are already doing this – and getting massive returns on investment.
For example, EE, the UK’s largest digital communications company has quadrupled accepted offers thanks to this one-to-one customer engagement approach. By leveraging big data and using real-time context to improve customer engagement in every channel, EE is able to move beyond mass-segmentation to completely personalized customer journeys that are driving very significant business returns.
ABOUT THE AUTHOR: Matthew Nolan is a marketing director at Pegasystems, enabling the vision and go-to-market strategy for Pega’s marketing and advertising technology portfolio. Before joining Pega, Matt was General Manager of the National Data Cooperative at Target Analytics, and served as Director of Modeling, Analytics & Data Services for Blackbaud, Inc. He is a regular keynote speaker who shares his professional insights on more than 17 years of marketing technology experience.