Have you ever been talked out of your tools? Has someone ever cast doubt on your marketing ideas? A cunning plan of many marketers is to say nothing of the past works and everything is new. While that is a partial truth they use a plan as unpredictable as evolutionary theory; where random events in market history suddenly change the game to something it has never been. This is the story of Babyl. The mantra is a never ending cry for more work, higher and higher tiers of influence and a never ending path ahead.
Today I tell you, TRUST in what works. Trust in the tools; but remaster what you have, not to eliminate what has worked, but to take advantage of innovative ways to increase predictability and narrow the gap on what has been and where you can actually arrive with IT Inheritance.
Now today our IT Inheritance includes big data; a disruptor on the scene not to dismantle your marketing efforts but to increase predictability. With an ear in the prayer closet for single insight into key objectives; we then drill deep into current and future data models of existing internet behavior by users in route for REAL TIME optins to your social outreach.
This real time advantage couples the idea that two people are not alike in their behavior. An audience with these 2 people could easily be an audience of 2M of like behaviors. When selecting these key word advantages in social targeting, your total Cost Per Click could be much higher, because you are targeting an extra million of people who may not have a click through behavior. Real time advantage is more predictable in that, with precise data mining one can narrow the 2M person audience, down to 1M in buyer behaviors or people willing to stop by your physical location. This cuts Cost Per Click almost in half and saves you precious ad spend.
Now drilling down the behaviors that are in the buying mode could mean a difference between those who shop for future opt ins verses those who are real time actors. We are getting more acurate. Let's continue!
Now you have a market plan to indeed discuss the fuller picture with user behavior models. Let's consider the next step. . .