The secret to High Performing Sales Teams – Analytics

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53% of high performing sales organizations according to McKinsey effectively use analytics to deliver growth, efficiency and effectiveness.

Professional selling is a competitive sport.

The performance-based nature of the job is what attracts most people to this challenging and rewarding profession. Just like performance athletes needing the best gear and equipment to excel, sellers are in the quest for the right tools to stay on top of their game. Being able to visualize and benchmark performance against their targets and against teammates helps motivate them and drive the challenger mindset that is synonymous with sales success.

Now consider this dynamic – Customers are more aware than ever before and are choosing to take their own path towards evaluating and buying the products and solutions they need. This independent exploration coupled with data privacy and anti-spamming regulations like GDPR in Europe and CCPA in California are making it harder to reach customers.

These restrictions are making sellers reconsider their ‘spray and pray’ method of reaching out and interacting with customers to a more well thought out game plan to be effective. Sellers are desperate for insights that will help them understand the customer better so they can reach out at the right time and offer the right information needed to guide customers along their own journey.

The answer is analytics.

Insightful analytics help sellers understand performance, analyze opportunities and uncover hidden customer insights that can help them increase the odds of closing deals. Analytical sales organizations can identify true drivers of business growth and apply advanced analytics for a prescriptive set of actions that will help them win.

Across the sales organization analytics can be used in many ways.

Powerful, answers for professional sellers begin with insightful questions.

Empowering the field

Sellers want to know how they can sell better.

They want to be able to analyze their historic sales performance, evaluate what worked, and gain insights into activities they should focus on to succeed.

Starting with visibility

Compensation is arguably the biggest motivator for sales. Sellers are eager to keep a pulse on how they are doing and what they are going to get paid. But between the airport layovers and the sales calls, sellers find themselves struggling to keep track of performance and without access to analytics they can easily be blindsided. Being able to answer questions like ‘How much more sales do I need to make to achieve quota’ or ‘Did I get a credit for the big sale I made last month?’ easily gives them the clarity they need on performance, and the confidence in their compensation.

Forecasting performance

Selling comes with a great deal of uncertainty with deals that fall through the cracks for various reasons. While these unpredictable outcomes exist with conversion, sellers want to understand the impact that each of these scenarios can have on their attainment.

Looking at past sales trends and using ‘what-if’ modelling, they want to be able to answer questions like ‘Will I achieve my quota if I sell 50 more units of X?’ or ‘If I sell at the current rate, will I be eligible for the special annual bonus?’

Prioritizing actions

According to Hubspot, 60% of the customers only want to connect with sales during the consideration stage, after they have researched the options and come up with a short list. This leaves sellers with fewer opportunities to get it right. Sellers want to perform adequate due diligence themselves to make sure they have meaningful conversations every time they connect with customers.

They are desperate for a deeper understanding of the customer so they can prioritize their actions. Being able to answer questions like ‘Is there a way to know how much the customer buys each year, so I know their appetite to spend?’, ‘Is there seasonality in buying so I can contact the customer at the right time?’, ‘Which accounts are faster to close?’ provides sellers a deeper insight about actions that drive the best outcome.

By 2022, two-thirds of sales leaders will begin considering a new generation of sales analytics and applications designed to improve performance and productivity.

Mark Smith, CEO & Chief Research officer, ventana research

Driving team performance

Sales managers want to know how their team can perform better.

They want to be able to be able to analyze team and individual performance, understand gaps and gain insights into actions they should take to set their team up for success.

Assessing risk

The one thing that keeps sales managers up at night is the fear of their team not achieving their targets. A sales manager is keen on understanding the health of the sales pipeline and risks involved in her team achieving their targets. Being able to answer questions like ‘Which of my territories are at risk of attaining targets?’ and ‘How many of these open opportunities will convert?’ helps her identify areas where her team might fall short of the revenue goals.

Improving performance

Sales managers are looking for ways to constantly improve the performance of the team. They are keen on identifying bottlenecks and fixing them so the productivity of the team can be optimized. Being able to answer question like ‘What are the specific areas where Brian needs coaching?’ and ‘Is territory A understaffed?’ helps sales mangers put an action plan in place to drive performance.

Instilling a competitive mindset

Sales managers want to drive healthy competition among their sellers. The want to know how gamification and other short-term incentive programs help in driving performance and healthy competition.

Maximising operational efficiency

Sales operations want to know how they can make their sales team more efficient.

They want to use analytics to optimize their sales processes and drive sales effectiveness.

Harnessing the right KPIs

Sales operations wants to know how they can drive the right sales behavior and motivation. They want to be able to analyze key elements of the compensation plan and evaluate how they influence sales behavior. Being able to answer questions like ‘Should the commission be volume-based or margin-based for product X?’ helps then identify key drivers of performance.

Forecasting sales

There are several factors that affect the dynamic of the sales organization for e.g., seller churn, territory shifts, compensation plan changes etc., Sales operations are desperate to predict the outcomes these changes have on quota attainment. They want to be able to model various scenarios and understand the impact. For instance, ‘What will be the impact to quota attainment for team B if 20 accounts were removed from their territory?’

Diving deeper with advanced analytics

Organizations with good analytical foundations in place are able to find more predictive and prescriptive uses of analytics, improving decision making with greater accuracy. Some of the applications include:

Seller churn

Maintaining sales capacity and territory coverage is essential to delivering on the revenue goals of the organization. Sales leadership is keen on understanding when and why sellers leave so they can implement measures to address churn and ensure adequate staffing.

Predictive models help analyze relationships between seller attrition and sales tenure, ramp up timelines, amount of training, quota achievement etc.,

Customer churn

It is often assumed that profitability is related to growth in the customer base, but the cost of acquiring a new customer is five times more than the cost of retaining one. As organizations get more maniacally focused on customer retention, they are looking for insights into what causes churn.

Analyzing customer behavior, transaction data, demographic data and usage patterns, companies can find key motivators and detractors along the customer journey and use actionable insight to implement strategies for retention. The telecom industry is a good example where sales teams offer personalized a la carte plans based on the customer profile, past usage patterns and churn risk.

Advanced analytics also helps in building predictive churn models that extrapolate these data sets and understand potential churn rates in the future.

Propensity to buy

Sales organizations want to focus their efforts on accounts that are ready to purchase. With analytics, organizations can build scoring and grading models to classify accounts using data from various sources like firmographics, historic sales, digital interactions etc., allowing sales to pivot focus to accounts that have a higher propensity to buy.

Accurate Target setting

Organizations want to be able to set accurate sales targets bases on actual potential and not just set targets incrementally on historic performance. Analytics helps them better predict customer behavior looking at historic buying patterns and can supplement that data into the quota planning processes, making targets more accurate and equitable.

Next best action modelling

Analytics helps model and predict a customer’s likelihood to respond to certain offers, allowing them to optimize their next actions – be it the next best marketing offer, or the next best product to cross-sell.

Conclusion

Strong analytics provides sellers a competitive advantage. It empowers them to become more efficient and productive in accomplishing their job. By turning data into action insight, decisions can be made with less gut feel and more clarity than ever before, allowing sales teams to focus their time and effort on actions that drive better business outcomes.

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