What’s your pipeline coverage? We all feel good about 3x pipeline. But what did you do to confirm the quality of that 3x pipeline? Most sales leaders are burdened with spending a lot of time vetting opportunities with reps. Considering all the other work that has to be done to fill and convert the pipeline – there’s hardly time left to thoroughly inspect it. There is a better way – the following is a plan I use and that is being used by many successful sales leaders I know to ensure that there’s enough quality pipeline to hit the number.
To find out if there’s enough pipeline to cover the number – we focus on the following:
- Of my list of opportunities – how many are qualified to include in my coverage? Are the reps just miraculously showing 3x coverage because I tell them to have 3x?
- Can these opportunities really close in this period?
- Are the reps closing out all the junk? How much is new vs. existing pipeline? Of the existing pipeline, how many have pushed from previous periods?
- Which deals have momentum (how old, how long in a stage) and which are going stale?
We assume that if we have 3x coverage – these things will work themselves out and we’ll address them in our weekly sales meeting/forecast call/pipeline review and 1:1s. But how can we be sure we’ll really purge all the bad opportunities and focus on the real opportunities – while having confidence that we have the right coverage to meet our number?
Confidence comes from properly assessing your pipeline health and coverage by having rigor in the following three areas:
- Process: a good rigorous and well-defined process to show the progress of an opportunity by stage, milestones, and gates that are aligned with how the customer buys and how we gather qualifying information and guide the customer while they are moving through their buyer’s journey. (We recently published two incredibly helpful guidebooks about sales process. Part 1: Creating a Winning Sales Process and Part 2: The Sales Process Evaluation Guidebook)
- Deal Inspection: we need to have accurate information on the activity of the deal. Example: Is the next meeting scheduled? When was the last time the customer communicated with us in a meeting, email or call? What levels are we dealing with and what kind of progress have we made with the demand unit buying team? Was the last sentiment positive or negative?
- Coaching guidance for 1:1s: Is the sales process being followed consistently among all the reps – and is everyone on the same page about the status on each deal? How well are the reps executing at each stage of the process? Do they know the proper next steps to focus on to advance the deal? (Here’s a cool LinkedIn post about data-driven 1:1s from a customer of ours!)
Unless you execute well on the above 3 areas – you will not have a pipeline that you can have confidence in – so I wouldn’t rely on any coverage assessment without it.
In fact, I wouldn’t even use the old 3x litmus test to indicate proper coverage. There’s better ways to understand if you have enough pipeline to meet your number this period and next period. And, it will be a lot easier to implement these four steps and manage sales if you have TopOPPS AI for sales forecasting and pipeline management with machine learning, predictive analytics and prescriptive analytics.
The four steps to get a better understanding of your pipeline:
Step 1: REPLACE THE 3X COVERAGE METHOD WITH DYNAMIC PIPELINE COVERAGE AUTOMATION
Analyze win rate by stage for your sales period. But remember the math changes daily as you move through your sales period. So, don’t rely on a win rate analysis of some previous period – that will not be reliable. And definitely throw out any weighted forecast that has a win rate percentage created by your gut. You’ll need technology that does this automatically, like TopOPPS (link to a demo). A new win rate has to be calculated each day using history and machine learning trained by sales activity. This is the only way to get an accurate interpretation of what will be won within your pipeline. Trying to build something like this or do this manually would be terribly expensive and time-consuming.
Step 2: ANALYZE WIN RATES BY COHORT
Analyzing win rate trends in different sales periods is a must. Win rates change based on activity over a period. At our company, we found that win rates go up within the same period and immediately following our customer conference called DRIVE. Obviously a lot of our customers come to this event and network with our other customers – which makes them much more confident in buying. We’ve also found that in some quarters we had better webinars and campaigns than in others – so win rates are impacted by different activity and the quality of activity. When I see a win rate that is an outlier over a trend – I review the reps, events, and activity.
Analyze win rate for each stage of the buyer/seller journey. Identify the stage that you first start winning 30% of your opportunities. Include all opportunities in that stages and later in your coverage.
Analyzing sales by cohorts includes analyzing across the sales team and by different sales processes. For example, the funnel graph tells me the following:
- At the stage “Compelling Need” which is the 5th stage of our buyer/seller journey, we consistently sell 30% or better (1 in 3 deals) across the sales team. In this case, we show 33.3% consistently or better. So, I will use “Compelling Need” as our official stage of qualified opportunities. The four stages prior to Compelling Need are lead qualifying stages as we guide the buyer through their journey – because the win rate is consistently less than 30% in each of those stages – we are still vetting those leads. I let the buyer/seller journey tell me what stage it becomes qualified by analyzing win rates in each stage.
- I see that in Q3, we did better than usual in Compelling Need stage (it went up to 54.5%) so I can investigate what lead gen activity was done or other activity that led to more wins in that quarter.
- As I compare my two reps – I see that Mia Swift worked fewer deals than Crystal but sold the same amount (Crystal sold 33% of her deals and Mia sold 42% of hers). I’d like to see if Mia consistently sells at a higher rate and if so, what she does differently than Crystal.
Analyzing by cohorts (ex. Sales period, ideal customer profile, rep, etc.) will help in getting a better understanding of the quality of pipeline. Also, having empirical data that tells you at what stage in the buyer/seller journey that you start winning 1 out of 3 deals consistently is a good indicator of when you have a qualified opportunity that can count toward the total qualified pipeline. You can get this kind of analysis out of the box by adding TopOPPS to your CRM (Click here for a demo of TopOPPS).
STEP 3: UTILIZE ARTIFICIAL INTELLIGENCE
Utilize AI to enforce consistent sales process and bring things to the surface during pipeline inspections and reviews.
Prescriptive insights from machine learning will maximize the rigor in:
- Sales Process Consistency
- Deal Inspection
Artificial intelligence will provide the reps with the right prescriptive Insights and at the right time. Prescribing the right behaviors in pipeline hygiene such as where a deal belongs or if you should close it out should be done with automation – reducing the time and effort to perform the pipeline housekeeping and admin work. Also, prescribing next steps and what needs to be done to make the deal healthy is better done with automation than manual inspection. This leaves more time for doing the things that count to fill the pipeline and to convert it.
Artificial intelligence will also keep track of what deals will come in that are not yet in the pipeline. (Click here to see a demo of TopOPPS Artificial Intelligence.)
Step 4: INSTANTANEOUS & EASY UPDATES
Forcing a rep to update the CRM or click all the checkboxes in the opportunity object is a waste for the manager and the rep. In order to make this work for the rep, and to get sufficient data in the CRM, you need two things to happen:
- Automatic integration with emails, meetings and appropriate roles and contacts
- Automatic sentiment analysis
- Guidance or prescription on “just” what needs to be updated and changed at the right time.
- The ability to bring just what needs to be updated to the surface by mobile device or wherever the rep is working – so the rep is not burdened with having to login or navigate to the appropriate fields.
Click here to see how TopOPPS makes updates seamless and easy for the sales rep.
By implementing these best practices you’ll have a very clear understanding of what’s real in the pipeline, what has momentum, and what the number will be for the current period and the next period. This will replace the old “I’ve got 3x in the pipeline so I’m good” method of assessing pipeline and quota health. Also, having AI for pipeline management and AI for sales forecasting is the easiest way to ensure these best practices are successful.
Contact a TopOPPS specialist for further guidance or to demonstrate how TopOPPS artificial intelligence for forecasting and pipeline management can help you get these results.