Email Tags

Definition

Email tags are metadata labels applied to subscriber profiles or email campaigns to categorise, segment, and trigger automated actions. Tagging systems come in two primary forms. Profile tags are applied to individual subscriber records based on behaviour (purchased product X, attended webinar Y, clicked link Z), demographics (industry, company size, role), lifecycle stage (new lead, active user, at-risk, lapsed), value tier (high-value, medium-value, low-value), or interests (content topic preferences, product category affinities). Campaign tags are applied to individual email sends to track performance by category, initiative, or season — enabling cross-campaign reporting that aggregates results by tag rather than individual campaign. According to Klaviyo's 2024 platform benchmarks, brands using tag-based segmentation achieve 35% higher click-through rates and 25% lower unsubscribe rates compared to brands using only list-based segmentation.

The most effective tagging systems incorporate RFM (recency, frequency, monetary) tags that segment subscribers by when they last engaged, how often they engage, and how much they spend. An RFM-tagged subscriber profile might read: highRecency_highFrequency_highValue — indicating an ideal customer for VIP treatment. Lifecycle tags (new, active, at-risk, lapsed, resurrected) enable stage-appropriate messaging that reduces unsubscribes from over-engagement. Interest tags (product_category_A, content_topic_B) power content personalisation without requiring complex segmentation logic. Most ESPs support automated tag assignment based on trigger events — a subscriber who abandons a cart can be automatically tagged with abandonedCart, which triggers the abandoned cart workflow and segments them for re-targeting.

Best Practices

• Design a tagging taxonomy before implementing tags in the ESP: Map out the complete tag hierarchy on paper or a spreadsheet before creating any tags in the platform. Define the naming convention (use lowercase_snake_case for consistency), tag categories (behaviour, demographic, lifecycle, interest, source), tag relationships (mutually exclusive tags, overlapping tags, parent-child hierarchies), and the maximum number of active tags per profile. A well-designed taxonomy prevents the tag bloat that slows ESP performance.

• Automate tag assignment through triggers not manual entry: Manual tagging creates errors and gaps. Configure automated tag assignment based on behaviour events (purchase, page visit, email click), data value changes (profile field update, score threshold crossing), and integration syncs (CRM deal stage changes, ecommerce order status updates). Review automated tagging rules quarterly to ensure they still align with current segmentation needs.

• Limit active tags per profile to 20-30 maximum: Too many tags per profile degrades ESP performance, makes segmentation confusing, and suggests the tagging system needs simplification. If profiles regularly accumulate 50+ tags, the tag taxonomy is too granular — consolidate similar tags, archive obsolete tags, and implement a tag archiving policy that removes tags after 12 months of non-use.

• Use tags for segmentation, lists for sending compliance: Tags enable flexible, multi-dimensional segmentation across behavioural, demographic, and lifecycle dimensions. Lists (or static groups) are better for permission-based sending — maintain a "marketing consented" list separate from tags for compliance. A subscriber with promotional interest tags who lacks the "marketing consented" tag should not receive marketing sends regardless of their tag profile.

• Implement a tag governance process to prevent tag bloat: Designate a tag owner responsible for the tag taxonomy, approve new tag requests through a weekly review process, and archive unused tags monthly. Without governance, tag systems grow chaotically as each team member creates their own tags. A 2-year-old ESP instance with no tag governance typically has 3-5x more tags than needed, and 40-60% of them are unused.

• Integrate tags with preference centre data: Allow subscribers to set their own interest tags through the preference centre (selecting content topics, email frequency, product categories). Self-selected tags are 2-3x more predictive of future engagement than behaviourally inferred tags because they reflect explicit intent. Prompt preference centre updates periodically ("Are your interests still the same?") to refresh tag accuracy.