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Analyzing the 

Sales Pipeline

The 5 things you need to know about your 

sales pipeline to ensure consistent revenue growth.

Courtesy of TopOPPS

Jim Eberlin, Founder & CEO


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Most sales leaders analyze their pipeline the same way they’ve done it for years - 
this is why sales is still a grind, forecasting is still a struggle, and there are still 
surprises or disappointment at the end of the sales period.  

Your sales pipeline analytics should answer these questions with precision:   

How much new and total sales pipeline do we need – and will we have enough?

Is the sales pipeline filling at the appropriate rate?

Where are deals getting stuck in the pipeline so I can change or coach on 
those sales activities?

Am I converting what’s in the sales pipeline at the necessary rate?

These questions have to be answered for the whole company, the region or 
division and for the sales representative.  

If I don’t know the answers to these questions (and some follow on questions), I 
may be caught flat footed at the end of the sales period and miss the number.  But 
more importantly, without good answers to these questions throughout the sales 
period, I can’t make good decisions to improve my process and my reps – costing 
the company millions in lost deals.  

So, let’s look at what us sales leaders use to answer these four questions above. 



If you don’t know these 5 things about 

your sales pipeline, it’s costing you millions!

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Most sales leaders look at total sales pipeline for the period and 
closes (see graphic below). 

This graph tells us:

Total pipeline in dollars or units 

Closes from that period

The specific period and its respective  total pipeline and 

This type of graph can be used at the beginning of the quarter 
to compare to previous quarters and it can also be used to 
decide if we have enough coverage based on what we’ve 
needed in the past.

Here’s what it doesn’t tell us: A lot.  Let’s start with some 

How much of our sales pipeline is new?  

Are we filling our sales pipeline at a rate that we need?

How much of this sales pipeline was already there at the 
beginning of the quarter?


How does this compare to previous periods? (in our case 
it’s quarter over quarter)


Sales Pipeline and Closes Per Sales Period

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Then, let’s drill down to see if it’s a healthy pipeline by asking:

How much of this sales pipeline is scheduled to win this 

How many open opportunities do we have to work on?

How much of this sales pipeline pushed into this quarter? 
(Push definition: deal was scheduled to win in the 
previous period but was pushed into the following 

How many have had multiple pushes prior to this 

How does our number of pushes compare to previous 

The problem with only being able to answer the former (simple 
answers such as total sales pipeline and closes) leaves you at a major 
disadvantage to impact revenue growth for the following 4 

There’s no time to react if there’s not enough sales pipeline 

There’s nothing to help you pinpoint a problem or make 
adjustments for the future

There’s nothing to help you coach-up your reps to 
perform better

There’s nothing that tells you what happened to these 
deals – or if they were any good to begin with

What’s needed is the ability to understand more about your 
pipeline – where it came from, what happened to it, and 
ultimately, to understand and predict if I’ll have enough to hit 
my number.  Sales analytics with artificial intelligence is helpful 
because it can predict the outcome in time for you to make an 
impact.  CSO Insights reports that 94% of their World Class sales 
performers use sales analytics technologies for better decision 
making and less digging.  

The following are 5 fundamental components of 

understanding your sales pipeline and predicting early on 

(and in time) if you’ll hit your number.


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Checking the composition of your sales pipeline is like checking the ingredients of 
something you’re about to buy at the grocery store. Before you buy it you want to 
make sure it has enough of the good stuff and not too much of the bad stuff.  Also, 
you need to compare each component of the sales pipeline to previous periods to make 
sure you’re optimized for performance.  You want to know if you’re getting better 
month over month, quarter over quarter and year over year.  

Components to analyze in the current period to compare to previous periods 


New sales pipeline entering - this tells you if your pipeline is filling at the 
appropriate pace


Open sales pipeline – this tells you how many active opportunities you are 
working each period


Scheduled to Win Pipeline - deals with close dates for the current period


Pushed Pipeline - this is sales pipeline that was scheduled to win in a previous 
period that pushed into current period 


Multi-pushed Pipeline - this is sales pipeline that has been scheduled to win in 2 
periods or more prior to pushing into current period

Within every sales period you have to analyze what was scheduled to win and 
actually won, what was lost and what pushed into the following period.  You may 
filter these same metrics by industry, size of company and other important 
attributes of your ideal customer profile.  


Composition of the Sales Pipeline


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Composition of the Sales Pipeline


Example shows a comparison of the composition of the pipeline from 

current week to the same week last period.

This example shows the 

current composition and 

future composition

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Every sales period you have to look at the rate that you are producing new sales pipeline 
and how much open sales pipeline you have on a daily, weekly and monthly basis – in 
addition to the quarter.  You have to compare to the previous periods on the 
sales pipeline fill rate so that you can predict and also react in time if you’re not 
performing to what it should be.

By having the ability to predict the outcome of your pipeline generation for the 
period – you’ll understand the urgency and the speed necessary to react.  AI 
applications such as TopOPPS automatically predict how much sales pipeline you’ll 
generate, how much you’ll close and what will happen to the rest of it (ex. Push, 
win or loss).  


Sales Pipeline Prediction


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Sales Pipeline Prediction


Example shows previous periods plus current period prediction, additionally 

it can show next period prediction.

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A fundamental ingredient to having a pipeline you understand and can predict is 
accuracy.  You need a scoring mechanism to rank leads and opportunities – and 
accuracy is one of the components to score. The more effective you are at 
scrutinizing opportunities – and removing what doesn’t belong – the more 
predictive and the more confident you’ll be in your sales metrics.  Artificial 
Intelligence is a huge benefit for ensuring accuracy within a sales pipeline – telling you 
which deals require updates, which deals should be focused on and which should 
be removed.  


Accuracy of the Sales Pipeline


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Accuracy of the Sales Pipeline


Example shows ranking by best opportunities in single stage, and insights to 

improve sales pipeline hygiene and accuracy. 

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Here’s a real story that happened here at TopOPPS that helps with understanding 
the importance of knowing what happened to new leads and open opportunities.  

We discovered that we were not producing as many new leads for the week as we 
were in the same week of the previous month.  We thought this was a fluke after 
the first week – but when it happened again in the following week, we knew there 
was a problem.   

We had recently made changes to the sales team structure – but I was confident 
that they were positive changes and they were not causing the problem.  So, my 
first guess was that the leads were fewer – but maybe they were much better 
quality.  The new sales teams were experienced and focused and therefore were 
probably producing fewer but better leads.  But by analyzing the previous period’s 
leads, I found that many of them closed and also were still active in later stages.  
So my first guess was wrong.  We knew it had to be something else because the 
previous period’s leads were good.  I knew the teams were performing well so it 
was not long before I discovered the problem was within the lists.  Our call lists 
needed to be enriched – something that was accidentally yet understandably 
dropped during the big change going on within the team structure.  

Thankfully, this was discovered in time to adjust – and we had solid pre-existing 
pipeline that covered us in making our number.  But if we wouldn’t have had the 
ability to analyze what was happening to our sales pipeline and within the sales pipeline – we 
would not have caught the problem until it was too late.  


What Happened in Previous Periods


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What Happened in Previous Periods


Example diagram shows what happened to the leads created in Q3 of 2016. 

It shows what closed and what deals are still active from this cohort.

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Analyzing the trend of conversion rates of the different components of the sales pipeline 
helps us have confidence and a great handle on the forecast as well as the 
sales pipeline.  

We need answers to these questions:  

How many of the new leads do we close in the sales period?  (this question 
is based on your sales cycle)

How many of the pre-existing pipeline do we close?  

And of course, how many do we convert of the total sales pipeline?

Tracking this is helpful to see if we are getting better or worse – but it also helps us 
be more predictive.  If I knew that I got 500 leads in per month, and we closed 50 
of them consistently within the sales period and 125 overall – that would be a great 
thing to know and understand.  

Going into every period, it’s not enough to know aggregate conversions.  I want to 
know how many I expect to get new, and what’s there already – and how much I 
can convert from both new and pre-existing.  

You also need to know how much of your pushed and multi-pushed opportunities 
you’re converting.

And finally, you need to track conversions by stage of opportunity.  This is a great 
way to understand where deals get stuck and if it’s a problem company wide or 
just with that sales rep.  So, having the ability to see trends of the conversion rates 
as well as the ability to compare to peers helps to focus where to coach and how 
to coach.  


Conversion Rates


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Tracking Conversion Rates


Example shows conversions by stage and where deals get stuck for 

coaching opportunities. 

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TopOPPS can predict your sales pipeline and forecast results, and 

prescribe the right activities with AI - 

request a demo




By applying these five best practices, you will look at your sales pipeline more 
often because it will tell you more and help you with your strategy for 
the sales period as well as indicate how urgent your reaction should be.  
And you’ll have the right kind of information to help you coach the sales 
team and adjust the sales model to accommodate the appropriate 
amount of opportunities at the correct rate.  

Artificial intelligence, predictive and prescriptive analytics for sales is 
a great way to immediately apply these best practices and to get 
results quickly. 
Business Intelligence (BI) tools cannot give you the 
insights and bring problems to the surface quick enough to understand 
and react.  So, a good AI application for sales such as TopOPPS can help 
you become more knowledgeable and predictive about your sales pipeline 
and utilize insights to coach up the sales team – without doing the time 
consuming “digging around” data.  

The cost of not having these five components to your pipeline has a 
negative impact on your conversion rates and the number of leads and 
opportunities flowing into the sales pipeline – which easily results in millions of 
dollars in losses over time.  Apply AI, predictive and prescriptive 
solutions such as TopOPPS to prevent these losses and accelerate 
revenue growth.