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Looking to add AI to your demand generation mix?
Can you start by testing AI tools for random tasks? Of course. But if you’re looking to optimize multiple programs and repeat the results, consider your existing workflows.
Scaling isn’t about finding shiny new objects; it’s a real-world implementation.
“The challenge we all face is really how do we optimize demand generation when AI can do so much?” says marketing consultant and author of The Modern AI Marketer Pam Didner. “The question we ask ourselves in terms of optimization is: what should AI do for you?”
His recommendation? Look within yourself to see what you are already doing and optimize it first.
His recent MarketingProfs online seminar detailed his seven steps to expand AI-powered efforts into your existing demand generation programs.
Step 1: Understand your demand generation channels
First, the easy part: create a list of all the channels and campaign types you currently use in your demand generation programs.
E-mail, social networksPPC, original content: List them all, even if you rarely use them, like in-person roadshows.
Step 2: Document processes and workflows
“The next step is to document processes and workflows,” says Pam. “This will give you an idea of what to optimize.”
Perhaps you already have a manual that describes the reproducible activities you undertake and how you do them. Great!
Don’t have documented processes? Don’t worry, many companies don’t. But you’ll want to take a few minutes to map out these workflows so you can identify where AI can add the most value. A one-slide flowchart for each campaign type works great.
Detail the key activities and steps of each program. For example, if you are using webinars, document the activities before, during, and after the event.
Pam explains: “Let’s say you’re hosting a quarterly webinar and it’s a big event. You may have paid ads on LinkedIn, you run multiple email campaigns, and you also publish lots of social media posts to drive traffic to the signup page. Then a day comes, you have the webinar and after the webinar you send a thank you email. »
While this is a fairly typical webinar process, it may not be the case. your Process. Document what works for you, not what you think others are doing.
If your campaigns include lead nurturing, sales enablement, or related top-down processes, document those as well.
Step 3: Evaluate the place of AI
Now is the time to rely on AI. According to Pam, “there are many ways to do it,” and only part of it involves writing.
Back to your process flowcharts: Circle everything with an AI use case. “You need to write LinkedIn ads, emails, social media posts, even the webinar thank you email. So this is one way to automate the process.”
Watch this clip from Pam’s recent MarketingProfs presentation, “Optimizing Lead Generation with AI,” for more ideas on where and how AI can fit into your programs:
Step 4: Inject the tools
It’s time to select your tools. Many marketers mistakenly start their AI journey at this stage because shiny new technologies are fun. But the selection and purchase of any new tool should come After you understand your existing programs and the problems you need to solve.
Pam suggests using existing AI tools and built-in features your organization already has before considering new tools. “Focus on using existing tools” in your martech stack. “See if existing tools can satisfy all needs.”
For example, if you already use a chatbot, like ChatGPT or Google Gemini, continue to use it and test its performance. Or, if your CRM has built-in AI features, give them a try.
Step 5: Test and modify
Then: test, measure and optimize.
“You might not get it right the first time. Give yourself time to correct or make adjustments based on the workflow,” advises Pam. “Create a control environment, test your hypothesis with A/B testing and start small. »
If it’s not working (or not as well as your traditional methods), change what you’re doing.
Step 6: Think like a data analyst
Measure and analyze your results. “You have to think like a data analyst,” says Pam.
“When you’re using AI to help you generate demand, you want to make sure it’s actually helping you. It’s not hurting your demand generation efforts.”
Quantify the results. “That’s the key. That’s the really important part that we marketers tend to overlook,” she emphasizes.
Step 7: Retest and Edit Again
Get ready. Be prepared. Do it again.
Pam says: “Test results based on specific changes”:
- First, does it actually make your workflow more efficient?
- “The other one, because it’s demand generation, is SQLs and leads,” as well as any other conversion metrics or financial KPIs you’re responsible for.
“Then you have to retest and re-modify.”
Who is the boss?
Finally, consider who is doing all the thinking. If you’re considering outsourcing strategic demand generation work to AI (or, further down the line, downsizing and employing AI instead), ask yourself: Can AI think like a demand generation marketer?
He can perform tasks. It can even help you generate new ideas for your campaigns. But to achieve meaningful KPI results, You You need to embrace strategic thinking. AI is just a tool to help you get there.
Want to see more of Pam’s ideas on AI use cases and steps to scale AI, including using AI for demand generation planning and budget allocation? Discover his AI for Demand Generation Marketers presentation.
Other resources in the AI for Demand Gen Marketers series
Can AI save you from marketing hell?
Using AI across the customer journey requires alignment across teams
Use AI to create your personas: don’t lose sight of your real buyers
AI Can’t Write Thought Leadership (But It Can Do Other Things)
Your AI needs a human reviewer
AI can do hard things for you (like predict your future success)
