Why 14% of Sellers Dominate and How Automation Levels the Field

The top 14% of sales people drive 80% of revenue growth. It’s the Pareto Principle on steroids. Meanwhile, 80% of data in CRMs is rubbish. These are just two of the insights from the annual Ebsta Pavilion Go-to-Market Benchmarks report, which is a treasure trove of sales data.

The analysis covers 655,000 opportunities worth $48 billion. Half of the deals analysed are worth $10-50,000. Two-thirds of the companies surveyed have either 51-250, or 251-500 employees. These are the sweet spots for scaling companies in any industry.

The main conclusions I draw are that the top sales people focus on human relationships, and the top organisations focus on automation. One enables the other. In this post I’ll hit the highpoints of the data and why three automations in particular are a great place to start.

What makes a top salesperson?

This year’s survey reveals the largest gap on record between the top and bottom performing sales people. Effective automation is widening the gap because it allows an improved analysis of the sales process. A narrow focus on what works and making it better beats a volume-based approach covering every channel from every angle.

A common theme of the annual benchmarks is that sales people miss quota. Targets are unrealistic because sales people lack the tools to do their job and are not focused on what works. The average salesperson spends under two hours a day with customers. The top performers at AI-enabled companies dedicate more than twice that time.

Top performers outperform in four areas. They work on 2.6x more deals, with 76% higher value, have a 43% better win rate and 42% shorter sales cycle. These metrics combine to make them 11x more effective than the bottom performers.

The traditional sales cycle was shaped by Customer Relationship Management software, such as Salesforce. It focuses on role-based selling, meaning a person’s job title determined the sales service they received. This is giving way to a more personalised service focused on key decision makers.

Getting to the decision makers early improves the deal win rate by 55%. Remaining engaged with these stakeholders results in four times the success. A top dealmaker is skilled in discovery, qualification and maintaining senior relationships, and does not discount. This last skill alone saves a quarter of negotiation time with new clients and half with existing.

The full-cycle model, where sales people are involved throughout the process from discovery to nurturing clients, is gaining in popularity. 45% of companies, responsible for 52% of revenue analysed in the survey, adopt this approach.

What makes a top sales organisation?

Salesforce may have pioneered the data-driven sales era but it admits that four-fifths of the data in CRMs is useless. This is critical because quality data is necessary to automate the sales process. People are bogged down by manual tasks and changing that is the number one priority of companies adopting AI in sales.

A core problem is that 44% of sales contacts are not recorded in the CRM. A quarter of them are C-suite stakeholders. Sales people too often view the data collection process as big brother watching over them, rather than a means to more deals. Adopting AI is about changing that perception.

Ebsta Pavilion highlight 20 metrics to track to improve lead generation, deal closing, customer retention, and upselling. There are three things to focus on to get started.

The first is data quality. It must be easy to capture data about contacts and companies to avoid hours of manual data inputting. Automations that record meetings and messages, and upload them to CRMs are essential services.

With quality data, you can track involvement of people at each step of the sales process. The average new B2B sale involves eight people, and even upselling to existing clients involves five. How many contacts do your sales people keep?

Finally, examine where the decision-maker at a buyer disengages from the process. It is essential to do this with AI, as humans may not spot when problems start.

Better data, a full-cycle sales model, and focus on the decision-maker, should be enough to make a material difference to your sales success rate. Thereafter, you can work on gradual adoption of the remaining metrics, starting in the area where your organisation is weakest.

Automation and Investment

For all the change that AI and automation brings to the sales process, the old truths of selling remain. Most sales people miss quota because customers are unqualified, engagement with stakeholders is poor, and deals take too long to close. Automated analysis of deal pipelines enables management to track live deals against benchmarks, and to see who and which deals are failing.

I will leave the last words to Ebsta Pavilion. Efficient, rapid and sustainable sales growth comes down to three things. Automate wisely, refine your processes, and invest in relationships with clients.

Questions to Ask and Answer

1. Do we have the necessary data in our CRM?

2. Are we analysing the data or staring at default charts?

3. Are sales people involved at each step in the sales cycle?

Here are 3 ways I can help:

1. Book a consultation to talk about AI.

2. Explore how to manage an AI project.

3. Explore use cases using NVIDIA accelerated computing.