Four-Part AI-Era Marketing Playbook
Combine AI efficiency, human creators, personalization, and indirect measurement
- Difficulty
- Advanced
- Time to result
- ~months to results
- Steps
- 4
- Confidence
- 98%
The playbook updates marketing across four connected areas. First, use AI to perform research, pattern analysis, and routine production so people can concentrate on differentiated perspectives, data, and answers. Second, build audiences natively on social platforms through credible employees, dedicated creators, and external partners rather than relying on links back to a website. Third, combine CRM, intent, enrichment, and behavioral data to replace segment-level messaging with individualized experiences across email, chat, and eventually voice. Fourth, adapt measurement to a less linear customer journey by combining direct attribution with surveys, qualitative evidence, model queries, and correlation. The mechanism is cumulative: AI creates operating leverage, creators earn attention, unified data improves relevance, and broader measurement captures effects that platform analytics can no longer reveal.
Origin
Extracted from Marketing Against The Grain as the hosts workshopped how HubSpot and other marketers should adapt inbound strategy during the experimental early phase of the AI internet.
Core principles
- 01Use AI to create room for differentiated human work
- 02Build native audiences instead of treating social as a referral pipe
- 03Replace broad segments with data-rich individual experiences
- 04Measure influence beyond directly attributable conversions
- 05Experiment while the technology and channels remain unsettled
How to run it
- 1
Enable Inbound With AI
Use AI for large-scale research, competitive pattern analysis, templates, and routine content work. Invest the saved time in differentiated perspectives, proprietary data, complex answers, and other defensible qualities.
Pro tip Connect internal performance analytics so the AI can learn which content patterns actually work.
Watch out Do not respond to declining traffic by publishing a larger volume of undifferentiated content.
- 2
Build Creator-Led Channels
Treat social platforms as destinations where the company must earn a real audience. Empower internal experts or dedicated creators to publish native, human-led video and partner with trusted creators in the market.
Pro tip Give each creator ownership of a channel and freedom to test formats at scale.
Watch out Do not bury creators under the approval processes and operating constraints of a conventional large-company team.
- 3
Deliver One-to-One Personalization
Combine CRM history, first-party behavior, intent signals, enrichment sources, and current external events to understand each prospect. Use AI to generate relevant interactions across outreach, email, chat, and later voice.
Pro tip Begin with a narrow high-value journey where data quality and commercial impact can both be measured.
Watch out Personalization without accurate data can produce irrelevant, intrusive, or factually wrong messages.
- 4
Measure Direct and Indirect Impact
Retain direct attribution where it remains available, but supplement it with surveys, qualitative research, correlations, and visibility inside AI systems. Align leaders on how indirect influence will be evaluated before shifting budget.
Pro tip Document a shared measurement model so indirect activity is not judged retroactively by direct-response standards.
Watch out Do not assume that untracked activity is either worthless or automatically effective.
In the wild
A B2B team uses AI to study ranking pages, identify their common structure, and reveal unanswered complex questions. Editors then add proprietary customer data and a distinct point of view instead of publishing another generic article.
→ The team produces fewer interchangeable pages and competes with content that is harder for search summaries to replace.
A software company selects an employee with deep industry knowledge, gives that person ownership of one video channel, and supplies outlining and editing support. The creator experiments without routing every post through the full corporate approval chain.
→ The company builds a trusted native audience around a recognizable person rather than using social only to distribute links.
A team combines CRM records with external company research and monitors events such as a new funding announcement. When a relevant event occurs, AI updates the prospect's outreach sequence with timely company and individual context.
→ Outreach becomes current and individualized instead of relying on a static segment message.
Common mistakes
Automating the Undifferentiated Majority
Using AI only to multiply standard educational content increases supply without creating an advantage. AI should handle groundwork while people improve the distinguishing portion of the work.
Using Social as a Link Distribution Feed
Closed platforms suppress outbound links and reward content that retains attention. A company must create value inside the channel and earn an audience there.
Demanding Direct Attribution for Everything
Privacy changes, fragmented journeys, and closed platforms hide an increasing share of marketing influence. Judging every activity by directly observed revenue will misprice valuable work.
Is it for you?
Best for
It is best for established marketing teams adapting inbound programs to AI-driven changes in discovery, content, customer data, and measurement.
Not ideal for
It is not ideal for teams without reliable customer data, basic inbound capabilities, or enough capacity to run controlled experiments.
From the transcript
“this is the four-step marketing Playbook that is going to allow you to beat all of your competition”
“you will need to integrate AI to well in in the way you do inbound anyway to be able to have enough time to really…”
“we go from SE segmentation segment personalization to onet toone personalization”
From the episode
How Ai Is Changing A $28.6B Company’s Marketing Strategy (2024)