Batch personalization for key contacts at target accounts

Engage key decision-makers at target accounts with content that feels relevant from the first touch. This playbook shows how to pre-personalize and distribute content at scale for specific individuals at target accounts so ABM and Sales teams can move faster, stay consistent, and generate stronger account-level signals without creating bespoke assets one by one.

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 creating the core piece of content you want to personalize, for example a guide, report, or sales asset tailored to a specific persona or use case.

This base asset becomes your single source of truth. It holds the messaging, structure, and visuals that will carry through every personalized version, so you’re not rebuilding content from scratch for each contact.

From the outset, identify which elements will be adapted per contact - such as persona, seniority, or geography - while the rest of the content remains consistent.

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.

Think of this step as investing once, so you can scale relevance without sacrificing quality.

This step is where your content starts to feel personal.

Instead of creating multiple versions of the same asset, you define modular parts that adapt based on who’s viewing. This could be copy, images, or entire pages that are only relevant to certain contacts, industries, or roles.

Once you’ve decided where relevance matters most, configure personalization so the base asset can automatically produce multiple tailored versions in the next step. This is done by marking variable text or visuals with personalization tokens and setting page rules that show or hide sections based on contact attributes - so each reader only sees what applies to them.

Behind the scenes, a personalization form acts as the control layer for the base asset. This form defines which data replaces each token and which page rules are applied.

You can set this up in two ways:

Once this is done, you’ve locked the logic. From here on, personalization scales cleanly without rework.

This is where your setup pays off.

Instead of manually personalizing content one contact at a time, you generate an entire batch in one go using the data you already have.

Start by exporting contact data from your CRM or MAP as a CSV. The fields you include should align with how you plan to personalize. Each row in the CSV generates a new contact-specific version from the same base asset.

Upload the CSV into Turtl and map each column to the corresponding fields in your personalization form. If your form fields were created via an integration, this mapping step will be faster and more consistent.

Once mapped, generate your batch. Each contact receives their own personalized asset, complete with a unique URL and GIF, ready to be shared by via link, email, or any distribution options. Your full batch is available directly in Turtl and can also be exported as a CSV if needed.

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 important 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.

Once your personalized content is live and readers start to engage, data flows into your Turtl Dashboards, giving you visibility into what’s landing and where interest is building.

For this playbook, you’ll see three types of audience insight:

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 pay attention to include:

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.

There are two main ways this data is used:

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

Supported Integrations

This is where long-term ABM efforts start to show commercial impact. 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 influences 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.