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‘The Power of Now’ was one of the most favorite sayings of my first manager. A simple one but effective enough that you should know & adopt. It was social media marketing then…but now the crown has passed on to Artificial intelligence. Artificial Intelligence which once was part of science fiction novels is now a reality & is influencing the business world in the most amazing ways.
“bright glimmers of intelligence that is advanced enough for enterprises to exploit now.”
B2B enterprises around the world are implementing Artificial intelligence for accelerating their growth & revenues in the past 10 years. In fact, B2B professionals believe that Artificial intelligence will revolutionize the field by the year 2020.
At glance you may not notice hoe artificial intelligence plays the part in lead generation processes but by diving a little deeper you’ll see that artificial intelligence can aid amazingly in identifying more leads. Artificial intelligence makes it easier in filtering the massive databases & discovering the leads that are most relevant. Majority AI lead-generation platforms allows marketers to set specific parameters.
It’s a sad fact that salespeople spend too much of their time on monotonous tasks such as cold-calling, responding to emails etc. As stated by McKinsey Global Institute, artificial intelligence can automate 40% of the time spent on these menial tasks by embedding into CRM databases, Salesforce automation software & other B2B applications.
Artificial intelligence & data quality
Precise data is crucial for all sales & marketing functions. But marketing data decays 30% every year due to multiple reasons in addition to simple errors, bias, and duplications. As automation software becomes machine learning & when it starts to feed on artificial intelligence, inaccuracy & errors move downstream & infect entire decision crafting systems.
Artificial intelligence & data quantity
It’s very much crucial to gather robust amounts of data for sales & marketing systems because if datasets are too small, irregularities and differences can appear which can lead to incorrect conclusions. The success of artificial intelligence & machine learning platforms is entirely dependent on both the quality & quantity of the datasets being used to train them.
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