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Data and analytics are key to moving from a sales culture that makes decisions based on intuition to an organization that makes strategic decisions.
Nov 22, 2019
A great sales forecast requires analyzing data, such as, CRM data, financial data, including all product margins, and external data which could include industry-specific data sources and market trends.
We recommend that you begin with your historical data to create benchmarks. Then, it's important to determine if there are future conditions that will impact your forecast. For example:
- Are you changing your pricing?
- Are you increasing your sales team or running more promotions that could result in new customers?
- Are you going to explore new or different channels?
- Are you introducing new products or services?
Discover how to achieve agile decision-making in less time.
Next, use Advanced Analytics tools to do predictive analysis of this data to find patterns that can identify risks and opportunities in the future. One role of these tools is capturing relationships among different factors and to assess risk with a particular set of specified conditions, and then assign a score to the risk assessment. From this information, the sales team can take this assessment and target opportunities with higher scores. This allows sales teams to more effectively manage their time, and improve overall sales performance by accurately targeting the best opportunities.
The final key to a great sales forecast is an expert analyst who specializes in your business and industry, and understands all current and future conditions that influence sales.
The proper analysis of data will result in:
- A more comprehensive sales forecast
- The ability to detect possible cannibalization between products
- The knowledge of product, or groups of products that are trending
- An agile territory analysis
- The ability to predict resource and growth allocation
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