Predictive Analytics: The Ground Zero for Today's B2B Sales and Marketing
Data is imperative for organizations to succeed in today’s business environment. The data generated by sales and marketing houses critical signals regarding the buyer journey, but the data remains underutilized. The organizations must look beyond data extraction and aggregation from their typical ERP, CRM, and marketing automation platforms. Sophisticated sales and marketing tools harness the data that organizations can use to create a central repository and building machine learning models powered by data to have a competitive edge. The organizations who fail to incorporate a predictive element into their customer engagement strategies will fail to take full advantage of the data. Additionally, they will lose the competitive edge.
Fusing all the data in one location and using machine learning to capitalize the data’s potential entirely is still untested waters. In the coming years, organizations are going to use data from additional sources such as sales and marketing systems and third-party sources to gain better correlation and more confidence in the predictions. In predictive analytics, there is no such thing as too much data. Therefore, more data means the organization can quickly identify the right target accounts. The customer journey, the best channel, and the message to reach those target accounts are clearly understood. Feeding correct data to the predictive engine results in reliable predictions.
Expanding into new areas means that the organization has the opportunity to experiment with new technologies, tools, and data sources to determine the moment of influence. Depending on data is the best way for marketers to find a new audience. However, understanding new audience takes historical, firmographic and lookalike data and most marketers often lack in this area because of outdated legacy systems. Predictive engines can form the base of a zoomed-in and highly relevant target account list even with minimal data.
Becoming a data-driven organization demands an upfront investment of time and money. Predictive analytics bring short-term windfalls and also brings valuable results when predictive data becomes a part of the daily workflow. Marketing technology has a quick pace, and while adopting a data-driven strategy, predictive technology and legacy systems should be fused to get smarter predictions. If an organization wants to grow in the market, they have to adopt a data-first approach. To prosper, an organization must embrace the power of data because predictive analytics and data bring novelty to the organization.
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