Forecasting is a very complex topic, and forecasting processes can vary wildly across different businesses. To ensure accurate predictions, it is crucial to have an effective forecasting tool that can adapt to your specific business needs, sales processes, and cadence of forecasting.
In this article, we’ll dive into multiple use cases to drive ROI (return on investment), plus best practices to ensure the success of your forecasting setup.
Salesforce Forecasting Use Cases
New Business vs. Existing Business
Nurturing existing customers and acquiring new customers are two distinct strategies that businesses use to grow and maintain their revenue. Each approach has its own focus, benefits, and challenges.
Typically, acquiring a new customer costs five times more than retaining an existing customer, and the sales process is often longer and more resource-intensive. It’s estimated that you have a 60-70% chance of success when selling to an existing customer versus a 5-20% chance of success selling to a new customer. It’s important to factor this in when setting up forecasting in Salesforce, and a way to do this effectively is to forecast new and existing business separately using Forecast Types.
Forecasting by Delivery Dates
Forecasting by product delivery dates in Salesforce can be a valuable approach to predict and manage your sales based on when products are expected to be delivered to customers. Use cases might include subscription items such as magazines that are delivered on a monthly basis.
This method allows you to estimate the amount of stock needed or revenue based on the timing of product deliveries, which is particularly relevant for businesses with longer sales cycles or when product availability significantly affects sales.
Forecasting by Revenue Schedule Date
Forecasting by Revenue Schedule Date in Salesforce allows businesses to predict and manage their revenue based on the specific schedule dates when payments or revenue recognition are expected.
This is particularly useful for companies that deal with subscription-based services, recurring revenue models, or contracts with multiple payment installments. Use cases include subscriptions to SaaS products such as Salesforce, Amazon Prime, or Netflix.
Forecasting by Revenue Schedule Date provides a more granular and accurate view of cash flow and revenue realization over time. In Salesforce, this can be achieved using line item schedules.
Forecasting with Team Selling
Splits allow you to allocate contributions by total Opportunity Amount or by product amounts when multiple sales teams are involved, for example, overlay teams, product specialists, and solution engineers. These teams can forecast off these split amounts instead of the total opportunity amount.
You’ll need to enable Opportunity Teams as a first step.
Once Opportunity Teams are enabled, you’ll set up Opportunity Splits. Opportunity Splits have been around for a while, but Product Splits was a new addition in the Summer ‘23 release. This functionality offers an even greater granular definition of splits, allowing percentages to be distributed between team members at the Opportunity Product level.
Both Opportunity Splits and Product Splits can be easily added to an Opportunity and edited directly from the Opportunity Splits Lightning Component, and once Product Splits are defined, the Opportunity Split percentage is automatically recalculated. Opportunity Splits are locked and can’t be edited when Opportunity Product Splits are defined for a given Opportunity.
As you would expect, this data is fully reportable and forecastable, allowing the operations teams to deep dive and organize the data by user, product, role, and so on.
For example, if a new product is launched to a limited number of customers, you can easily note the associated revenue, as well as different team contributions, varying from sellers to – why not – even dedicated product marketing managers who contributed to the deal.
Salesforce Forecasting Best Practices
Before you start creating or tweaking your forecasts, there are a few best practices to remember for optimal results.
- Go back to basics and evaluate your company’s maturity and data quality. Artificial intelligence (and humans) can’t work with bad data. So, first things first, how are you enforcing good data hygiene, and should you consider a data cleansing project prior to your forecasting setup?
- Review and document existing processes and simplify where possible. This means asking “why” and streamlining.
- Collaborate with stakeholders and define what needs to be measured. For example, are you measuring revenue, products, or both?
- Decide if single or cumulative forecasts suit your business best.
- Try to standardize your processes across the business. Keep in mind that by default, you can only create four Forecast Types (although this can be extended by contacting Salesforce).
- Use Quotas in addition to Forecasts to take advantage of the more visually appealing features of forecasting! Sales users typically respond best to targets and an interface that offers them all the information they need at a glance.
- Don’t wait until the end of the month or quarter to check your forecast. Get into the habit of checking your forecast early in the month or quarter for insight into future issues such as insufficient pipeline coverage. Forecasting shouldn’t be used as a tool to berate the sales team. Instead, it should be used to help them identify at-risk pipelines and determine next steps.
- If this is your first time implementing forecasting, consider starting with a small pilot group and iterating frequently. You can then roll out to further groups of users. Going live with a minimum viable product (MVP) to a small group will enable you to identify issues early and reduce onboarding efforts.
- Don’t aim for perfection! As with all projects, there will be learnings and adjustments as you go along. Keep the business and key stakeholders engaged throughout the implementation to create and maintain trust and positivity.
- Don’t fail at the final hurdle – no matter how fantastic your implementation of Salesforce Forecasting is, you need user buy-in and adoption for a successful project. Run training sessions for different types of users and provide documentation.
Salesforce has significantly enhanced Salesforce Forecasting over the past few years, so now is the perfect time to implement (or reevaluate) your existing forecasting!
Don’t forget to gather the requirements from the business before you begin, and be sure your data hygiene is tip-top before you launch – dirty data is guaranteed to torpedo the success of your forecasting implementation.
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