Personalized content on demand for sales and ABM teams

Make it easy for sales and account teams to generate polished, personalized content for each prospect or account by filling out a simple form. This removes manual editing, keeps messaging consistent, and helps teams deliver tailored collateral faster.

This playbook is designed to spark ideas and provide the practical details you need to understand how a campaign will play out - what’s supported, how it functions, and what to plan for. Pick the steps that fit your objectives, and mix or adapt approaches from other playbooks to create campaigns that suit your goals and tech stack.

This diagram presents a high-level overview of the playbook, illustrating each step and the integrations supported along the way. The article then explores each step in more detail.

Start by building the content you want to personalize, this could be a sales proposal, a post-call follow-up, or a product overview. Treat it as your base template. It should include the core messaging, visuals, and structure that will later be tailored for each account or contact.

Use Hatch AI to speed up creation and refinement, helping you draft, rewrite, translate and localize, and keep content on brand as you build. The stronger and more complete this base asset is, the more effective your personalization will be later.

Prepare your content for personalization by deciding which elements should change for each account or contact. This might include adding the customer’s name on the cover, pulling in the sales rep’s details, showing or hiding pages based on interests, or importing a custom pricing table from a CSV.

Once you’ve identified where relevance matters most, configure personalization so the base asset can be used by your wider team. Mark variable text or visuals with personalization tokens, and apply page rules that show or hide sections based on contact attributes - ensuring each reader only sees what’s relevant to them.

A personalization form then acts as the control layer for the base asset. This is what your team completes to generate personalized versions, defining which data replaces each token and which page rules are applied.

When the form is ready, publish the content and run through it once yourself to confirm everything personalizes correctly.

Once the document is published, your front-line teams simply log into Turtl, fill out the personalization form, and generate a tailored version for each prospect or account whenever they need.

They never touch the base template, so everything stays consistent. Turtl takes the form inputs and applies them automatically to the base asset, producing a ready-to-share personalized content.

Now that each contact has their own personalized asset, the focus shifts to distribution and visibility. If you’re sharing content with contacts that already exist in your CRM, it’s helpful to ensure engagement in Turtl is attributed to an individual contact within the Analytics Dashboards.

Once engagement is attributed to specific contacts in Turtl, you can:

There are two ways to identify Known Readers in Turtl:

If you choose not to identify readers in Turtl, you’ll still be able to see engagement for each personalized asset in the Personalization Dashboard. However, you won’t get contact-level attribution or CRM enrichment, which limits how actionable that insight is.

This step ensures your personalized content doesn’t just look relevant, but feeds directly into follow-up, prioritization, and pipeline decisions.

As people read your personalized content, their activity flows straight into your Turtl Dashboards.

For this playbook, you'll see three types of audience data:

This step gives you clarity on whether your personalization is resonating, and where to focus follow-up, sales outreach, or optimization next.

With engagement data flowing in, Turtl Dashboards help you move from activity to insight.

Instead of guessing whether personalization is paying off, you can clearly see what content, sections, accounts and contacts are driving meaningful engagement, and which ones need adjustment. This makes it easier to prioritise follow-up, refine messaging, and improve future campaigns based on real behaviour.

Hatch AI plays a key role here, with an analytics chatbot enabling you to query and interrogate data without a heavy lift.

Key metrics to watch:

By reviewing these signals regularly, you can spot patterns early, focus effort where it matters most, and make informed decisions about what to repeat, refine, or retire.

Supported Integrations

At this point, your personalized content is generating intent you can act on.

By syncing Turtl engagement data into your existing platforms, you make that insight available where teams already work, so it can inform prioritisation, outreach, and targeting without manual effort.

Turtl supports syncing intent data into platforms such as HubSpot, Marketo, Pardot, Demandbase, and 6sense. Exactly what can be synced depends on the specific platform.

This step ensures the effort you put into personalization directly strengthens lead scoring, account prioritization, and campaign targeting across your stack.

Supported Integrations

Once you have Known Readers in Turtl, those readers are matched to CRM contacts, and those contacts are linked to opportunities, Turtl’s Revenue Dashboard can show how content engagement aligns with pipeline movement and closed revenue.

The Revenue Dashboard helps you understand what content influence progression, acceleration, or conversion, giving you a clearer picture of where content supports revenue, rather than relying on assumptions or last-touch attribution.

The Hatch AI chatbot within the analytics dashboards helps you to explore this data more deeply, identifying patterns in what’s performing, surfacing successful approaches, and highlighting where content is having the greatest commercial impact. These insights make it easier to double down on what works and refine what doesn’t.

This final step closes the loop, linking personalization efforts back to measurable business outcomes.