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5 Ways Commercial Analytics Can Help Your Sales Team

Strategy   |   Alteryx   |   Jan 28, 2020

Sales is often referred to as a mix of art and science – a numbers game of volume and velocity and ratios, paired with the human element of one person connecting with another and encouraging them to try something new. When it comes to executing the science portion of sales, effective use of sales analytics is highly correlated to success. In fact, in a survey of over 1,000 global sales organizations, 53% of “high-performing” companies rated themselves as efficient and regular users of sales analytics(1).

 

Sales analytics (often called commercial analytics in the Pharmaceutical industry) is all about identifying, modeling, understanding, and predicting sales trends, in order to strengthen an organization’s abilities to improve overall sales results. Or put another way, sales analytics helps teams to understand past results and monitor present conditions so they can determine the best course of action for future sales improvement.

 

How Sales Analytics Increase Sales Profitability

Sales Analytics can help sales teams and sales reps improve their performance in several key areas of the sales process.

 

1. Planning

Analytics can provide a good baseline understanding of sales volume and distribution (by geography, industry, product type, client size, competitors, etc.) from recent past periods. This will help managers and sales leaders make sound projections about the direction of future sales trends. Managers depend on this insight to determine the right type and quantity of resources needed for the sales team to maximize the opportunity in front of them, and how to allocate those resources for maximum effect. Individual sales reps can use a similar approach to create a plan for how to optimize their own territory results.

 

2. Goal-Setting and Team Motivation

Properly set goals can motivate a sales team to maximize their efforts and to reach their true potential. But if goals are set too high, sales reps can become demotivated and are at a greater risk for attrition. The resulting loss of sales reps ultimately reduces sales outcomes and drives up the cost of sales, due to uncovered sales territories, the cost of recruiting and training replacement reps, and reduced productivity while those new ramps are ramping up. And if goals are set too low, it can dramatically impact the cost structure of a sales organization by artificially inflating commissions. That doesn’t sound too bad to a sales rep, but it can significantly erode trust for sales leaders among the rest of the executive leadership team in a company (as a fun exercise, ask your CFO how they feel about low sales targets!).

 

3. Prioritization

A well-designed data analytics program can utilize the spending history of existing customers and their key characteristics to help you target the prospects that best match your most profitable customers. Using this information wisely can help make decisions about which customer demographics to prioritize and which accounts to target. By combining customer history with sales team territory coverage data, managers can also refocus coverage areas to determine where individual sales reps should concentrate their time and efforts to increase overall team performance.

 

4. Finding Patterns and Refining Sales Approaches

Sales analytics can help managers and sales teams to identify which strategies are effectively contributing to sales and which strategies are holding the team back. When used regularly as a quality control feedback loop, sales analytics support refinement and revisions of team prioritization and strategies. Routine examination of internal sales data compared with third-party, industry-specific data can also help teams benchmark their performance and identify new opportunities. By combining both data sources into analytical approaches, sales teams can identify new approaches and underserved markets.

 

5. Monitoring Progress and Motivating The Team

Combining a real-time analytical approach with sales data provides an added edge for sales teams. Team members receive up-to-date information regarding sales patterns and performance metrics that can shape robust, targeted sales strategies and minimize wasted time.

 

Sales analytics can also be an excellent motivational tool for sales teams. By making performance metrics visible and accessible, sales teams can track progress towards team and individual goals. Transparent sales analytics programs can tap into the competitive nature of many sales reps who want to be on top of the leaderboard, and motivate everyone on the team to outperform goals.

 

To achieve the many potential benefits of sales analytics, you first have to have the right tools in place to capture the data and deliver the insights to the sales and management teams.

 

Setting the Stage for Sales Analytics

To achieve the many potential benefits of sales analytics, you first have to have the right tools in place to capture the data and deliver the insights to the sales and management teams. Getting the underlying infrastructure in place is often where sales leaders need to turn to their partners in sales operations or IT. For that conversation to go well, it’s important to have some understanding of the types of options available.

 

A good place to start is by surfacing data that is generated internally by your own sales team, such as sales rep activity, deal stage progression, conversion ratios and close rates. This data often lives in a single place, your CRM system. That eliminates the task of gathering and combining data from multiple systems, and allows teams to focus on the kind of calculations and presentation of data that is most useful. Be sure you are enforcing good hygiene for how your sales team keeps the CRM system up to date if you hope to get value from the data in they system. For sales analytics that are based solely on data from your CRM, there are many good choices in the market and the launch of analytics can usually be managed by a sales operations team. You can find several good options in the Salesforce AppExchange, or if you are using a different CRM, there’s a good chance that vendor offers an analytics option too.

 

Sometimes you need to combine data from several sources, and can’t rely on CRM data alone. For example, sales figures of your own product in the Pharmaceutical industry typically come from external sources, and sales analytics without that data would be of very limited use. In Pharma, your competitors’ sales data may be available from third party sources as well, and enhancing your own sales analytics with that data provides a powerful opportunity for insight that you won’t want to miss. Once you decide to combine data from multiple sources the underlying infrastructure process can get much trickier, often posing up to 80% of the time and effort required to launch a sales analytics project. In these instances, companies often need something like a data warehouse or standalone data analytics app. To continue the Pharmaceutical industry example, this can mean hiring large internal IT teams with a specialty in “commercial” data warehouses, or handing control and buckets of money to an external service provider. Another approach is pre-built but flexible industry specific sales analytics, (why yes, like the one offered by my company, Lore IO – Commercial Analytics for Life Sciences).

 

As markets become more competitive and buyers become more savvy, companies can gain an edge by utilizing data analytics to improve the effectiveness of their sales efforts. The right data analytics approach will provide both guidance for sales teams and important answers for organization leadership. Over the next decade, expect effective use of sales analytics to distinguish highly successful organizations from their competitors.

 

 

1) Atkins, Charles; Valdivieso De Uster, Maria; Mahdavian, Mitra; and Yee, Lareina. “Unlocking the power of data in sales.” McKinsey & Company, December 2016, https://www.mckinsey.com/business-functions/marketing-and-sales/our-insights/unlocking-the-power-of-data-in-sales

 

 

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