Netcore Pioneers Agentic Marketing, Redefining Customer Engagement
Autonomous
agent-based, artificial intelligence systems are beginning to replace
traditional campaign-based marketing, marking one of the most consequential
shifts the martech industry has seen in decades. As consumer behaviour
becomes more volatile and fragmented across channels, brands are moving away
from rule-based workflows towards real-time, outcome-driven decision-making.
For years, marketing has relied
on fixed rule-based campaigns, predefined journeys, segmentation, and A/B tests
to reach scale. While effective in a more predictable environment, these
approaches struggle in a world where customer intent can change daily and where
engagement spans multiple channels, including WhatsApp, email, push
notifications, RCS, and in-app messaging. Linear journeys and
one-size-fits-all campaigns increasingly fail to deliver the personalised
outcomes consumers today expect, at the very least.
To meet these changing consumer expectations, leading martech
vendors today have been really quick at adopting agentic
marketing systems: autonomous AI agents that decide how and
when to engage each customer. Rather than optimising for activity metrics such
as opens or clicks, these agentic marketing systems are designed to maximise
measurable business outcomes, such as revenue, retention, and customer lifetime
value (CLTV), which are the leading metrics that brands value the most.
Under agentic marketing models,
execution is no longer driven by predefined workflows. Consumers move fluidly
across channels, devices, and moments that rarely follow a linear path. Their
behaviour and intent fluctuate rapidly, shaped by factors such as pricing
sensitivity, inventory availability, timing, and competitive offers, many of
which lie outside a brand's immediate visibility.
Autonomous agents continuously learn from these signals, adjusting
message, channel, timing, and frequency without human intervention. Instead of
asking, "Which journey should this customer enter?", the
system evaluates a more precise question: "What is the next best
action for this customer right now, based on their past behaviour and
preferences and if any?"
Industry analysts describe this as a shift from campaign planning
to autonomous decisioning,
where each interaction is treated as a unique moment rather than a step in a
fixed flow. Crucially, these systems can also decide on restraint, pausing or
stopping outreach when engagement would create friction instead of value. For
marketing leaders, this means faster responses to changing signals and less
wasted budget on poorly targeted communication.
Leave A Comment