Account Based Marketing (ABM) is human capital intensive, so generative AI is an exciting new enabling technology. As Marketing teams embrace Generative AI, they need a ChatGPT Account Based Marketing Playbook to be successful. One thing is clear: Generative AI will impact every aspect of ABM programs. The ChatGPT Account Based Marketing playbook below outlines AI areas that get your ABM programs started quickly and run more effectively by leveraging AI technologies.
While AI will save human resource cost, your ChatGPT AI ABM Playbook success must be measured on new and expansion revenue. Justifying marketing based on the value of work saved will limit your ability to invest. ChatGPT will open new opportunities that may also cause more spend. When you measure success on revenue generated and ROI, investment opportunities and testing become obvious decisions.
AI MarTech Stack
Steven Moody developed this brilliant illustration of AI’s impact on Marketing Technology. He’s right! AI will impact every aspect of MarTech and create new capabilities within marketing products. Some of those will be good, and others won’t work as expected.
Some legacy technology vendors will “check the box” saying they have AI, but when you scratch the surface, there won’t be a lot of value. New vendors and products will arrive that offer streamlined tools and expand your marketing reach in meaningful ways. For ABM, the early work will streamline areas like content, personalization, and engagement. Tool selections will evaluate this capability, and vendors who integrate valuable AI features fastest will win market share in 2023 and beyond.
For each area in the playbook below, I shared how to use ChatGPT to get immediate value in your ABM approach. ABM specific tools will automate and integrate AI into ABM, replacing the generic ChatGPT approach. Here’s a roundup of the latest AI-powered marketing technologies from Martech.org. Consider this growing list of enabling technologies as replacements for the ChatGPT references in the playbook.
Create your ABM Strategy without AI assistance
Your ABM strategy matches your corporate strategy. That won’t come from ChatGPT. ABM Strategy starts with conversations between sales and marketing leaders. A well developed Go-To-Market strategy combines growth in new account revenue and expansion revenue from existing accounts. The balance depends on your product, customer base, and sales success. If you have a strong customer base and valuable features that users adopt over time, focus your ABM strategy on existing customer expansion. If you’re growing your base to create future opportunities, focus on new business. Driving retention starts with each new customer, so it should be an early focus regardless of the new and existing ABM program balance.
Once the Go-To-Market Strategy is established, ABM strategy becomes obvious. Marketing approach to new vs. existing, large vs. small, and industries is informed Product and Sales strategic direction. Marketing must be willing to adjust as those strategies evolve. Customer conversations and feedback will show problems to solve and use cases to focus on. Those strategic insights are the starting point for program objectives and will drive goals, content, campaigns, account lists, and messaging. Marketing can structure the ABM strategy conversation, but relying on ChatGPT will cause your ABM program to fail.
AI Enablement for Competitive Market Analysis
Understanding competitive market size and composition will focus Go-To-Market Strategies on the right industry, buying teams, and messages. Unlike ABM Strategy, generative AI will provide a headstart in understanding your market, and streamline market definition and research activities. Competitive Market Analysis projects, including Total Addressable Market, Ideal Customer Profile, and Persona Development, are typically managed by marketing and informed by corporate Finance, Sales, Product, and other executive teams. Companies have invested in those projects at various growth stages, so in most cases, ABM programs will have an initial starting point. You should consider whether those starting points represent the current customer base and product strategy. Do they still represent your potential market? Have they been maintained?
Companies have a wealth of internal data available on how prospective customers engage with marketing and sales. That information can redefine competitive analysis in an AI driven world. ChatGPT and other tools will take a bit of well analyzed success points and steer you toward related industries, companies, and personas. External data is easily pulled in to expand industry keywords, identify interested companies, and determine which buyers have the business issue that matches your product. AI will identify the relevant industries and companies, provide inputs to market sizing, and define the buyers’ pain points. ChatGPT can be used as an enabler for competitive market analysis now, and tools will better curate competitive analysis information in the future.
AI Generated Content for ABM
OpenAI’s ChatGPT and other Generative AI Large Language models (LLMs) will revolutionize Account Based Marketing (ABM) approaches and challenge existing content strategies. AI will create a competitive advantage for companies that personalize messaging to better engage with their customers. ABM Marketers will create content differently, and campaign development speed will increase. New programs that were once impossible due to cost and team resources will be available to small, innovative teams. Marketing’s ability to write relevant, personalized content will no longer limit marketing teams.
Increasing ABM Campaign volume and speed to market will also create new challenges. Without proper management and controls, ChatGPT hallucinations, irrelevant or bland content, and out-of-date insights will reach customers and end users. New policies, workflows, and management will help brands avoid headaches while leveraging the power of AI for Account Based Marketing efforts.
In the past, a personalization miss was limited to “Dear First Name,” or the wrong company in the subject line. Now your content could be completely irrelevant or even factually incorrect. Bad marketing due to AI generated mistakes will become the reality for some marketers. For your ABM campaigns, you must continue to limit that potential by identifying low risk content areas or adding human content review content.
As you consider where and when to deploy ChatGPT, customer brand perception should be a top consideration. Will your customers be impressed that you’ve integrated AI? Or offended that you’ve taken humans out of your campaign production? Be sure to consider that perception in each ABM program and AI technology decision.
AI Personalization
According to David Edelman from HBS, AI Depends dramatically on the amount of data you have. In his HBR article, Customer Experience in the Age of AI, “Most brands don’t personalize customer experiences at the scale or depth necessary to compete with the world’s leading companies.” Personalization scale traditionally relies upon human writing. Leveraging ChatGPT allows marketers to personalize at scale. Variable fields like company, industry, and title become inputs for personalized messages.
A caveat when personalizing with ChatGPT: The Large Language Model (LLM) is trained on a dataset from 2021, making the results less relevant today than newly researched content. ChatGPT can easily miss that your target buyer has changed roles or companies. Keep AI-driven personalization to a higher level of pain point, industry challenges, and product solutions. Eventually, integrated AI tools that produce personalization from corporate data, LinkedIn, and fresh web content, will deliver more relevant, up-to-date ABM content.
ABM Policies
As responsible marketers embrace AI for ABM and other marketing campaigns, they will benefit from setting internal AI standards. Reviewing those with executives will build credibility for marketers throughout the organization and encourage other departments to embrace AI messaging and tools in their work as well. Your Marketing department must create these policies across campaigns.
- When is it ok to use AI, and when is human writing needed?
- Who writes prompts or confirms API inputs?
- Which AI-generated content must be reviewed?
- How do you approve content when it is created dynamically?
- Should you note to end users that the content was generated by AI technology?
- How do you ensure that AI content is factual and relevant?
- What is the proper apology message when AI gets it wrong?
Limits of ChatGPT for ABM
To avoid chatGPT mistakes, carefully consider the following limits of ChatGPT. As you evaluate new tools and approaches, consider whether they resolve these areas.
- AI will not provide up-to-date contact information. ChatGPT does not have access to personal information, and the LLM data is at least two years old.
- Competitive keywords and content change rapidly. Using a dataset from 2021 won’t get the most relevant keywords. You will need to leverage traditional tools and lean on their AI features. I recently managed an SEO exercise, and the tools were surprisingly similar to similar tools from 10 years back. The analytics have improved, but human research and campaign analysis remain critical and have not been replaced by ChatGPT.
- Hallucinations. Consider the risk of ChatGPT hallucinations and leverage the tools in low-risk environments. Review everything that could land your company in hot water. Consider the headlinemust be reviewed and edited by humans!
- Tools like ZeroGPT, have been developed to determine if AI generated a text block. In which cases will ChatGPT damage your brand? Consider that end users may be checking.