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About This Episode
We know measuring sales productivity is all a numbers game. But chances are you may be doing it wrong.
Rob Käll started working on this problem when his company, over a period of 3 years, went from 2 to 100 sales reps and he didn’t get 50 times the bookings. And he always thought there must be an answer to that.
Rob is the CEO and co-founder of Cien.ai, a software tool that uses machine learning and natural language processing to help measure the productivity of sales reps and identify their points of improvement.
On this episode of The Sales Engagement Podcast, Rob explains how sales productivity should be defined, how it should be measured, and how doing so can be an incredibly effective way to achieve predictable growth.
Defining and Measuring Rep Productivity
Sales productivity means a lot of different things for different people.
Not coming from a sales background, but rather a technical one, followed by being an entrepreneur, the simple definition Rob uses is the classical definition of activity:
activity = output per hour/day/month/year
It comes down to how much your reps are producing.
While this sounds very simple, when you are dealing with large complex high-velocity sales teams, it can become very complicated.
You’re trying to measure the sales development reps, business development reps, prospectors, and the true productivity of our account executives.
You can think that if an account executive sells $100k his productivity is $100k. But that’s wrong. If you have an SDR team, they delivered value to that AE. You need to discount that value.
And if you don’t keep track of those values, you’ll end up not comparing apples to apples.
How to accurately measure and keep track of those values is what Cien.ai has spent years building technology to solve.
The 3 Key Areas to Measure Rep Productivity
You could be looking at
- calls made
- emails sent
- opportunities set
- meetings held
The list goes on and on. But traditional KPIs don’t paint the whole picture. You need a 360-degree view of the whole sales environment, which you can get by looking at three distinct areas:
Lead and pipeline factors
These are the things that have been delivered by your marketing team. At times you have leads that are great quality and other times not.
These are things like:
- Work ethic
- Product knowledge
- Communication skills
- Engagement ability
These are things that are outside your control but still affect your ability to sell. Things like competitive pressure or seasonability. All three of these can be challenging to measure, but that is where new technology comes into play.
Through natural language processing, you can look at not just the number of calls and emails but the nature of those calls and emails.
How Does It Work and How Is This Objective?
Rob’s company is an AI-first company. Everything they do is based on analyzing data using various types of machine learning algorithms and natural language processing.
Their goal is not to replace Salesforce or Outreach.io, but to help you understand how your team can move the needle.
For example, it can find where you have reps who show low product knowledge and help you correlate that back to that reps success.
Different reps will have different issues, and when each one can be identified and measured, you know exactly what to address to get better results.
Rob likes to ask sales leaders what the most important quality in a rep is. He usually hears things like communication skills, great work ethic etc.
But all of these are important.
If you are great at lots of skills but your work ethic is zero, it’s like multiplying everything by zero.
What Are The Results?
Rob’s business is from the beginning about not using anecdotal evidence. They are literally measuring their success every single second as they run the company.
That’s the beauty of running a completely integrated solution that connects to products like Outreach.io.
Rob says the typical number is an increase of 4-6%
You have to pay attention to the weakest area of each of your reps and try to fix that. If it’s not fixable, then that rep is not fixable.
When you are identifying and solving weak areas in reps, all of a sudden they can see improvement in their performance and become more valuable to the company.
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