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            Increase Global Pipeline and Forecast Visibility with Data 360

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            Increase Global Pipeline and Forecast Visibility with Data 360

            Use Sales and Data 360 together to see all your revenue predictions and to track different types of income, such as sales, billing, and ad purchases. Compare your forecasts with actual results to make smart adjustments for more accurate forecasts, engage with the right customers to close deals, alter account strategies, and boost your pipeline to meet your sales goals.

            Required Editions

            Available in: Lightning Experience
            Available in: Enterprise, Performance, Unlimited, and Developer Editions

            To get the whole picture about your forecast and the pipeline that’s there to fill it, gather and prepare data from these possible sources.

            Data Type Examples
            Sales and service data from Salesforce
            • Leads
            • Opportunities
            • Accounts
            • Open service cases (if you use Service)
            Revenue and marketing data from Salesforce
            • Past purchase activity (if you use Revenue Management)
            • Billing and subscriptions (if you use Revenue Management)
            • Website engagement (if you use Marketing)

            Depending on your Salesforce setup, some of this data can be available from external sources.
            Third-party data
            • Inventory and fulfillment status
            • Consumption rates
            • Conference attendance and webinar engagement
            • Customer survey results
            • Social media sentiment
            Systems and assets data
            • Network information
            • System performance
            • Device information

            Combining this data means you can create insights that help to predict your potential sales. These insights are just a few examples.

            • Customer satisfaction. Use your past purchase data with your service case, consumption, and customer survey data to assess overall customer happiness with your products and services, which can influence their potential to buy more.
            • Calculated run rate. Use your Salesforce opportunity data with your billing and shipping data to predict your revenue for the year.
            • Likelihood to Close. Use your Salesforce opportunity data with your consumption rate, past purchases, inventory, and seasonal sales trends to make sure you’re engaging with the customers most likely to close the deal.
            • Propensity to buy. Use your Salesforce opportunity data with past purchase history, conference and webinar attendance, and web engagement data to determine a customer’s interest, propensity, and when they’re likely to make their next purchase.
            • Seasonal Sales Trends. Use your past purchase data with your inventory data to determine whether the inventory on hand meets potential demands and whether enough pipeline exists to meet your forecast during a busy season.

            Task 1: Configure Users for Data 360

            To work with external data in Salesforce, ensure that Data 360 is set up and provisioned in your Salesforce org.

            Assign Data 360 permission sets to any users that need access to Data 360.

            Task 2: Connect and Map Your Data Sources to Data 360

            To bring your data together, connect your data sources in Data 360. Data sources are the places that hold your data. Those places can be Salesforce for lead and opportunity data or third-party sources such as Google Storage or Amazon S3 for conference attendance and webinar engagement. Make a list of where your external data comes from and who has access and credentials to that data.

            How you connect your data to Data 360 depends on where the data is coming from. To make sure your data source can be connected to Data 360, review the available Data 360 connectors and integrations.

            1. Connect and map your sales and service data.
              1. Set up a Salesforce connection in Data 360.
              2. Install a standard data bundle for Sales and for Service.
              3. To begin the flow of data to Data 360, create a data stream.
              The standard data bundles automatically map Salesforce standard objects to

              Data 360

              standard data model objects (DMOs). See Sales and Service Data Bundle Mappings.
            2. Connect and map your third-party data sources.
              1. Configure third-party data sources by using a connector service or a pre-built connector or integration in Data Cloud Setup.
                You can also connect data using the Bring Your Own Lake (BYOL) Data Federation in

                Data 360

                .
              2. Create a data stream for each of the external data sources. See Data Sources in Data 360.
              3. For each external source, map your data to DMOs. Make sure you map all fields that are required for your business.

            For data available in other areas, explore the connectors and connector services available. If a connector or service isn’t available, manually ingest the data and map your data accordingly.

            Task 3: Unify Your Data into Profiles

            Consolidate your data from all your sources into a comprehensive view of your customers and accounts. From that customer view, you can start to learn more about that customer’s buying trends and how they fit into your forecast.

            1. Create an identity resolution ruleset.
            2. Add match rules.
            3. Run the ruleset and then view unified profile results in Profile Explorer.

            Task 4: Analyze Data with Calculated Insights

            With all your data now safely in Data 360, you’re ready to build the insights that join your data together. For example, create insights that correlate past purchasing patterns from customers with open opportunities, or take a closer look at subscription and web engagement data to determine what upsell or cross-selling opportunities can boost your pipeline.

            Each insight you create provides better visibility into your pipeline and forecast so you can make forecast adjustments and engage with the right customers to ensure key deals close on time. Knowing exactly where your forecast stands gives you time to update your account strategies to increase your pipeline to ensure you hit your forecast goal.

            Sales leaders work together to decide which metrics and insights they need and help to identify what data is needed to arrive at that metric. For example, to see the total amount spent by a customer, which can influence future spending habits and your pipeline, you need the customer’s past purchase data.

            1. Create the calculated insight.
            2. Verify the insight in Data Explorer.
              To verify the calculation, run or schedule the SQL job.

            See Enhance Data in Data Cloud in Trailhead to learn more about the types of insights available and how to build your insight expressions.

            What’s Next

            Now that your data is connected together, you can bring the power of that data across Salesforce. Here are a few suggested next steps.

            • Segment data into target customer sets. Based on what you find after unifying your data and looking closely at the insights it provides, you can segment your data. For example, create segments for high probability to close or greatest upsell opportunities. These segments can be used to build email campaigns or to create a report or dashboard for sales leaders that can be useful when forecasting.
            • Enrich Sales records with insights. Provide your sales team access to the calculated insights data on account, contact, or lead records.
            • Do more analysis with Tableau. Use Tableau to find useful and actionable insights that can drive business success and create a personalized experience for your customers. Data 360, Tableau, and Salesforce 360 apps work together to consolidate your data and create a single customer record.
             
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