The future of demand gen will be wildly different than today.
Picture this.
You spend the majority of your budget acquiring opted-in, marketable contacts from types of companies you can sell to.
You invest in a proper data warehouse.
Contact enrichment becomes your top priority.
You rigorously test and implement intent data.
You fund a kick-ass marketing ops team.
You label, classify, and bucket all of the contacts by account types.
You build a hierarchy of account types based on vertical, spend potential, geo, maturity, etc. It gets better over time.
You develop propensity models based on all the data you've collected that bucket contacts and accounts by in-market vs out-of-market.
The in-market accounts get messaging with a jobs-to-done message, driving urgency.
You measure the behavior-- the signals they've created in the buying journey. All of those data points flow into the CDW.
You use the growth process to identify signals and ideate messaging. You execute the messaging and feed the data back into the model so the account and contact classification gets smarter and smarter.
Eventually you start to create meetings for sales or convert accounts through a self-serve funnel. Now your flywheel begins.
You do this so well, you establish a 50% conversion rate on in-market accounts. As more accounts convert you analyze why and feed that data back into the model.
Still with me?
Meanwhile, the out-of-market accounts receive slow and steady communication streams that build curiosity, tell delightful stories, and create interest (aka more signals).
You do this iteratively with the growth process until you understand which messaging sequences turn out-of-market accounts into in-market. You establish a 20-30% conversion rate on moving accounts from out-of-market to in-market.
Your team starts to hit ideation velocity. They are able to test messages in days not weeks, and they graduate winners and quickly deprecate failures.
The flywheel continues.
Then you plug an LLM into your database that feeds all of these customer signals into a conversational AI that can write pretty good messages to dozens of segments you created.
Now this entire process runs mostly automatically.
You re-position your marketing team to managing and diagnosing insights across this entire engine. They become experts at investigating data and interpreting insights.
You then hire copywriters to train the conversational AI to get it better at telling stories, being human, and personalizing to the unique preferences of your ICP.
This entire process becomes a machine and marketing's job is to keep it gassed up and maintained.
This now becomes the foundational demand gen process. Am I wrong?
Picture this.
You spend the majority of your budget acquiring opted-in, marketable contacts from types of companies you can sell to.
You invest in a proper data warehouse.
Contact enrichment becomes your top priority.
You rigorously test and implement intent data.
You fund a kick-ass marketing ops team.
You label, classify, and bucket all of the contacts by account types.
You build a hierarchy of account types based on vertical, spend potential, geo, maturity, etc. It gets better over time.
You develop propensity models based on all the data you've collected that bucket contacts and accounts by in-market vs out-of-market.
The in-market accounts get messaging with a jobs-to-done message, driving urgency.
You measure the behavior-- the signals they've created in the buying journey. All of those data points flow into the CDW.
You use the growth process to identify signals and ideate messaging. You execute the messaging and feed the data back into the model so the account and contact classification gets smarter and smarter.
Eventually you start to create meetings for sales or convert accounts through a self-serve funnel. Now your flywheel begins.
You do this so well, you establish a 50% conversion rate on in-market accounts. As more accounts convert you analyze why and feed that data back into the model.
Still with me?
Meanwhile, the out-of-market accounts receive slow and steady communication streams that build curiosity, tell delightful stories, and create interest (aka more signals).
You do this iteratively with the growth process until you understand which messaging sequences turn out-of-market accounts into in-market. You establish a 20-30% conversion rate on moving accounts from out-of-market to in-market.
Your team starts to hit ideation velocity. They are able to test messages in days not weeks, and they graduate winners and quickly deprecate failures.
The flywheel continues.
Then you plug an LLM into your database that feeds all of these customer signals into a conversational AI that can write pretty good messages to dozens of segments you created.
Now this entire process runs mostly automatically.
You re-position your marketing team to managing and diagnosing insights across this entire engine. They become experts at investigating data and interpreting insights.
You then hire copywriters to train the conversational AI to get it better at telling stories, being human, and personalizing to the unique preferences of your ICP.
This entire process becomes a machine and marketing's job is to keep it gassed up and maintained.
This now becomes the foundational demand gen process. Am I wrong?
