Times ahead for “Marketing to Things”
In a connected world where things are linked to other things and people, there are multiple touchpoints to manage. To a marketer, this means – they have to manage these touchpoints, which are invariably expected to increase in the days to come.
With the way AI is proliferating, it is time for us to rethink who our customer is!
Is it going to be human selling to other human by creating better experiences with hyper-personalization, contextual messaging and more? Or are we going to see a mix of selling to human as well as to machines?
MARKETING TO THINGS
The fundamental pain-point for marketing professionals today is the overload of messages reaching the targeted prospect. It thus becomes increasingly difficult to break through the clutter.
Though the martech landscape today comprises AI tools to help you break the clutterby identifying signals indicating prospect’s intent and fit to your products & services, the key question is how much are we leveraging it?
How about directly marketing to machines such as your CRM, ERP than the people championing it?
Empowering machines with AI will make them consume the marketed information, compare the information across its signal library and make an informed decision in minutes.
AI + Connected world: Increase in marketing opportunities
Once AI begins to balance factors for decision making, the ultimate opportunity for marketers and data science experts would be to understand the algorithms used to calculate & compare and then offer bundles or pitches that suit the machine. Thus, the most basic qualification of AI vendors enabling marketers, would be the ability to crack the intent data.
Here are a few key factors for us to address:
- Data accessibility and integration: The quality of output is directly proportional to the quality of input. Make sure that data is integrated across internal & external touch points and is consolidated in a centralized data lake.
- Data enrichment: Sanctity of data is paramount, especially with customer data. With data decay being a natural phenomenon, data enrichment needs to be a continuous exercise.
- Need for closed loop learning: In a new environment such as this, with such heterogenous data, results cannot be 90% and above from Day One. AI algorithms need closed loop learning, specially to accelerate and be effective at the fascinating intersection of technology and humanity.
It’s not the fittest that survives, but the most adaptive.
Ones that create and adapt their models to changing conditions, yet ensuring sanctity of data, will have the upper hand.
Evaluate AI vendors and their capabilities based on their adaptability. Check if they enable and simplify your life as a Marketer. Ensure they integrate with your existing ecosystem, thus being able to leverage the existing data.
Maybe, it’s time to have a Chief AI Officer!
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