Why Are Sales Down (or Up!)? Sales Funnel 101
This is part of an introductory series written for first-time sales managers and also for executives, founders, and owners whose day-to-day is not sales. Links to the rest of the series are at the bottom of this post.
Why are sales down (or up)?
You will face this question. The question will be asked of you or by you.
The bad news: even if you are not a Salesforce.com reporting savant or an Excel PivotTable ninja, you need to have an answer to this.
The good news: your answer (at least the start of it*) can usually fit on an index card using back-of-the-napkin math.
More important that doing the math yourself is learning to ask the right questions that point everyone toward what will be the right answers.
What follows is largely a guide in question-asking.
The sales funnel equation
Accounting has its own equation (Assets = Liabilities + Equity). Sales has its own, as well.
At its most basic level, this is the equation that you can write on an index card and carry around in your pocket. In some way, shape, or form, a sales funnel’s reality is captured in this.*
The questions to ask
Sales are down, you say?
Okay, look at the funnel and starting asking questions.
Note that the first-level answer to each of the below four questions is binary — it’s yes or no. It’s that simple (at least at this point).
Any “no” response is your metal detector dinging and saying, “Dig here!”
Warning: There’s a potential bogeyman assumption in all of the above, lurking in all of the metrics. It looms larger and larger as the delta between actuals and targets gets larger. It’s this question: is the problem the performance or the target (or some combination of both)? Targets are set to various degrees based on assumptions. These assumptions are a mix of historical precedent, speculation about the market, and (honestly) aspiration. If five months into a fiscal year your sales organization is way off target (especially if a lot of change went into the new fiscal year), you need to be willing to ask, “What are we learning from our experience so far this year? How does it differ from our expectations? How can we take what we are learning and make use of it moving forward?”
Digging
Ok, let’s do some digging. Below is each key question followed by suggested (but by no means exhaustive) “digging” questions.
- Close Rate: is your close rate on target? (Yes / No)
If yes, skip ahead to #2.
If no:
- What is your closed loss data telling you?
- Are close rates consistent across individual sellers, geographic regions, products, competitor, segments, deal size, etc.? Are they consistent across time frames, as well? Has their been any movement in them?
- Why are you losing? Are the areas that you are losing also opportunities for improvement?
2. Opp #: do you have your target number of opps? (Yes / No)
If yes, skip ahead to #3.
If no:
- Is everyone clear on the definition of an Opp? (More on this later)
- Where do your opps come from? Whether you are in a generalist or specialist model, your opps come from somewhere and someone(s) is / are responsible for generating all or some share of them. Everyone should have clarity on this. If you need 100 opps and marketing is responsible for generating 70, SDRs 20, and sellers 10, that needs to be clear and it has to be tracked and reported on. If you need 100 opps and only have 90, then it should take all of ten seconds to see which party / parties are delivering or not.
- If you identify one or more parties as the laggard, then you’re even more zeroed-in on where to keep digging. Keep digging.
3. Conversion %: are your leads converting at the expected rate? (Yes / No)
If yes, skip ahead to #4.
If no:
- Is everyone clear on Lead conversion criteria? (More on this later)
- Are there any scenarios that qualifiers are unclear about that could be causing inconsistencies in the results?
- What is your DQ data telling you? What are the DQ reasons? What are the patterns? Have the numbers moved over time? Is it consistent across segments, regions, employee, lead source, qualifier, etc.?
- Is the share of lead source contributions consistent? Example: maybe it used to be that 55% of your leads came from your best converting lead source but recently marketing spend has be reallocated and now only 35% of leads come from that lead source.
4. Lead #: is sales receiving the expected number of leads from marketing? (Yes / No)
If yes, skip ahead to #5.
If no:
- Just like with Opps, it should be clear who is responsible for generating what number of leads. Who is delivering or not?
- Is everyone clear on the definition of a Lead? (More on this later)
5. Average Sale Value: is the average sale value on target? (Yes / No)
If yes, skip ahead to #6.
If no:
- Is the issue consistent across all sellers, regions, segments, order types, products, etc.?
6. Average Age of Opp: are opps closing in the projected amount of time? (Yes / No)
If yes, you’re done. Summarize your findings.
If no:
- Is the issue consistent across all sellers, regions, segments, order types, products, etc.?
Signs of success
No matter how complex your Salesforce.com dashboards are, no matter how many moving parts your funnel has, ultimately your organization should be able in some way, shape, or form to affirm something like:
- “Sales are down because our close rates have dropped since Q1”
- “Sales are down because we only have 70% of the opps we projected to have. Marketing is generating 100% of their projected opps but the SDR team is way behind their projection.”
- “Sales are down because we only have 65% of the opps we projected. This is because leads are converting at half the target rate.”
…and so on.
It’s really no different than a factory manager being able to say, “We only produced 82% of projected widgets last month. When we investigated, we found that the problem was that we received only 79% of the raw materials from suppliers that we anticipated. We investigated the cause and found that issues within our procurement system delayed orders being placed for the raw materials that we needed.”
Is that your final answer?
Probably not.
*The above is simple but I don’t want to oversimplify. Whatever is going on in your sales funnel will show up in the numbers in some way — it’s unavoidable. If all you can say is, “Sales are down because lead conversion % is down” then one could argue that you haven’t really answered the ultimate “Why?” question yet. So you don’t really know why sales are down. You’ve identified a symptom but not the root cause. That’s fair push-back. What I’m trying to do here is offer a framework for systematically asking questions of the funnel. From there, you can just keep asking, “Why?” over and over until there’s nothing left to dig into and there’s (hopefully) only action left to take to address the problem. Sales may be down but the funnel itself doesn’t tell you that it’s due to specific market dynamics or changes in buying behavior or the entrance of a new competitor etc. But those realities will play out and show themselves in your funnel data somewhere. The funnel is a signal. The questions provided above are signals for where to dig.
But, there still is a helpful simplicity present in all of this. You can fairly easily set up repeatable (often real-time) reporting that captures these funnel dynamics and makes it obvious to everyone when the metal detector is dinging. It’s so much easier for leadership to start a conversation on the same page with something like, “We all know that opportunity totals are down in Q2 and that it’s specifically around opps that marketing usually provides. Let’s discuss…” That fits on the back of a napkin and is a crucial step that’s already been completed. Pat yourself on the back.
TL;DR Recap
- The Sales Funnel is an equation
- If Sales (bottomline results / outcomes) are off projection, then you start looking at the parts of the equation that feed into the bottomline to see where the problem is.
- The four basic places to look: 1. Close Rate, 2. Opp Count, 3. Lead Conversion Rate, 4. Lead Count
- Two additional places to look: 1. Average Sale Value, 2. Average Age.
- Once you identify the signal in the equation data, you dig to analyze and find out what is causing the problem.
- The funnel itself doesn’t tell you the root cause. But it signals where to dig.
