Context

When running outbound campaigns in Unify, customers often need to customize their messaging based on different target industries (verticals) and personas to make their outreach more relevant and effective. This involves setting up sequences and plays that can deliver personalized content based on company verticals and recipient roles.

Answer

To effectively customize messaging for different industries and personas in Unify, follow these best practices:

1. Create Separate Sequences by Persona Create distinct sequences for different personas (e.g., HR, Operations, IT, Support) rather than trying to handle all variations within a single sequence. This helps maintain clarity and reduces complexity in your messaging.

2. Set Up Industry‑Specific Plays Create plays using the following structure:

   • Start with a company audience trigger node

   • Add a prospect node to identify specific personas within target companies

   • Include a loop node to process the prospects

   • Add your sequence node within the loop

3. Define Clear ICP Parameters In your personas settings, define:

   • Target verticals (e.g., Healthcare, Financial Services, Automotive)

   • Relevant job titles and roles

   • Company size parameters

   • Other qualifying criteria specific to your target market

5. Use Smart Snippets for Customization Smart Snippets can be used in two ways to customize messaging:

   • Conditional logic - Limit logic branches to 1-4 conditions total, focusing on clear, distinct segmentation criteria. Keep snippets short and focused on personalizing only the parts that vary (e.g., salutation or opening line). Limit variables to high‑fill essentials like {{Person First Name}} and {{Company Name}} to avoid fallback issues, and avoid low‑fill variables (e.g., address, company descriptions) that may trigger unexpected fallback text. Define clear fallback text for all variables, as snippets fall back if any variable is missing. Maintain a human, straightforward, and concise tone; avoid gimmicks. Provide 2‑3 example outputs in the Smart Snippet setup to anchor tone and style.

   • AI Research summaries - Use Smart Snippets powered by Agents to generate personalized content based on AI Research findings. Create Agents to answer research questions about your prospects, then reference those agent outputs as variables in a Smart Snippet prompt. Structure the prompt to generate a 1‑2 sentence actionable summary of research findings, and include a static text fallback for cases where research data is unavailable. Add a short delay at the start of your sequence/play to ensure research completes before the snippet runs.

   Note: When using AI Research with Smart Snippets, fallback text must be static only and cannot contain variables. If any variable is missing, the snippet will use the fallback.

Technical Limitations of Smart Snippets in Unify

While the published guidance recommends keeping Smart Snippet logic simple, understanding the underlying technical constraints is crucial for successful implementation.

Critical Technical Constraints

• Single-variable fallback behavior: If ANY variable in a snippet is missing or empty, the ENTIRE snippet falls back to static text, even if other variables have values.

• No variables in fallback text: Fallback text must be completely static and cannot contain any variables or conditional logic.

• No multi-variable conditional logic: Attempting to create "if A, else B, else C" logic within a single snippet will not work as intended.

Practical Workaround Pattern

1. Create separate, single-variable snippets. Each snippet should use only one variable (e.g., snippet_primary uses only {{field_A}}, snippet_secondary uses only {{field_B}}).

2. Use Play If/Else logic for routing. Route prospects to the appropriate snippet based on which fields are populated.

3. Ensure each snippet has static fallback text. Keep fallback text completely static with no variables.

Conditional Logic for Industry-Based Personalization

You can implement conditional logic based on prospect attributes like industry to populate relevant customer references. For example, create conditions that reference your insurance customers if the prospect is in insurance, finance customers if in finance, with a general template as the default fallback for other industries.

You can also run an Agent on industry data and specify what to flag in the guidance, then use that output in your conditional logic.

Common Use Case: Handling Missing Contact Data

A frequent scenario is handling missing first names to avoid awkward greetings like "Hi ,". Use Smart Snippets to create: if first name exists use {{first_name}}, otherwise use "there" as a fallback for professional salutations.

Best Practice: Rather than creating complex conditional logic within a single sequence, create separate, focused sequences for specific industry-persona combinations. This approach provides better control over messaging and typically yields better results.