The effectiveness of their marketing campaigns, their marketing initiatives have also witnessed a shift from being outbound focused to both outbound and inbound focused. The proliferation and adoption of digital channels, rise of social media and ecommerce, upsurge in the adoption of mobile, wearable’s and other devices have contributed to an even greater explosion of data.
While this looks like the advent of happy days for marketers, they are, at the same time, faced with the challenge of dealing with this huge volume of both structured and unstructured data and design marketing initiatives based on events and triggers that are generated real time. The B2B Predictive Analytics Technology Report forecasted, 36.8% of high-growth companies planned to invest in predictive analytics initiatives to drive successful marketing and sales initiatives in 2016 alone.
Having a stable, robust and flexible predictive analytics model in place can help marketers achieve the following benefits.
The more we know about our buyers, the better we can plan our marketing initiatives. Since a marketing database does not contain all the information that we need to deeply understand our customers, coupling predictive analytics with customer data helps us uncover the right patterns to design optimized experiences for our customers.
With so many data sources how do you profile your customers? Predictive analytics helps in mapping customer journeys and identifies how the customers respond to marketing initiatives.
The time investment to acquire a new customer is a great deal higher than to retain existing ones. By employing predictive analytics models, marketers can recognize customers who display an attrition risk and the reason behind the same.
Since predictive analytics looks for micro patterns in data, the right data, when fed into the system, can reveal what best offer should be sent to a prospect. Predictive analytics helps marketers drive personalized campaigns which are more impactful and measurable.
With predictive analytics, marketers can gauge the customer’s propensity to buy with greater accuracy. The predictive analytics model can analyse customer data to make these projections and thereby help marketing teams pass on high quality leads to the sales teams.
Predictive analytics also help in identifying new trends and growth opportunities. It gives marketers insights into industry pain points and new trends that are brewing and gives them the opportunity to tweak and model their product or service to suit the customer’s requirement.
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