Introduction to Salesforce Data Cloud: a Customer Data Platform that's making a name for itself

This invaluable tool is based on four key principles:

Data collection

Gathering data from information systems of different types and origins (CRM, website, ERP, third-party data such as advertising or marketing targeting, etc.) on a single platform.

• A platform that can accommodate and connect to different data sources to adapt to the structural diversity of companies.

Customer profile harmonisation

Linking anonymous information to personally identifiable information from customer profiles using the "identity resolution" method. A system combining the analysis and cross-referencing of multiple data sources to create a unified, consistent and refined customer profile.

• A method that guarantees the respect and security of individual confidentiality, while enabling a company to reliably associate a set of anonymous data with an individual customer, thereby enriching their profile.

Data processing and segmentation

Cleansing reconciled data to obtain structured, harmonised, up-to-date and duplicate-free data. Then segment the cleaned data by defining customer clusters.

• A key preparation step that will then facilitate the construction and definition of intelligent, relevant and specific segmentations by customer or by attribute. This data could also be used and enhanced by a predictive tool to reinforce the relevance of targeting and facilitate decision-making by teams.

Activating customer initiatives

Reinforce and optimise the targeting of marketing initiatives by choosing the right communication channels. Audiences identified with the data platform can be activated and exploited through other related functionalities.

• Connected systems such as Marketing Cloud, Sales Cloud and Tableau can directly exploit customer information and recommendations to carry out appropriate actions, such as email campaigns, product recommendations, optimised sales paths, problem resolution, etc.
• Processed and segmented data can be exported by Data Cloud to other systems external to Salesforce to facilitate activation.

Use case 1: Optimizing customer service

A luxury brand wants to enhance its customer service by offering a unique and attentive experience to every person who contacts them. The after-sales service is mostly contacted by demanding customers who are not satisfied with a product or service. It must respond quickly to highly codified quality criteria and offer a seamless customer experience as exceptional as in-store.

A customer calls after an express delivery of a faulty product from their flagship store. Thanks to Data Cloud, when the call is received, the telephone advisor can view the customer's complete, harmonized profile live, without a complex interface or the need to access other information systems.

• Real time: Data Cloud gives you the advantage of near-real time. A delivery note was generated less than an hour ago by the delivery service and their courier. As the information is directly accessible from the customer file, the telephone advisor can confirm the context of the customer request without difficulty, and without leaving the conversation window.
• Intelligent marketing: The creation of a customer request is recorded by Data Cloud and automatically cancels the satisfaction survey scheduled for the first delivery. The customer will receive another campaign a few hours after receiving his new product.
• Transaction: A payment was made that morning by telephone for the purchase of a product and express delivery from the flagship store to the customer's home. This ERP information is accessible in Data Cloud by the after-sales service, which is then able to see the products and quantities ordered.
• A thoughtful gesture: Thanks to the harmonization and unification of data into a single customer profile, product preferences and recommendations are proposed to customer service via Einstein Copilot. A product sample tailored to the customer's wishes can be added to the next delivery as a token of attention.

With access to all the customer's transactional and behavioral data, as well as product data, the advisor's work is facilitated to best meet the customer's expectations. The customer experiences a fluid and coherent after-sales experience. 

Use case 2: proposing an adapted product assortment

A cosmetics laboratory wants to expand its product range in pharmacies. During a visit to a point of sale, pharmacists have very little time to devote to sales representatives, so visit preparation is a key factor in sales efficiency.

Data cloud has been set up to centralize customer information from the company's various departments (Sales, Marketing, Customer Service, Finance, etc.). A complete customer file is available to help sales reps prepare for their visits and provide rapid access to the information they need for their appointment:

• Segmentation: Pharmacy segmentation is classically based on criteria such as size, location and purchasing habits, thanks to Data Cloud's ability to integrate third-party data such as sell-out data supplied by IQVIA. Einstein's AI creates consistent segmentation based on this large volume of data.[HL1] 
• Next Best Offer: Using Product Information Management (PIM) and CRM customer information, a product recommendation is made, based on the pharmacy's segmentation, proposing a list of products likely to be ordered. A proposed selling price is displayed to optimize the pharmacist's margin.
• Campaign Pitch: Marketing campaigns are necessary to support the launch of a new product. The marketing pitch is written by Einstein GPT to support the sales person in his preparation. Beforehand, they have the right samples and technical data sheets for the beauty consultants present at the point of sale.
• Real Time: A customer service request was created 15 minutes ago, indicating that some of the products delivered this morning were in poor condition. Armed with this information, the sales assistant can reassure the customer and place a new order for these products at no extra cost.
• Pre-Credit Check: Customer risk has been pre-assessed and outstanding credit maximized just before the visit, so that the salesperson can place orders without constraints and make requests to the credit department.

The implementation of the new product ranges has been a success, and the appointment has been optimized for both pharmacists and sales staff.

Use case 3: Personalizing customer offers through marketing

A hotel group wants to improve the targeting of its marketing campaigns by offering content that is as personalized as possible. A customer is enquiring about his next reservation: he has consulted a group newsletter, read information on the website and, as part of his Premium status, contacted customer service to obtain more information about the services offered by one of the group's hotels.

Data Cloud will be able to leverage the associated customer data from these different sources (website, customer service) as well as others (purchase history, CRM customer profile, etc.) to retrace the path followed and personalize the next interaction between the customer and the hotel group.

• Segmentation: Enriched and advanced categorization according to various possible attributes: preference, loyalty program, last booking date, by destination/hotel, ... Data Cloud offers the opportunity to target customers with greater relevance for future activations and to associate the customer with a precise segment.
• External marketing activation: The generated segmentation is exported by Data Cloud outside Salesforce to the group's Marketing Automation system to share a targeted and effective e-mail campaign.
• Digital hyper-personalization: Customers can be tracked throughout their journey. They receive and open an email containing a promotion code linked to their loyalty program. When they return to the hotel group's website, the discount is visible because the web content has been adapted to the email.
• Campaign intelligence analysis: A few days later, the marketing director can consult the analyses built up in Tableau in Slack. They can thus visualize the impact of the promotional campaign in real time.