Introduction
The Effects of Big Data on the B2B Marketing Landscape
Big Data and ABM Strategy Go Hand in Hand
Conclusion
Introduction
Big data analytics in B2B marketing can help generate unparalleled insights such as client behavior, purchasing trends, inventory management, and the overall supply chain. However, this method of collecting, processing, storing, and preparing large data sets for B2B marketing organizations can take time to understand the data management tools. Big data analytics in the B2B marketing field lets marketers and sales professionals gather large volumes of data from different or siloed sources and further conduct data analysis through business intelligence (BI) platforms to get valuable insights into their daily operations. This eventually helps identify patterns and movements in data, aiding marketers and sales professionals to enhance decision-making and optimization, and being a problem-solver in your enterprise during a crisis.
A case study found that B2B companies using big data analytics have witnessed a speed increase in their first sales by 50% and churn reduced by 25%. There were also instances of new accounts for sales professionals and a 2-4% return on sales through pricing.
Therefore, in today’s exclusive MarTech Cube article, we will focus on the importance of big data in the B2B marketing realm, as we are focusing on digitization in the 21st century.
The Effects of Big Data on the B2B Marketing Landscape
The ultimate goal of creating an effective big data B2B marketing and sales ecosystem is to open the doors for opportunities to cross-sell clients by gaining knowledge about the customers and potential clients and offering products and services that meet their needs. Being a savior, big data tools will help sales professionals gain massive amounts of data and quickly process vital information to rework sales and marketing strategies if needed. For instance, the marketing and sales team can review previously closed deals in specific campaigns and use this information to identify new lead-generation opportunities. You can find multiple BI platforms, such as Tableau or Looker, that have inbuilt big data technology that will help you provide insights into the lead generation process, which can further help you analyze metrics such as cost per lead, qualified lead volume, and sales volume.
The big data tools can further break down successful sales attempts on a basic level to uncover which advertisements, channels, and landing pages work best. Another benefit of big data analytics in the B2B marketing sector is creating a better customer experience, especially in tracking metrics such as customer satisfaction (CSAT), customer lifetime value (CLV), retention rate, and churn rate. This information can be further utilized in optimizing communication and engagement with business stakeholders and customized products and services. B2B businesses also use big data analytics techniques such as predictive analytics to forecast future results and prepare marketers for any events that might impact the business goals.
Big Data and ABM Strategy Go Hand in Hand
Account-based marketing (ABM) is considered a robust marketing strategy that concentrates resources to set target accounts within the B2B market, and big data is known to identify high-value accounts and allow more personalized marketing campaigns. Therefore, ABM is treating every account as a separate market, making it more manageable and causing a shift from the traditional MQL strategies for creating more precise, accurate, quality data that identifies paramount accounts and makes targeting easier. According to Salesforce’s State of Marketing, 70% of marketers use some form of ABM, yet 45% struggle to deliver a personalized experience; therefore, they use marketing tools such as 6sense and Demandbase, which are developed for accelerating ABM strategies. Hence, marketing and sales teams need to closely work together to successfully align good ABM strategies and target accounts with your ideal customer.
Conclusion
Every organization has its own set of challenges and opportunities that can only be executed with proper technology, such as big data, that will eventually aid in reaping benefits regardless of size. The only solution is to generate high-quality data that drives better decision-making and determines factors that will eventually impact everything in the future.
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