Convert, win, analyze, refine, repeat
When you find something that works in sales you want to repeat it.
After you land a great client, you take a moment to review the sales path for them. What lead to the close? How did you meet them? What did you say to them? Where did they fall into your funnel? How long did it take to convert them? What worked, what didn’t work, and what can you replicate for the next prospect?
Often you don’t have time to do this with every sale; you need to jump on the phone or back into the funnel for another prospect. But it’s still natural for sales professionals to mentally categorize and break down what’s working and not working for them.
The danger is when we begin to see patterns where there are none. On the surface the data may point to a specific conclusion, but there are any number of reasons for the way the numbers fall, or appear to fall.
Correlation is not causation, especially when it comes to sales.
So how do we cut through the dreck to see what is really working?
Trust, but verify
There’s an old Russian proverb that Ronald Reagan was fond of: “Doveryai, no proveryai.” It means “Trust, but verify.”
If you are seeing a correlation in your sales cycle, particularly if it’s data driven, it’s ok to question what you’re seeing. Ask if there really is a pattern. Is there a correlation, or could some outside factor be driving the numbers? If it appears there is a correlation, remember that it still might just be coincidence.
As Rebecca Goldin, professor of mathematical sciences at George Mason University and Director of STATS.org writes:
“Just because two things occur together does not mean that one cause the other, even if it seems to make sense.”
Trust that you may be onto a way to positively tweak your process, but verify that there is causation before you upset your whole strategy. If you can’t verify a correlation — if you can’t repeat the results — then it’s just a happy accident.
Analyze all the data
We live in a world of data. As a modern sales professional you have access to more data than your selling ancestors dreamed of. When you see a correlation in the data, check to see if other data points help to reaffirm your hypothesis.
Are you really selling more because of the way you changed your email workflows, or was that customer going to buy anyway? Do you really see a 25% increase in sales from customers that visit a specific page on your site, or is there some other factor?
If no other data or KPIs back up the pattern, then there is probably not causation: the correlation did not directly cause the results you are seeing.
Be willing to be proven wrong
It can be so tempting to want to finda correlation where there’s really just a coincidence in your data. We’ve all read dozens of articles on how some company made a tweak in their process and it resulted in X% increase in sales.
Those solutions are out there. However, you have to be careful that you don’t want to find causation so badly that you aren’t willing to be wrong. It’s easy to find data that correlates are own preconceived theories. And it’s natural to focus on data that backs up what we want to see.
It’s much harder to be able to spend time and effort checking a possible correlation, only to find that the data shows it to be just a correlation, there is no causation.
And that’s ok, too! It doesn’t take anything away from your efforts. It just means you found data that proves there wasn’t causation. Don’t stop looking. Don’t stop verifying. The next correlation could be exactly what you’re looking for.
Remember the person through the data
We have so much data surrounding all of our activities that it can be, at times, distracting from the actual results. Data is a wonderful gift, but remember that beneath it all are people who make very human decisions.
Sometimes a business decision is not trackable by pure data. Sometimes the deciding factor that causes a customer to do business with you is simply … you. Your existing customers are more than account numbers in your database, likewise, your prospects are people too.
Don’t be so distracted by the data that you forget the person behind the numbers. And if you have a great relationship with an existing client, you can always ask them. “Mike, I’m trying to improve our processes to better help our customers. So I was curious, why did you decide to go with us?”
Sure, a customer’s final decision could just be an outlier; but you’d be surprised how a handful of those conversations can show you a detailed view of your sales cycle from a different perspective.
Verify your data and see if it’s repeatable. It may sound like correlations can be a mirage in our big-data selling world, but careful analysis will show you that you can find an oasis of causation if you look hard enough.
Be willing to question your data and verify the patterns you find. You have a wealth of data at your fingertips. Work it methodically and you will improve your processes.
“Doveryai, no proveryai.” Trust, but verify.