Customer 360

Customer 360 is the single, unified view of a customer that consolidates, in one profile, all the data and interactions a company has with that person or account: the sales opportunities, the marketing campaigns they received, the support cases they opened, the purchases they made and any other touchpoint. The central idea is that every team (sales, marketing, service, finance) sees the same customer in the same way, with no contradictory versions depending on which system they check.

The term was born as Salesforce's platform vision: connecting its different clouds (sales, service, marketing, commerce) on a shared data model to solve the classic problem of siloed data. In practice, building a Customer 360 on Salesforce means integrating internal and external sources and resolving duplicate identities, so that "John Smith" in the sales database and "j.smith" in the online store are recognized as the same person.

It is not a single product you plug in and you are done: it is an architectural approach. It requires integration between systems, data quality rules to avoid dirty records and a layer that unifies identities, usually supported by tools such as Data 360 (formerly Data Cloud).

Why Customer 360 matters

Most companies do not suffer from a lack of customer data, but from having it spread across systems that do not talk to each other. The sales team looks at the CRM, marketing at its campaign platform, support at its help desk and finance at its ERP. Each one has a slice of the truth and none has the full picture. The result is inconsistent experiences: offering a product the customer already bought, asking for the same information three times or failing to notice that a "loyal" customer has been filing complaints for months. Customer 360 tackles exactly that: putting the customer's entire history in one place so that every decision, automation or conversation starts from the same information.

How it is built in practice

Building a Customer 360 is not a one-day project; it is a sequence of layers stacked one on top of another:

• Identify the sources: CRM, e-commerce, ERP, marketing platform, support system, WhatsApp Business API data and legacy spreadsheets.
• Integrate and move the data: through point-to-point integration, an iPaaS layer or ETL processes that bring the information to a common place.
• Clean and normalize: apply data quality rules to fix formats, complete fields and discard junk records.
• Resolve identities: detect and merge duplicates so that each real customer has a single profile, not five fragments.
• Unify and expose: make the consolidated profile available for sales, marketing and service to consume, ideally as a single source of truth.

A concrete example in Argentina

Consider a consumer goods distributor in Buenos Aires that sells both through the traditional channel (corner stores, kiosks) and through its online store. Without Customer 360, when a kiosk owner calls with a complaint, the support agent does not know that this same person bought ARS 400,000 on the website last month or that they have an open opportunity in the CRM. With a well-built Customer 360, the agent sees order history, pending payments, previous cases and the campaigns they received on a single screen. That changes the conversation: it stops being an isolated complaint and becomes serving a valuable customer with full context. The same unified profile keeps marketing from sending an acquisition promo to someone who is already an active customer.

Customer 360 vs CRM and Data 360

These three concepts are often confused. The CRM is the system where commercial relationships are managed; Customer 360 is the broad vision that goes beyond the CRM and incorporates marketing, commerce and service; and Data 360 (formerly Data Cloud) is one of the technology tools that makes that unification possible at scale.

Common mistakes when implementing it

The first mistake is believing that buying the technology is enough: without data governance, Customer 360 fills up with duplicates and ends up being one more source nobody trusts. The second is trying to integrate everything at once; it is better to start with the two or three sources that add the most value (for example, CRM and e-commerce) and grow in stages. The third is forgetting identity resolution: if duplicates are not merged, the "single view" shows split profiles and the team loses trust. And the fourth is underestimating the cultural change: the full picture is of little use if each team keeps working in its usual system.

Done right, Customer 360 becomes the foundation for personalization, predictive analytics and, more and more, AI agents, which need reliable, unified data to respond with real context about each customer.