Sales companies are under increased pressure to reduce selling expenses while stabilizing margins and completing only the most profitable sales. Marketing departments in all sectors are under increased pressure to maximize the number, efficiency, and performance rate of leads that are most likely to close this year. AI-based pricing and revenue management applications and systems are proving invaluable in keeping revenues, marketing, operations, services, accounting, and senior management connected with real-time alerts to achieve more. The ten ways AI is revolutionizing revenue today are as follows:
- 40% of Marketing & Sales divisions using AI platforms & apps attain 6 percent or higher average revenue growth: AI makes the most of its contributions and lowers prices. The majority of executives whose businesses have implemented AI claim that AI has hugely contributed to provide an increase in revenue in the industry areas where it is used and 44 percent state that AI has lowered costs. Marketing & Sales are the strong winners of revolutionizing how they produce money through AI.
- AI’s biggest sales contributions this year are enhancing the accurateness, scale, and speed of price optimization: Sales VPs, Chief Revenue Officers (CROs) and CEOs say that embracing AI-based pricing management is one of the best choices they have taken before and after the pandemic to secure margins and avoid getting into price wars. AI-powered price optimization improves business feasibility, drives more revenue and profit growth and has proven cost-effective in resolving problems. AI-based pricing and marketing can generate between $259.1B and $500B in global market valuation, according to McKinsey. Leaders in this field include Vendavo, which has years of experience offering price optimization solutions for the chemical, distribution, high tech, manufacturing, and after-market industries.
- AI-based lead scores have a major effect on automating lead qualifications: Each CMO and its counterpart in the CRO are discussing how to improve the rate of opportunities for the transitions from Marketing Qualified Lead (MQL) to Sales Qualified Lead (SQL). Pre-pandemic lead weighting for many B2B businesses is not working since one of the most important sources of leads, events, is no longer accessible. AI helps to align the residual sources of lead production with the updated eligible requirements.
- Using AI-based cross-selling and upselling to increase trade win rates in their aftermarkets, manufacturers are growing their penetration applications that operate smoothly with their CRM systems. Salesforce Einstein is gaining recognition in manufacturing as more CROs turn to their aftermarkets for more margin and sales increases as new agreements have declined this year. B2B-based suppliers who have years of consumer data in their Salesforce CRM programs claim that Einstein will qualify current customers as leads in seconds – saving in sales weeks and getting closer to after-sales revenues.
- AI-based Demand Generation is affecting revenues by supporting Marketers with the daunting challenge of creating new leads and understanding their inclination to purchase in real-time. CMOS is implementing AI-based Demand Generation applications and networks to help organize and incorporate marketing campaigns that produce more MQLs with a higher tendency to become SQLs. Knowing why approval and rejection rates are occurring in a given campaign, the effect of marketing techniques on lead development, and how the time spent at each level of certification affects close rates. AI-based demand generation is also offering new insights into the relation of marketing to revenue and marketing-driven sales pipelines.
- Using AI to enhance Customer Lifetime Value (CLV) is becoming popular, making it a key measure in marketing and sales efficiency. Using AI to identify what influences often impact and hinder CLV is supplying sales and marketing teams with the expertise they need to fine-tune mutual prospecting and sales strategies.
