B2B marketers are facing more resource constraints now than ever before. The latest Gartner CMO Spend and Strategy Survey indicates marketing budgets have fallen to 9.1% of total company revenue this year (from 9.5% in 2022), and more than 70% of CMOs believe they do not have the necessary funds to fully execute their marketing strategies.
AI is the exception: 75% of marketers say they’re spending more on AI initiatives, and with good reason. A 2023 McKinsey study estimates that the economy-wide value generative AI could deliver a potential productivity lift of $463 billion or 10% of marketing spend. But as transformational a technology as generative AI is, there’s an uphill battle in terms of the difficulties marketers today are trying to tackle.
Best-in-class B2B marketing demands hyper-personalized content that fuels always-on campaigns to reach prospects at every stage of the marketing journey. Most marketers never have enough personalized content, and often fail to get the most out of the pillar content they’ve created. They can’t always produce enough creative for rigorous A/B testing, nor do they get to nurture all the leads they produce because it takes a lot of time and effort to set up those multiple touchpoints.
But AI has changed the game, and effective use of generative AI is now table stakes. Leading organizations are already using AI to enhance their offerings; according to Forrester, 67% of B2B organizations are already using AI to enhance customer experience.
Here are 3 things B2B marketers can do more effectively and efficiently with AI right now:
1. Produce unique creative for always-on campaigns
Every brand wants to be visually distinctive, but creating original illustrations can be costly and time-consuming. That’s why 65% of B2B organizations rely on stock images, but the trade-off for this convenience is images that don’t really stand out. Employing generative AI technology to co-create allows graphic designers to create a broader range of unique images with significantly less effort than illustration from scratch. It also serves as a rapid prototyping tool for designers to test different ideas and styles for different audiences. This ultimately means marketers can now provide tailored visual experiences for a variety of buyer personas more efficiently, besides creating unique imagery that stands out from the competition.
2. Enable content personalization for higher engagement
A Forrester study found that 66% of B2B customers expect the same or better personalization in their professional lives as when shopping in their personal lives. Delivering on that expectation can create a real impact on an organization’s bottom line. According to McKinsey, companies with faster growth rates derive 40% more of their revenue from personalization than their slower-growing counterparts. But creating personalized content is slow and laborious…until now. One of generative AI’s primary use cases is as a writing assistant, and many content-driven organizations are already experiencing the significant boost to productivity and output that comes from using AI as a co-pilot. This means marketers can spend less time creating assets and more time curating and crafting unique experiences for their customers.
3. Turn on ‘video everywhere’
Wyzowl’s State of Video Marketing 2023 report indicates that 92% of marketers agree video content gives them great ROI, but 10% find video too expensive, and 30% of people find it too time-consuming to produce. Generative AI democratizes video; a suite of AI tools means teams can produce more videos faster than ever before, without compromising on quality. For instance, developing compelling storyboards and scripts is a crucial first step of your video production process, and generative AI helps transform raw ideas into captivating narratives. Hours of tedious post-production tasks can also be significantly expedited, from creating human-like voiceovers to tackling production quality issues and even enhancing the background of raw footage.
But to maximize the value marketers can get from of this emerging technology, guidance and best practices are essential. Otherwise, AI risks becoming yet another under-utilized component of the MarTech stack.
Here are 3 key steps for marketers to get started and set up for success with AI:
1. Set up an AI council
Having a specialized team dedicated to pioneering the use of AI across your organization will help set internal guidelines for its ethical and effective usage and shape your strategy for applying AI to create a competitive advantage.
2. Be intentional when purchasing AI tools
Before making a purchase, understand and outline the needs of your organization, the expertise you have at hand (and if you require outside experts), and the outcomes you hope to achieve.
3. Invest in training and creating an AI-driven culture
Human-machine partnerships deliver exponential business value, which is why an integrated approach that aligns both tools and people is key. Allocate time and resources to onboard and train employees, helping them see how they can approach their work differently with AI.
As AI use becomes more widespread, B2B companies who are slow to leverage AI technologies to produce business outcomes stand to lose. Some companies have moved on to even more sophisticated AI-driven marketing tactics such as hyper-personalization, and achieved a 10% increase in market share.
Most importantly, think about generative AI as a force multiplier for marketing. While AI can reduce costs and save time, it is only as valuable as how you reinvest those savings. Leveraging AI should lead to more personalized and strategic marketing activity, which drives more conversions, creates tangible impact on key metrics, and leads to real pipeline contribution and growth.
