Sales Cloud is the world’s leading sales platform, helping businesses identify growth opportunities and manage complex client orders. Like all software, you’ll need to provide Sales Cloud with tidy data and clear relationships so it can run processes seamlessly.
We’ve spoken about cleansing and importing data into Sales Cloud before in previous articles (some of which we go even more in-depth). Today we’ll focus on your Salesforce Sales Cloud data model: covering key topics like ‘what is a data model, and what does it do?’.
Creating a data model can be challenging for businesses keen to leverage the full power of Sales Cloud but unsure of where to start. Read our how-to guide on creating an adaptive data model for your business and gain oversight into your sales performance.
What is a data model in Salesforce Sales Cloud?
Data models are how you instruct software to use and record data. If you’ve been using spreadsheets until now, you’ve already been using a type of data model (after a fashion), called a flat database.
Flat databases record data in rows and columns, meaning it can be difficult to draw data from external sources or create elaborate processes. The next evolution in data modelling comes in the form of relational databases. Relational databases hold data just like flat databases (with fixed fields for certain types of information like addresses and phone numbers) but can go further by recording the connections your data has to other internal records or external organisations using objects.
Objects are how to label your data (like the column title in a spreadsheet) and are made up of fields (like rows and cells). Data models specify how you want to connect objects and data contained within the fields.
If you have external or legacy data sources, you can use APIs (application programme interfaces) to bridge the gap and carry information between parts of your model for later processing.
How to create a data model in Salesforce Sales Cloud
Sales Cloud offers an out of the box data model via standard objects and fields. These objects cover data points that Salesforce knows are commonplace within businesses, like contact details and delivery information for customers.
However, you can also create custom objects to build a tailored data model with unique data and relationships. Doing so allows you to create an adaptive data model of your business to learn from and refine your strategy.
Step 1: Plan your data architecture
The first step in creating a Salesforce Sales Cloud data model is to plan, define and create important objects/fields for your data to populate.
Sales Cloud already covers the main culprits, so you’ll likely find that your data maps pretty well onto Sales Cloud out of the box. In doing so, Sales Cloud can also tell which data is related to others. For example, Sales Cloud will quickly gather which of your professional contacts are all from the same organisation.
However, identify some KPIs your business uses and consider how to measure them through data. Doing so will help you adapt your model later on and create a more efficient sales strategy. Make sure to capture all the input for your KPI so it’s an accurate measure of your performance. But only gather as much data as you need, as unnecessary objects and data can create unhelpful and inefficient clutter.
Step 2: Import data using Salesforce tools
The next step in your data model is to import your data into Sales Cloud.
Smaller businesses will likely be best placed using the Data Import Wizard. Data Import Wizard can handle up to 50,000 records at a time and automatically catches duplicate records — especially useful if you’re light on IT resources.
Data Loader is the tool for larger firms importing up to 5 million records at a time or data from a range of sources (like legacy databases or multiple office locations). Read more about the ins and outs of importing data into Sales Cloud in our dedicated guide.
Step 3: Use your KPI data to inform your future strategy
The final step in creating your adaptive data model is Salesforce Sales Cloud is about identifying bottlenecks and/or strategic opportunities and adapting your data model to take advantage of them.
At early stages, you should primarily be concerned whether your data model captures all you need it to (especially if you don’t have an IT department to help). From here, consider what your model shows from your performance: what’s good and bad about your business, and what can you do with the information.
For example, tweaking your data model to route niche customer questions to more experienced team members. Similarly, adding client-specific pricing structures can help your business address specific pain points throughout the sales process. In sum, you can use data to address specific and previously hidden problems within your business to quickly maximise your revenue.
Streamline your business with an efficient data model in Salesforce Sales Cloud
Data models run the engine of your business, so get the sports model with Salesforce Sales Cloud. Use the steps above to plan and reflect on your business performance, and access new insights to bottlenecks and strategic opportunities.
Discover how to get started with more of Sales Cloud in our dedicated guide and elevate your business with Salesforce today.
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