The send looked fine. The persuasion was zero.
Open and click rates hide the mismatch. A buyer can politely open every PDF you send and never read past page one, while the format they binge sits unused in your library.
Wave · Engagement Format
Your webinar person does not want your whitepaper. Wave knows the difference.
Every database has buyers who watch everything and read nothing, and buyers who do the opposite. Wave learns each person's format from what they actually consume across your stack and writes it to your CRM, so every send, nurture, and recommendation arrives in the format they engage with.
Quick answer
Engagement Format is a Wave prediction that identifies the content format each person actually consumes, webinar, video, whitepaper or report, blog post, podcast, case study, and more, from their real engagement history across your stack. The prediction carries a confidence grade, refreshes daily, and writes back to your CRM so campaigns and content recommendations can route on it.
Key capabilities
- Per-person format prediction with a confidence grade
- Trained on real consumption across your stack, not email opens
- A format taxonomy you define and control
- Feeds Next Up Content recommendations
- Daily refresh with CRM writeback you opt into
- Per-tenant kill switch, suppression always honored
- One model per tenant, never shared
Last updated July 2026
The problem
Format mismatch is the silent killer of good content.
Teams invest in the asset and guess at the distribution format. The whitepaper goes to the executive who only attends webinars, the webinar invite goes to the analyst who reads everything, and the reporting calls both engagement.
MAP data self-selects
Your marketing platform learned from email-native behavior, so it recommends what email people do. Ungated reads, webinar attendance, and video views never make it into the picture.
Personas are not preferences
Role-based format rules, executives want one-pagers, engineers want docs, are folklore. Actual format preference is individual, and it shifts across the buying journey.
How Wave does it
Learned from what each person consumes, written where your campaigns run.
Wave joins every engagement event to the format of the content it touched, then turns each person's history into a prediction any marketer can act on.
- 01
Read consumption across your stack
Wave gathers engagement from your connected systems, HubSpot today plus warehouse and file-imported history, so the signal covers ungated reads, webinars, and video, not just email clicks.
- 02
Know the format of every asset
Wave's content intelligence tags each asset's format automatically against a taxonomy you define and control, so every engagement event carries a format signal.
- 03
Predict the format, with a grade
Each person gets a predicted format and a confidence grade. When someone's history is too thin to support a real prediction, Wave says so instead of guessing.
- 04
Write it back, on your terms
The prediction syncs to your CRM on a daily cycle. Writeback is off until you opt in, governed by a per-tenant kill switch, and suppressed contacts are never written to.
Where it fits
The format axis of Wave's person-level intelligence layer.
Channel Affinity answers where, Cadence Affinity answers when, Engagement Format answers how. Together they give every campaign a person-level playbook.
Your sources
Wave
HubSpot
Wave reads from your existing systems through native connectors, trains one model per tenant so your data never trains on anyone else's, and writes the predicted format back to HubSpot today, with Marketo next. Next Up Content uses the same prediction to put the right asset in the right format in front of every contact, and every writeback is logged with previous value, new value, and the model version.
Works alongside Channel Affinity, Next Up Content, The full Wave platform.
Why Wave is different
No MAP, ESP, or content tool predicts this per person.
Content tools track sessions and sellers. MAPs track their own sends. Wave predicts the format each individual buyer prefers and hands it to the CRM your campaigns already run on.
Most tools
Wave
MAPs learn format from their own email engagement, which self-selects for email-native behavior.
Wave trains on consumption across your stack, ungated content, webinars, video, and imported history included.
Content experience tools score anonymous sessions, not people.
Wave's prediction is per person, attached to the contact record your campaigns already run on.
Sales content tools recommend assets to sellers, not formats to buyers.
Wave feeds format fit into Next Up Content, so per-person recommendations already respect it.
Format rules are hardcoded persona folklore.
Wave's taxonomy is yours to define, and the preference is learned per individual with a confidence grade.
FAQ
Questions buyers ask about Engagement Format.
What is Engagement Format in Wave?
Engagement Format is a per-person Wave prediction of the content format each buyer actually consumes, webinar, video, whitepaper or report, blog post, podcast, case study, and more, learned from real engagement history across your stack. It refreshes daily, carries a confidence grade, and writes to your CRM with an audited, reversible writeback.
Which formats can Wave predict?
Wave ships with a starter set of eleven common B2B formats, including webinars, video, whitepapers and reports, blog posts, podcasts, case studies, infographics, interactive tools, newsletters, landing pages, and in-person events. The taxonomy is per tenant: add, remove, or rename formats and Wave adapts to your library.
What data trains the prediction?
Each person's engagement history joined to the format of every asset they touched. The signal is entirely first-party from your connected systems, including ungated reads, webinar attendance, video views, warehouse events, and imported history. One model per tenant; your data never trains anyone else's.
How is this different from what my MAP already knows?
Your MAP knows which of its own emails and pages were touched, which self-selects for email-native behavior. Wave joins engagement to the format of every asset across your sources and produces a per-person prediction with a confidence grade, not a raw activity log.
What happens for a brand-new contact?
When a person's history is too thin to support a real prediction, Wave says so and predicts nothing rather than outputting low-confidence noise. As consumption accumulates, the prediction appears with its confidence grade.
Where does the prediction show up?
On each contact in Wave, alongside inbound channel, promotional channel, and communication cadence, and in your CRM as an enrichment field your workflows can route on once you opt into writeback. Writeback is off by default and governed by a per-tenant kill switch.
Does it feed content recommendations?
Yes. Next Up Content uses format fit as one of its ranking signals, so each person's recommended next asset already respects the format they prefer.
How do I see format predictions on my own contacts?
Book a 20-minute walkthrough. We will run Wave against your engagement history and show the format predictions it would produce for your real contacts.
See it on your data
See the format every buyer prefers, on your data.
Book a 20-minute walkthrough. We will run Wave against your engagement history and show the format predictions it would write to your contacts.
Request a demo