![]() For example, AI-assisted content generation tools can generate blog posts and articles faster than most human writers and designers can produce. The resulting structured data is then converted into an industry-standard format that marketers can import into their marketing automation software or CRM system.ĪI tools can help B2Bs with content creation in several ways-but the big sell for most marketing teams is increasing the volume of content created. Leadspace: Leadspace uses natural language processing (NLP) to parse structured data from web pages.Salesforce Einstein: Using artificial intelligence and machine learning, Einstein helps sales teams find their next best opportunity.Zapier: This service allows users to set up zaps, or automated workflows, between apps and services like Google Sheets and Slack.Some of these tools can even be used in conjunction with CRM systems and help generate leads based on information stored within the system. For B2Bs, generating leads can be even harder due to their complex (and often extended) sales cycles.ĪI tools can help you keep on top of lead generation and sales conversion by easily streamlining data, helping salespeople manage prospects throughout the funnel, and showing marketing and sales teams which leads are the most qualified. With so much data readily available, it’s easy for marketers to get overwhelmed and make costly mistakes. 7 Types of AI Tools for Every B2B Lead Generation A company’s marketing tech stack is as unique as its customers and goals. The stack can include some or all of the following: CRM, analytics, email marketing, social media management, web design tools, and more. What is a Marketing Tech Stack?Ī marketing tech (martech) stack is a business’s set of software tools that marketers use to organize and execute marketing processes. So let’s take a look at the different categories of AI available now and how B2Bs can dip their toe in with some interesting tools. Every business can leverage some form of machine learning to give leaders insights and boost its marketing performance. Machine learning for finance has become increasingly popular, with companies using it to analyze vast amounts of data, detect patterns, and gain valuable insights that can help them make informed decisions and optimize their operations. There are a plethora of tools available today that provide some sort of artificial intelligence capability to help you create, curate, automate, optimize, personalize, and more. AI in Marketing: Breaking Down the Pros and Cons.AI in B2B Marketing: Where Human Intelligence Meets Martech Intelligence.This is especially true for marketers-who are finding ways to use AI in creative marketing endeavors as well as data analysis-with both consumers and businesses reaping the benefits. AI has come a long way since those early days, and every industry seems to have no AI and machine learning tools to optimize and improve business processes. ![]() We can thank IBM’s Watson and Apple’s Siri for popularizing artificial intelligence (AI) and giving us access to technology that used to be reserved only for the mind’s science fiction writers. ![]()
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