Author: <span>Cien</span>

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Does Quota Even Matter?

00Blog: The Science of Sales, FeaturedTags: , , , , February, 20

 

Several years ago, in my last position as a major account executive, my brand new first-line sales manager asked me to sit down with him so he could give me my new quota for the year. I told him that I did not care what quota number he assigned to me and that the quota assignment would not impact my performance. I thought his head would explode.

 

What I told that new manager was 100% true. The only thing that quota meant to me was it gated when my commission rate would go from 4% to 6% to 8 % to 10%. Other than that, the quota assignment was just an arbitrary number that came from HQ.  He was incredulous. “We are sales guys”, he exclaimed, “We live and die by quota performance!”

 

We live by commission check.

 

So I walked with him to his office and drew a turtle chart on the wall. The company, I explained, is counting on the top 20% of the reps to produce the most revenue and make or exceed their quota assignments. That 20% will also make the most money. The thought was that some reps would attain the quota numbers, about half would be somewhere between 60% and 90% attainment, and the rest would be below 60%.


I admit that I was cheating here. I had seen the chart on the VP of Sales Operations whiteboard a few weeks before. The quota assignment exercise then became a simple algebraic model to distribute revenue assignment plus over assignment such that a bell-curved performance result would have the company making its revenue goals with about 25% of the sales reps achieving quota and hitting their performance bonuses. This controls for both the cost of bonus commission exposure and the attainment of revenue plan exposure.

 

So, I concluded, it does not matter to me what assignment number you give me. All that matters is that I know I will be in the top 20% and the question becomes how will I optimize my earnings. “OK, Get out of here.” was his reply.

 

I took two lessons from that exchange which has stuck with me. The first is that it is a waste of time for the manager to worry about the guys in the top 20%. The second is that quota is a useful tool for understanding relative performance.

 

David Brock wrote a very thoughtful blog post about Does Quota Matter last year for Partners in Excellence. I agree with his conclusion that the point of Quota is to maximize performance and Quota is one way to measure if we are meeting our performance goals. David also references an amazing piece of research undertaken by CSO Insights. Their annual Sales Enablement Study for 2019 stated that among the firms they surveyed, the average revenue attainment was over 100% of plan while the average quota attainment of the sales teams was around 61%. I find that shocking.

 

Part of what shocks me is that we accept that pattern as acceptable. Sales leaders I speak with, and most of my customers and prospects are sales leaders, tell me that one of their three most pressing issues is how to get the 70% of the reps in the middle to improve their performance. The sales leader who can grow the performance of those reps in the middle of the bell curve breaks the bank. The company posts more bookings and the reps make more money.  Everyone is happy. If you go back to the bell-curve chart, it is clear that the top 20% are carrying the freight. How do we extend that performance?

 

 

The answer I read frequently is that the correct course of action is to identify the best rep and have everyone else emulate that rep. I disagree. I believe that no two reps, like no two opportunities, are created equal.  Different reps have different skills. The key is to understand what are the skills and needs of each rep and how do we optimize each rep’s performance.

 

That is not easy. It is a challenge for which few sales leaders are trained and for which there are few tools in the market. Most AI for Sales tools are focused on activities rather than behaviors. One of the great beauties of the Challenger Sales system is that it teaches best practices and processes while allowing room for individual skills. Understand and coach each individual and the performance of the team will rise.

This article was written by Joe Lupton, Cien’s Head of Sales and Customer Success.

With Cien, all reps can make quota. We show you how.


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End the Bickering Between Marketing and Sales

00Blog: The Science of Sales, FeaturedTags: , , , , , , , February, 20

Firms can earn big returns by effectively measuring each step in the sales and marketing process

Do you hear your Sales leaders complain to Marketing that their teams are not getting enough high-quality leads?  Are the Marketing folks pointing to the high volume of leads that fit the Ideal Customer Profile criteria and have shown sufficient intent to trigger a qualification as a Marketing Qualified Lead?

There is a rich bounty of published work telling us that Sales and Marketing must run in lockstep.  In an account-based world, a common language is clearly required to understand and account for the contribution of the sales and marketing teams to the revenue generation process.

 

Marketing Contribution Measures the Value Added by Marketing

They say Marketing is from Venus and Sales is from Mars. Whether you recognize it or not, the performance of a sales team depends in large part to the amount and quality of the leads sent to it by the marketing team. While measuring lead volume might be easy, assessing quality is not.

Typically, the value of leads generated by marketing is calculated based on average values such as average customer lifetime value, average lead conversion rate and the average cost per lead. As with total sales volume by sales professional, this simplistic measurement is done because more precise assessment is not easy.

This traditional way of measuring the value of a lead doesn’t provide any color on the quality of the lead, however. It fails to account for a lead’s propensity to close, the prospecting effort required to convert it, and the expected deal size for the lead. This simplistic accounting excludes important operational intelligence for optimizing sales performance.

The Cien Value Chain employs a complex set of AI models that derive a true value for each lead and opportunity.  Using hundreds of machine learning and natural language processing models, the Value Chain calculates what the real value of any given opportunity is TODAY. Think of it as calculating the expected value of a lead that may not close for weeks or months.  What the Cien Value Chain gives you is a starting point value that all parties; Marketing, Business Development, and Sales can agree on as representing the real dollar value of leads attributed to Marketing.

 

Sales Contribution Measures the Value Added by Sales

If you can’t measure it, you can’t improve it.

Why did Bob sell more than Sue last year? Was it due to the quality of the leads he received from marketing, the territory he was assigned, his work ethic, or simply a winning smile?

Historically, sales representatives were measured by the total revenue of sales signed. This is still a commonly used indicator of sales performance in many organizations.

Using total sales revenue as a measurement for sales performance can be misleading at best and counterproductive at worst.

This is because the total sales revenue per sales rep is a simplistic measurement that doesn’t reveal the underlying dynamics of where marketing and sales are strong or weak. Marketing may be handing weak leads to a strong sales professional, for instance, making the seller look worse than his skills allow. Or a rep might be closing sales and generating a high total sales volume, but half the cross-sell opportunities for his prospects go unrealized while another sales rep could better uncover these hidden opportunities.

Total sales revenue simply does not capture enough operational intelligence for sales performance optimization.

Many sales managers know this. The problem is that measurement beyond sales quota achievement is hard; firms must account for lead, pipeline, human and market factors that come into play. The data for this operational intelligence is there in CRM systems, but it often is incomplete, inaccurate or insufficiently structured. So sales teams tend to measure on a few key performance indicators, and CRM data is used primarily for forecasting purposes.

Getting beyond these simplistic metrics is important for the operational intelligence that businesses need for improved sales performance. This requires looking at both marketing output and sales performance.

 

 

Let’s take an example.

Imagine two sales reps Bob and Sue who work in the same team. At the end of the quarter, Bob has signed $1,000,000 worth of bookings, and Sue $800,000. Without a clear picture of the team’s effectiveness, Bob appears to be the highest performing seller.

When a firm is able to take into account the true dollar value generated by lead generation and sales development efforts, it is able to compare the lead value received by a sales professional with the added value the seller has contributed to it.

In Bob and Sue’s case, it’s possible to calculate the value of leads they received and compare them with the actual value they signed. And it turns out that Bob actually received $500,000 of leads and pipeline value from marketing, while Sue only received $200,000. Bob actually contributed less to the business than Sue, even though at a superficial level his numbers were higher.

As this example shows, the best seller on the team isn’t necessarily the one who has signed the most contracts, it is the ones who have added the most value to the leads and opportunities received by the marketing and sales development teams.

It may be that other sales professionals appear to sell more because they’ve received more valuable leads from marketing, or because they work a territory that has greater demand than another rep. External market factors such as a local competitor leaving the market might also distort the picture of the seller’s performance.

 

Artificial Intelligence Makes it All Possible

Improving sales performance requires better operational intelligence. The problem, as stated above, is that most firms cannot effectively analyze their business data comprehensively enough for this insight.

The good news is that advances in statistical science, machine learning, natural language processing, and AI allow businesses to exploit sales data and CRM records for new levels of understanding previously not possible.

With AI, companies are now able to measure and account for the exact value created by marketing campaigns, the value generated by a sales development team’s prospecting, and the qualification efforts, distinguishing them from the value created by the sales professional who converted those qualified opportunities into signed contracts.

By looking at the multiple factors that make up a sale, artificial intelligence allows firms to break out the individual performance of every seller in the organization. From this, companies can immediately generate more revenue by allocating higher value leads to the most effective sales reps and train those reps who are underperforming.

Cien delivers the intelligence needed for this more sophisticated analysis. The first step to measuring sales and marketing’s contribution is to request a Hidden Revenue Assessment.

 


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Quantify Intangible Sales Factors Using AI Accelerate Your Sales Podcast

Quantify Intangible Sales Factors Using AI

00Blog: The Science of Sales, FeaturedTags: , , , , , January, 20

Cien’s Co-founder and CEO Rob Käll recently joined global sales expert Andy Paul on the Accelerate Your Sales podcast.

“Accelerate Your Sales” includes in-depth conversations with 700+ of the leading sales and marketing practitioners from top sales executives and industry leaders such as Salesloft, Outreach, DiscoverOrg,  Salesforce and many more.

With 2,000,000+ downloads and counting, Accelerate! sits on #10 of Cien’s 21 Sales Podcasts Business Leaders Should Listen To and has been named to more than fifty Top 10 lists as required listening for sales professionals.

Tune in to the full episode to hear what Rob has to say about AI, scaling SaaS businesses and making quotas.

 

 

Highlights from the podcast:

Rob and Andy discuss how artificial intelligence can help sales leaders measure the impact (or lack thereof) of their sales training and enablement programs.

In addition, they talk about how AI can help sales leaders know who their best and worst performers are and who on the team is coachable, or not.

What’s more, they discuss the importance of measuring and tracking intangible sales factors such work ethic, selling skills, time management and data hygiene.

This gives the sales manager and his or her rep a better backdrop to personalize training and their 1:1s.

When it comes to sales performance, the trick is to encourage reps to work on their weakest skill or behavior.

To motivate their reps to improve, sales teams use Cien to calculate the revenue and quota impact of improving a given skill and behavior.

You can connect with Rob on LinkedIn or Twitter.


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21 Stats Every Sales Leaders Should Know - Cien

21 Stats Every Sales Leaders Should Know

00Blog: The Science of Sales, FeaturedTags: , , , , , , January, 20

Whether you’re a numbers person or not, here are 21 stats that every technology sales leader should know.

 

Sales Quotas & Win Rates

1. Only 60% of companies say that quotas are set as a collaborative effort between the CEO with input from senior management. (CFO Alliance)

2. 64% of sales organizations reported correct quota setting as the major challenge for their compensation program. (Alexander Group)

3. The average quota attainment is just 54%. Only 30% of firms have 75% or more of their salespeople hit their quotas. On average, about 57% of salespeople make quota. (CSO Insights)

4. Companies that “peanut butter spread” quotas across similar roles see 14% less quota attainment than those that assign quotas based on territory-specific opportunity. (Xactly)

 

Sales KPIs and Reporting

5. 2/3 of organizations that use dedicated sales analytics tools say they have improved the outcomes of sales activities and processes. (Ventana)

6. Only 6% of companies who use a spreadsheet or static reporting can give their sales teams access to daily or near real-time data. (Xactly)

7. Two of the sales metrics tracked most often are margin at 65% and profitability at 51%. Surprisingly, only 6% of companies track the cost of a sales call. (OMG)

8. 79% of sales teams currently use or are planning to use sales analytics technology. (Salesforce)

9. Human and machine-generated data is growing 10x faster than traditional business data, and machine data is increasing even more rapidly at 50x that growth rate. (insideBIGDATA)

 

Sales Training and Management

10. Companies with a formal coaching process see 91.2% of overall quota attainment, as compared to 84.7% quota attainment for companies without. (Hoopla)

11. 60% of sales reps say they’re more likely to leave their job if their manager is a poor coach. (Center for Sales Strategy)

12. 55% of salespeople making their living in sales don’t have the right skills to be successful. (Caliper Corp)

13. Reps spend only 34% of their time selling and only 22% of high-performing teams rate their training process as very good. (Salesforce)

14. On average, a new salesperson takes 12 months to achieve success. (Sales Management Association)

15. A dynamic coaching process improves win-rates by 28% and quota attainment by 10%. Yet, 47% of organizations do not have a formal coaching process. (CSO Insights)

16. The top 10% of all salespeople are 304% more effective at listening and asking questions than the bottom 10%. (OMG)

17. Companies with dynamic sales coaching programs achieve 28% higher win rates. (Brainshark)

 

AI and the Future of Sales

18. AI associated with CRM activities will boost global business revenue from the beginning of 2017 to the end of 2021 by $1.1 trillion. (IDC)

19. Sales teams who use Salesforce as their CRM tend to be twice as bullish about the impact of AI on sales than teams who don’t use Salesforce. (Cien)

20. 75% of Sales organizations are planning, evaluating or have implemented some version of AI into their sales process. (Sales Mastery)

21. 31% of sales leaders see AI as a source of added complexity – a significantly higher rate than sales reps. (Cien)

 

While everyone seems to be looking for more data, at Cien one of our most frequently heard complaints is “I have a lot of KPIs and do not know how to make sense of them”.

So perhaps sales professionals are not measuring the right things to really solve their sales performance problems. Perhaps they just need a single metric that explains a reps performance?

Put your data to work. Get stats on your team’s strengths and weaknesses for with Cien’s Hidden Revenue Assessment.

 


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Keeping the Human Element in AI for Sales

00Blog: The Science of Sales, FeaturedTags: , , , , , January, 20

Why do we accept 60% quota attainment? It seems every day I see another news story read or an article discussing the fact that somewhere between 40% and 50% of B2B sales reps in the US fail to attain their quota numbers. Why is that?

There is a plethora of tools and applications available to Account Executives, Sales Leaders and Sales Enablement and Operations personnel in support. How can the efforts of these talented and hard working folks lead to such poor results?

I have a theory. Actually, I have a couple of theories. The first cause indicated is tenure. A 2018 report from the Bridge Group indicates that B2B Sales rep tenure is less than 24 months. David Stein, CEO of ES Research, writes that Sales Manager tenure can be as low as 19 months. If you look through the marketing materials provided by ABM leaders like Terminus, you will see similar statistics quoted for marketing tenure. Time in position has never been lower and is continuing to shrink.

Tenure of Reps and Managers is a Symptom

Clearly, tenure numbers like those indicate that there will be problems understanding products and customers, which will lead to poor quota performance. A new sales manager needs a year of experience to build an understanding of the product and the ways that customers use the product.

With such high turnover rates, sales onboarding becomes a very short runway that focuses on product knowledge rather than the skills needed to succeed in the new position. Kelly Riggs discusses this skills training topic very effectively in the Business Locker Room blog. I suggest that this is more a symptom than a root cause.

The underlying problem is twofold. There is an overwhelming pressure to deliver revenue within unprecedented levels of competition. In addition, there is the micro granular level of analytics focused on sales activities.

Take a look at SalesHacker’s 2018 Sales Technology stack. If you are selling sales technology, every one of those offerings is a competitor and more enter the fray every day. This market segment is far from unique, in fact every B2B market segment is fraught with competition.

A friend of mine is a Senior Director at a top 10 retail firm who prides himself on introducing effective new technology to the firm. He tells me that some weeks he gets 500 solicitations. Some of the products may be the next great thing, but he has no way of sorting them all out. If he did not know me, he would never open my emails or discuss my products. This is a good example of why sales longevity matters.

 

It’s time we balance the scientific and the human in B2B sales.

In this intensely competitive environment, the rep who only knows his or her product but may not have a strong grip on the overall technology market, or who may not be completely familiar with the nuances of the industry is at a hopeless disadvantage. This stresses the critical nature of making the most of each and every opportunity presented to a rep.

The second underlying issue I see is in the metrics surrounding sales. The volume of analytics and AI tools that measure sales activities, and I stress activities, calls to mind the early days of Taylorism and Scientific Management.

The theory of Taylorism was that all activities could be reduced to an optimal few repeatable steps and that each step could be patterned, models and measured.

The upside of Taylorism is that it facilitated the Fordist process of manufacturing. The downside of the Taylorist model is that it so dehumanized the worker that many unions insisted on not implementing the Taylorist process.

The Taylorist underpinnings matured and evolved and can be seen in more humanly inclusive terms in the Toyota Production System of continuous improvement and respect for people. I don’t want this to sound like a Luddite rant against new scientific sales methodology, so I will come to the point:

The Human Element of AI for Sales

I base my contention on two pillars. First, that the tool sets available today for Sales Operations and Sales leadership, whether they are metrics based or algorithmic, or employ Machine Learning (ML) and AI, are focused overwhelmingly on sales tasks. This is activity-based optimization.

The message is clear that the route to success is to define the most successful rep activity in infinite detail and then have every other rep emulate those activities as precisely as possible. This is classic Taylorism; one optimized size fits all.

The second pillar is that the tools available to sales leaders today do not help the sales leader understand the skills and attributes of the individual reps. The tools strike me as being prescriptive before there is a diagnosis. The tools want to provide the best average solution rather than the right individual training and skills enhancement needs for each rep.

 

One size fits all coaching systems are not an improvement over the status quo.

I would also suggest that the state of performance against quota discussed above argues powerfully that the current approach is not working well and that some key element of sales performance is being overlooked.

I further suggest that insight into the skills and attributes of individual reps in the interest of forming easy to use and effective prescriptions is the next step forward to start winning the war quota attainment. The new sales leader who is trying to make his numbers and manage a team and learn a new space needs the system to do the work for him or her; to shed light for him or her directly on the specific areas of performance that require coaching for each rep–not in activities, but in the skills and attributes that drive those activities.

 

Focus Your Attention Where The Most Benefit Can be Found

The sales team is a set of individuals with particular skills and attributes. Some team members are top performers, some are low end performers and most are in the middle of the pack. This is the classic bell curve distribution of human performance attributes.

The system provided for the sales leader needs to make it easy to see the characteristics of the team, not just the activities. The system needs to help the leader understand who needs help and who doesn’t; who can be coached to success and who should find success elsewhere and most importantly how to move the middle of the bell curve reps to the next level of success. Improve the performance of the reps in the middle of the performance bell curve and the entire team‘s quota performance will leap forward.

 

Why is this Important?

Improving Quota performance is likely the single most effective way to address the tenure issues discussed earlier. According to Sales Fuel, three of the five most common reasons for sales reps leaving can be managed through (1) better coaching from the immediate manager and (2) the opportunity to make planned money. A good, individualized insight system to help sales leaders get their teams to 100% quota attainment answers the call. If the team is making its quota and earning planned dollars, the impetus to leave is greatly diminished.

 

Measuring sales activities is not enough. To move performance, manage individual skills and attributes so that each team member can perform to the best of his or her ability.

Sales is the most human of business processes and appreciation of the human elements of sales success along with the provision of tools that help incorporate human attributes into the management flow will help turn the tide in our favor in the war for 100% quota attainment.


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