Messaging Events Data Modeling

this feature is currently in beta for access to this, please reach out to mailto\ help\@chord co ! overview this guide explains how chord models messaging engagement data from klaviyo and iterable to support campaign analysis, audience segmentation, and activation we highlight the most important attributes, event types, and how we enhance klaviyo’s and iterable’s native data with structure and long term storage for smarter use across your customer journeys both platforms are unified into a single set of models the same explores, the same attribution logic, the same metrics differences between platforms are called out where relevant who this is for marketing and crm teams using klaviyo to power messaging campaigns and segmentation core event attributes each klaviyo event modeled in chord includes the following key attributes event date when the action occurred—such as an email being opened, a message clicked, or an order placed session sessions help organize activity a session starts when a user engages with a qualifying event (e g , opens an email) we use this to model session based metrics like order attribution or conversion analysis touch type identifies the origin of the message touch type klaviyo iterable campaign one time sends one time sends (blast, triggered) flow / workflow automated flow messages automated workflow messages null external apps or non klaviyo sources events without a campaign or workflow measures & metrics we model multiple types of performance measures to support analysis event counts total number of times an event occurred—e g , how many emails were opened or links clicked unique events first time actions for a user within a given campaign or flow for example unique opened emails – used to start sessions unique click rate – calculated as unique clicks divided by unique opens this is especially useful for building performance funnels across flows or campaign types revenue attribution for events like placed order (klaviyo) or purchase (iterable), we capture revenue related fields and associate them with the triggering session this allows for clear connection between engagement and revenue outcomes supported channels by platform channel klaviyo iterable email yes yes sms yes no push yes yes attribution & session modeling chord’s messaging explore supports deeper insights with structured attribution windows and session rules both klaviyo and iterable use the same session based last touch attribution logic attribution lookback windows channel lookback period platforms email 120 hours (5 days) klaviyo, iterable push 120 hours (5 days) klaviyo, iterable sms 24 hours klaviyo only session defining events a new session begins when a user engages with one of these events klaviyo iterable opened email email open clicked email email click clicked sms (no sms) opened push push send campaign enrichment field klaviyo iterable campaign name yes yes campaign status yes yes utm parameters yes (source, medium, campaign, term, content) no message medium no yes (email, push) campaign type no yes (blast, triggered) template name no yes channel name no yes message type no yes target lists no yes (list names resolved) suppression lists no yes (list names resolved) workflow id no yes send size no yes when the optional campaign mapping transform is enabled, both platforms are enriched with standardized campaign classification fields (region, brand, objective, category, etc ) where to find this data on chord once your messaging events are ingested by chord, you will be able to further analyze your messaging data on chord follow the steps below to dig into your data log into the chord commerce data platform navigate to explores tab on the analytics page click on the explores dropdown on the left side of the page select one of the following options based on what you’d like to analyze messaging events use this explore to create session funnels and analyze campaign or flow performance messaging lists use this explore to dive into active subscriber counts messaging segments use this explore to analyze behavior based targeting in campaigns filtering & interpretation tips note klaviyo campaigns don’t include a field that explicitly identifies the channel (e g , email vs sms) campaigns rarely mix channels, so we recommend using event types and channel specific metrics for precision use source platform to filter for a specific platform or compare across platforms use campaign names to filter for one time sends if the campaign name is blank, the event likely came from a flow (klaviyo) or workflow (iterable) you can use touch type to distinguish flows/workflows from campaigns and external sources clicks and delivery outcomes are modeled separately by channel email and sms clicks are tracked independently rates like click through or bounce are also channel specific push messaging metrics include bounce, send, and open active subscriber modeling ( klaviyo only ) chord enhances klaviyo's list data by adding historical depth list membership klaviyo allows you to select lists when building a campaign, but doesn’t retain list membership counts over time chord enhancement we snapshot profile counts per list at regular intervals so you can track how many people were eligible for a campaign at send time; and understand historic list size and growth trends analysis not yet available identifying which users were members of specific lists for downstream activation