Doug Davidoff
As part of our services offerings we regularly conduct a variety of sales, marketing and lead generation assessments. When the goal of a company is to significantly enhance results, it’s important that you first assess where you are, what’s working and what’s not.
When conducting these assessments, we frequently encounter the problem of a lack of and/or ineffective data. We’ve learned that there’s no shortage of opinions, and people are filled with anecdotes to support those opinions; but clear, effective data is often missing making it difficult to separate the truth from the story.
Recently we were working with a client to assess their new-sales process. When talking to the executive of the client we were told that a salesperson was really struggling with closing sales. However, when talking to the sales rep, he insisted that he closed the vast majority of opportunities when they reached a particular point in the pipeline. The problem was there was no data that told us how many opportunities reach that point, so we couldn’t really determine what the truth is.
The Experience Fallacy
As with most things, everyone has an opinion when it comes to what works in sales and marketing. While these opinions can be important, and may even be right, they’re just opinions – not facts. While I certainly don’t believe that data tells the entire story, it tells a compellingly important part of it.
The fundamental problem with opinions is that they’re based almost exclusively on the experiences and prejudices of the person holding the opinion. In a world like sales and marketing where so much has changed, what worked even five years ago may no longer work today. Without data you cannot figure that out.
This is called the experience fallacy. We overweight the validity of what we perceive to be true. This is why sports teams invest so much in advanced analytics (think Moneyball).
Why Data Is Crucial To Predictable Growth
I often equate selling to hitting in baseball. The tough thing about both is that you can do everything right and still “fail” (and conversely, you can do a lot of things wrong and still “succeed”). When the only data you have to measure are results data (hits in baseball, sales in selling) you can’t accurately assess performance to reinforce what’s right or adjust what’s wrong.
A couple of months ago we were working with a client on their sales development process. The client was frustrated with the results and the executive was approaching it as a performance problem, with the executive expressing to us that he was considering letting two of his reps go. When we asked for data the only thing clear data they had were the number of leads, the number of calls, how many opportunities were passed on and the number of sales that closed.
They didn’t know (and thus could not share) what percentage of leads handled were qualified (or not), where leads exited their process or the timelines associated with getting a lead from one stage to the next. Upon review we identified both process flaws and potential performance flaws. The problem is that we can’t effectively address performance because it’s not clear how much of the problem is performance related, nor are we clear what aspects of performance need to be addressed (or in what order).
Coaching sales reps is critical to long-term success and development. I’ve discovered that there are two types of coaching that exist: opinion-based coaching and data-based coaching. The former can be a lot like teaching pigs to sing (it doesn’t work and you end up annoying pig). The latter is the only effective way to coach.
Think of it this way. Let’s say that you’ve got a sales rep who is deficient in some part of the sales process. For this example we’ll say that you’ve identified that they get enough sales qualified leads, but they’re not doing a good job of getting those leads to the middle of your sales process.
Without data you’re just talking about opinions, many of which your rep probably doesn’t agree with. Despite that, you begin coaching them on the skills needed in that phase, and they start to improve. The problem here is even as they begin to improve they’re still deficient. Lacking data you can’t identify the improvement.
With data you don’t have that problem. First, you avoid the opinion barrier because you’ve got facts to back it up. Joe, your stage 2 conversion rate right now is 23%. As you know our target for this stage is 40%, and the best reps are currently converting 60%.
In this type of coaching you’re not judging them, you’re simply managing the facts. No one can dispute there’s a problem. As the rep begins to implement improvements their rate increases to 30%. They’re still deficient (and that should be recognized in the coaching), but they’ve improved their performance by almost a third! That’s to be celebrated and reinforced.
The Critical Metrics for Measuring B2B Sales Performance
The metrics you track are highly dependent upon your approach and model. That said there are some key metrics that need to be tracked by everyone. They are:
- Number of leads
- Number of sales qualified leads
- Pipeline Performance
- How many opportunities enter the pipeline
- How many opportunities enter each phase of your pipeline (For example, at Imagine we have 4 key break points for each stage of our sales pipeline, so we track how many opportunities reach each stage)
- Average sales value per opportunity won
- Average sales value per opportunity lost
While there are a multitude of other metrics that can (and often should) be tracked, if you’re at least tracking these numbers you’ll be able to maintain an assessment of your processes and be able to use data to drive your decisions.
The Three Most Important Effectiveness Metrics You Should Be Tracking
At the end of the day the goal of your sales and marketing process is to enable you to bring on more revenue at lower costs. There are three metrics that you should be tracking that tell the true story about how effective your processes are:
- Sales cycle time. Measure by the time a lead become sales qualified to the time an opportunity is closed (either won or lost). You’ll want to segment this metric for wins vs. losses. Additionally, you should track the average time, and group by time block (i.e. <90 days, 91- 180 days, 180 days – 1 year, 1 year +). Effective processes will show measurable decreases in sales cycle times.
- Customer acquisition cost (CAC) as a percentage. CAC measures what it costs you to create a new customer. To determine your percentage simply divide your CAC by total new sales (or new gross profit). Effective processes will show a decreasing percentage for your customer acquisition costs.
- Cost per sales qualified lead (C/SQL). To calculate this, you simply divide the number of SQLs in a given time by the costs associated with getting a lead to a sales qualified status. Here again an effective process will decrease your cost per sales qualified lead.
By tracking these key metrics you (and everyone in your organization) will be clear about how they’re performing. This alignment will unleash the genius within your organization.
