Fantastic lost reasons and how to set them up

I firmly believe that tracking your lost opportunities is as important and in some cases even more important than tracking your wins. After all, won opportunities are pretty self-explanatory, obviously there are some metrics we can track and conclusions we can derive from them, but at the end of the day keeping an eye on your loses might in many cases give you a better idea of where the market is heading and how the needs of your clients are evolving. Jan Solecki, CRM and Integration Freelancer at SoftwareSupp‍

A tale of two data sets

To analyze your lost opportunities you need to have the proper kind of data that will make your analysis as painless and as little time consuming as possible. Before I dig into the various possible reasons we can track, let’s look at the two major types of data we can collect which are quantitative and qualitative data. As their names suggest, the first set deals with numbers, hence the quantity and the second one with in-depth descriptions. With these sets of data we can follow one of the 3 scenarios:

1st scenario: Only qualitative data

Qualitative data sound great, after all they are supposed to give you deep insights instead of raw numbers. Take a look at the sample qualitative data set below:

Lost reasons:

• Client went silent
• Not responssive
• Doesn’t pick up the phone, doesn’t respond
• Went with our competitor X (more features)
• Choose Y instead of us (better track record working with their industry)
• Compared us with different companies and choose someone else
• They couldn’t afford our services
• Didn't have the budget
• No budget this quarter

In this scenario lost reasons are tracked as comments. They provide a deeper understanding of why a particular opportunity was lost, in some cases they even specify which competitor was chosen instead of our company.

However, we need to remember that this sample data set only shows 9 opportunities, whereas in a in a real company those would be hundreds if not thousands of deals. Who would be capable of analyzing such a data set and how could any decisions be made based on it?

Since, analyzing qualitative data at scale is practically impossible instead of getting a better understanding of our business, we end up looking for a needle in a proverbial haystack.

2nd scenario: Only quantitative data

In this scenario, lost reasons aren’t tracked as comments using open text fields, instead they are selected from a pre-defined list of lost reasons in a company CRM. Take a look at the sample quantitative data set below:

Lost reasons:

At first glance, we are able to see that this set of data is much simpler to analyze. We have a total of 9 lost opportunities distributed evenly among the 3 available lost reasons. It’s all simple and clear if we need a high-level analysis, however the trouble begins when we want to dig deeper and try to understand why we are losing our business.

Let’s say we want to tackle our competitors. We find the corresponding reason - Different provider, and analyze it. We see that it currently accounts for 33% of our lost opportunities, but why is that? Why did we lose that opportunity? There’s a number of number of questions which remain unanswered:

• Why were our competitors chosen instead of us?
• What company was chosen in those 3 lost opportunities?
• Was is the same company? Or maybe 3 different providers?
• Why were they chosen instead of us? Was it the price? Was there something our product or service lacked in comparison to our competitors?

All of those questions are not only valid, but crucial if we want to adjust our offer, improve our processes and increase our closing rate and quantitative data doesn’t give us the answers.

That being said, if qualitative data is too difficult to analyze and quantitative data doesn’t give us enough insight to make an informed decision, how should we track our lost opportunities? This is where scenario no. 3 comes to our rescue.

3rd scenario: Quantitative + Qualitative data

The perfect solution is, like in many cases, mixing the two approaches. Using both quantitative and qualitative data combines the pros of the two approaches and at the same time allows us to overcome their individual limitations. Take a look at sample data set below:

Keeping these two sets of data at the same time allows both for a high-level overview and an in-depth analysis. Let’s see how this scenario plays out if you want to see how your competition is performing.

How much business are we losing due to our competitors?‍

33% of our lost opportunities are due to a different provider choice.

Who are those different providers?

In one case it was company X and in the other it was Y, we have no data on the third case.

Why have they chosen them instead of us?

In one case our competitor had significantly more experience in the client’s industry, in the other one we didn’t offer as many features as required by the client

Being able to ask and answer those questions allows you to respond more accurately to the ever-changing demand of your potential clients and also to make important decisions regarding your offer, pricing or the industries you need to focus on.

Summing up, you simply have to track the reasons behind your lost opportunities, there's no other option. Combining the power of quantitative and qualitative data will give you a full and precise 360 overview of why you are losing your opportunities and will help you act accordingly.