The Role of Predictive Analytics in ABM: Key Benefits

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The Role of Predictive Analytics in ABM

• By SalesMark Global

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Introduction

• In a world where the fast pace of business is
  something of a mantra and data is amassing at a
  phenomenal rate, it is smart data strategies that
  enable organizations to stay ahead of the curve.
• ABM (Account-Based Marketing) has gained a lot of
  popularity and is often referred to as a
  breakthrough in the marketing field, allowing the
  companies to target high-value accounts by using
  highly accurate data.
• However, blending the accuracy of predictive
  analytics in ABM empowers organizations to
  achieve levels of excellence they were unaware of
  when addressing future business challenges.

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Fundamental predictive analysis

• 1. Data Collection For the predictive model,
  data will be used as a source of inputs including
  firmographics, online behavior, and historical
  interactions assessed out of the target accounts.
  Thus, this data is the ground on which the
  predictive models are built on.
• 2. Predictive Modeling These models take
  historical data and extrapolate it into
  projections of future outcomes. The most
  important task in ABM is account identification
  where marketers determine which accounts have the
  best conversion or package accordingly.
• 3. Scoring and Ranking Predictive analysis
  grades accounts and ascribes them scores or
  ranks, hence affordin to marketers the option of
  allocating their efforts on the chances of
  success.

• 4. Machine Learning Machine learning has its
  cornerstone in predictive analysis through which
  models are made to adapt and improve their
  functioning with a time passing which utilizes
  more data to program the models more precise
  which improves predictions.
• 5. Feedback Loop This area of analysis is a
  superstar. It needs the feedback! Marketing team
  has to check forecasting vicinity to improve the
  segmentation methods.

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How Predictive Analysis Enhances ABM Initiatives

• 1. Identifying High-Value Accounts By finding
  out data, predictive analysis helps to point out
  which accounts are the most likely to bring
  conversion. This narrows the candidate list to
  the ones with high probability of success and
  helps in concentrating marketing resources on the
  most promising prospects.
• 2. Personalization Persuasive analytics provides
  the foundation for tailored marketing content and
  messages, that become personified, to reach each
  account individually, exactly as it needs and
  exactly as it behaves.
• 3. Lead Scoring With the help of predictive
  models, you can do the lead scoring directly
  within the accounts, so in result, the sales team
  will be better focused and have more engaging
  interactions.

• 4. Optimizing Resource Allocation The clue is
  that the company understands what accounts more
  probably will experience conversion and may
  ration resources effectively so that the money
  invested on marketing and sales get the very
  highest rate ROI.
• 5. Sales and Marketing Alignment Predictive
  analysis helps the sales and marketing
  departments to move in lockstep through
  alignment. Both these units operate together
  fostering them to focus joint efforts on
  opportunities with high conversion probability.
• 6. Continuous Improvement As the models become
  predictive and new data is fed into them, the
  accuracy and effectiveness of the ABM strategy
  roll-on for Brand improves over time.

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• SALESMARK GLOBAL

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• https//salesmarkglobal.com/

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