Every sales transaction is like a Roman candle: It shoots off all sorts of sparks in the form of newly created data that can be analyzed and used to ignite further sales and ongoing sales performance. This wealth of post-sales data is different from the pre-sales data housed in CRM systems, but it is just as valuable -- that is, if it can be captured and use systematically.
Pre-sales data can be somewhat conjectural at the start: "We may be able to sell to these prospects," or "these people are probably the right influencers." As the selling cycle progresses, pre-sales data solidifies into something more factual: "These guys are definitely interested in this product," and "we've had specific person-to-person meetings and outcomes."
In contrast, post-sales data is factual right out of the gate: "We sold these products to this customer, at these prices, with these terms. Here's how each person who touched the sale was compensated." End of story? Not quite.
Post-sales data is not an endpoint -- it's just the beginning. On a strategic level, post-sales data can provide insight into several areas including:
- selling patterns;
- commission spend;
- individual and team performance; and
- territory performance.
When combined with pre-sales data in CRM systems, post-sales data can provide tactical, fact-based guidance to those in the field, helping them make the right (i.e., the most profitable) decisions about where to focus their best selling efforts.
The problem, however, is that most organizations have a tough time getting their arms around post-sales data. Companies can't use what they can't collect. Collecting this data, however, is a major challenge because it lives in various back-office systems and applications, from inventory and shipping to human resources and payroll.
In order to meet this fundamental challenge, companies need a roadmap that includes essential best practices for driving sales performance with post-sales data and analytics.
Start With Compensation
The data used to determine a sales representative's commission on each deal is the same data that drives post-sales analytics. Most companies still use spreadsheets to manually manage the information needed to calculate commissions. Unfortunately, this method can be:
- open to human error;
- difficult to scale; and
- deprived of analytical capabilities.
But evolving the sales compensation management process from spreadsheets to one of today's next-generation, on-demand applications can automate the collection of timely post-sales data across all relevant systems in the company. This data, when integrated and cleansed based on the rules of compensation, is what companies need for timely and effective post-sales analytics.
At the same time, implementing these applications can help companies streamline their sales compensation processes, enabling real-time visibility into compensation plans and attainment of the sales representatives, while eliminating the time burdens, costs, and errors associated with manually administering compensation.
Implement an Analytics Overlay
With post-sales data now consolidated and cleansed, businesses can run more effectively once the following roles have access to the information:
- top executives;
- sales management;
- sales operations, and
For example, using dashboard-driven analytics, top management can track key sales performance indicators. Sales management can gauge the effectiveness of sales incentives, quickly see who is making the highest-margin deals, and track individual and team success. Sales operations can monitor the compensation process for exceptions and abnormalities and create analytic reports for management. Finance can keep an eye on commissions as a percentage of sales, and analyze the roll-up results of the sales organization.
The net result of these and other analytic activities enables better visibility across the sales organization, benefits of which include:
- an accurate and up-to-date representation of what is really happening in the field;
- the creation of more effective business strategies and tactics; and
- the ability to continually fine tune sales operations and improve sales performance.
Leverage the CRM Application
Post-sales analytics can also be combined with the pre-sales data in the CRM system to guide sales behaviors in real time. For example, a real-time analytics capability can be embedded onto the Salesforce.com application, allowing reps to run "what if" scenarios on live opportunity data. Thus, reps can easily determine which deals will deliver the best commissions payout and how to structure their deals to maximize that payout. Further benefits of combining pre-sales and post-sales data are:
- improved sales pipeline analysis;
- more effective sales forecasting and planning; and
- and a faster, easier way to determine total cost of sales.
This Can Be Done Today
None of the above scenarios and practices are "pie in the sky." Robust sales performance management (SPM) solutions, and applications for sales compensation management and post-sales analytics, are already available today.
Like CRM applications, SPM solutions are becoming more economical and can be rapidly deployed and easily integrated as a software-as-a-service (SaaS)-based application and service. Links between these on-demand solutions and leading on-demand CRM solutions such as Salesforce.com are easily and seamlessly integrated, and even include the convenient advantage of having a single sign-on.
About the Author
Christopher W. Cabrera (firstname.lastname@example.org), founder, president, and chief executive officer of Xactly, has over two decades of successful senior management experience. He is a noted industry expert in issues relating to sales performance management, sales compensation, enterprise, and on-demand delivery models. He is the coauthor of Xactly Sales Compensation for Dummies.
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