[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"$f3rkozou7t4xwn":3},{"_id":4,"slug":5,"title":6,"subtitle":7,"kind":8,"cards":9,"tags":58,"categories":60,"source":62,"lang":65,"author":66,"audioState":69,"stats":70,"publishedAt":73,"renderer":74},"6aba9324ca21c797c7e9a09c","how-to-build-an-ai-ready-customer-profile-3e05cdff","How to Build an AI-Ready Customer Profile","Connecting an AI application to a CRM or a customer data warehouse is relatively easy.","news",[10,13,18,23,28,33,38,43,48,53],{"headline":6,"body":11,"imageUrl":12,"sourceImageUrl":12},"Connecting an AI application to a CRM or a customer data warehouse is relatively easy. The harder part is deciding what the AI should actually receive.","https:\u002F\u002Fmedia2.dev.to\u002Fdynamic\u002Fimage\u002Fwidth=1200,height=627,fit=cover,gravity=auto,format=auto\u002Fhttps%3A%2F%2Fdev-to-uploads.s3.us-east-2.amazonaws.com%2Fuploads%2Farticles%2Fbfagijrn3fu6bo70l7f2.png",{"headline":14,"body":15,"imageUrl":16,"images":17},"A customer may exist in a CRM, an","A customer may exist in a CRM, an e-commerce platform, a support system, a billing database, an email platform, and several other systems. Each system contains only part of the picture.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F1.webp",{"local":16},{"headline":19,"body":20,"imageUrl":21,"images":22},"Bringing all those records together is useful, but","Bringing all those records together is useful, but it does not automatically produce a customer profile that an AI system can reliably work with.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F2.webp",{"local":21},{"headline":24,"body":25,"imageUrl":26,"images":27},"Before customer data becomes useful context for AI","Before customer data becomes useful context for AI, several architectural problems need to be addressed: identity resolution, event processing, derived signals, consent, governance, data freshness, and the different views required by different applications. This article looks at those problems from a data architecture perspective. A customer profile is not a data dump","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F3.webp",{"local":26},{"headline":29,"body":30,"imageUrl":31,"images":32},"A common approach to customer data is to","A common approach to customer data is to collect as much information as possible and make it available to downstream applications. That can work for analytics, where the analyst can decide which fields and tables are relevant. AI applications are different.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F4.webp",{"local":31},{"headline":34,"body":35,"imageUrl":36,"images":37},"An AI system may need a much more","An AI system may need a much more deliberate representation of the customer. It needs to understand which information is relevant, how different pieces of data relate to each other, and which information represents the current state versus historical behavior. Consider a customer support assistant. the customer's current account status relevant product information A sales assistant might need a different subset: A personalization system might instead be interested in behavioral signals and preferences. The underlying data can be the same, but the useful representation is different. This suggests a useful separation between the customer data foundation and the customer views exposed to applications.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F5.webp",{"local":36},{"headline":39,"body":40,"imageUrl":41,"images":42},"The foundation contains the information needed to reconstruct","The foundation contains the information needed to reconstruct and understand the customer. Application-specific views provide the context needed for a particular use case. Events and records describe different things Customer data generally contains two different kinds of information.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F6.webp",{"local":41},{"headline":44,"body":45,"imageUrl":46,"images":47},"Records describe a current state: A customer has","Records describe a current state: A customer has a particular account status, address, subscription, price plan, or set of entitlements.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F7.webp",{"local":46},{"headline":49,"body":50,"imageUrl":51,"images":52},"Events describe something that happened: A customer placed","Events describe something that happened: A customer placed an order, opened an email, visited a product page, contacted support, changed a subscription, or interacted with a service. Both are important, because: If the profile contains only the current state, an AI application may lose important historical context. If it contains only raw events, every application has to reconstruct the current state itself.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F8.webp",{"local":51},{"headline":54,"body":55,"imageUrl":56,"images":57},"That leads to another architectural question: where should","That leads to another architectural question: where should the transformation from raw events to useful customer context happen? Suppose a customer has visited the same product category twelve times during the last month. The raw events might look something like this: An AI application may not need to process every individual event. It may be more useful to expose a derived signal such as: The important point is not that every customer profile should contain this exact type of signal.","\u002Fapi\u002Fmedia\u002Fposts\u002Fhow-to-build-an-ai-ready-customer-profile-3e05cdff\u002F9.webp",{"local":56},[59],"dev",[61],"Technology",{"name":63,"url":64},"Dev.to","https:\u002F\u002Fdev.to\u002Fgazerro\u002Fhow-to-build-an-ai-ready-customer-profile-1gkp","en",{"handle":67,"displayName":68},"spots","Spots","queued",{"views":71,"likes":72,"saves":72,"shares":72,"completions":72,"opens":72,"skips":72,"depthSum":72},3,0,"2026-09-28T16:17:40.361Z","local"]