The scope of sales operations and its relationship to marketing automation is another point of confusion along the sales-marketing frontier. The Wikipedia definition of sales operations is very broad and encompasses:
- Sales strategy: design, planning and execution.
- Measurement of results: reporting, analytics and sales data.
- Compensation, sales quota and policies.
- Technology and tools, including CRM.
- Training and sales communication.
- Sales territory design and optimization.
- Contests and spiffs.
- Lead generation and sales programs.
- Customer segmentation.
Sirius Decisions enhances this definition by pointing out three relatively new (but critical) roles within sales operations: quantitative analyst, compensation administrator and contract administrator. Others will undoubtedly be identified and defined in the not-too-distant future.
The key takeaway is the trend towards centralizing and optimizing, through specialization, key tactical processes that makes selling more efficient. The CallidusCloud product family and its focus on sales enablement fits nicely with this approach.
Although the sales operations term has been bandied about our industry for years, its instantiation as a formal function is relatively new. According to the Sales Operations Excellence Center, 54% of these groups are less than three years old.
One of the primary values of marketing automation is, of course, the alignment – if not unification – of an end-to-end selling cycle that encompasses both marketing and sales. Two natural areas of collaboration between sales operations and demand generation are:
- The allocation of marketing campaign resources based on expected bookings and revenue by region.
- Campaign theme planning and the allocation of demand generation resources based on product revenue numbers.
Marketing operations often prepares reports that focus on marketing’s key performance indicators, while sales operations produces reports that look at the pipeline and near-term business view. Combining both yields clarity that is more than the sum of its parts. Both organizations can understand and refine their contributions to the end-to-end value chain.
Other examples of information sharing include:
- Combining marketing’s pipeline (leads that are sourced and influenced by demand generation activities) with sales’ pipeline can yield great insights about dynamics such as velocity, volume and value. An activity snapshot coupled with an understanding of demand generation stimuli provides invaluable feedback to those responsible for tuning marketing processes.
- Matching pipeline investment to sales and revenues helps to tune forecast accuracy and therefore predictability. That quality, of course, is valued highly in the C-suite. Moreover, the holistic perspective helps both organizations to understand the true cost of generating sales and the impact of marketing’s front-end investments on revenue.
- Blending waterfall metrics (inquiries, qualified leads, etc.) with source and quality data from sales operations provides a more thorough understanding of lead characteristics that contribute to sales conversions. The feedback helps marketing to generate leads that the sales organizations want.