Recently, we posted an article on the top reasons why companies miss their revenue targets: Not setting effective revenue targets at all; Low quality of sales pipeline; Insufficient size of sales pipeline; Low closing ratios; and slow conversion of sales to revenue.
In this article, we will explore in some depth the first of the five reasons: Not setting effective revenue targets.
It has been our experience that the degree to which CEO’s are directly involved in setting effective revenue targets and how much effort and time senior management spends on this critical issue make the difference between meeting revenue targets consistently and missing them more often than not. This becomes more apparent as we investigate the process for effectively determining and defining the:
- Ideal growth rate for your company over the next 1-2 years
- Key Market Segments
- Foundational targets for each segment
- Operational numbers and metrics
- Schedule (Timing) of these Numbers
- Right Type and Amount of investment required
- Organization-wide commitment necessary
We will discuss each of the above in some detail next.
Determine the Growth Rate to Set Your Effective Revenue Target
We believe that the first mistake many companies make is in what they choose as their benchmark revenue year. Most automatically set their previous year’s revenue as the new benchmark. Others set a rolling average of the past three or five years.
Our recommendation is that a company should always use its highest historical revenue year as the benchmark, regardless of when that occurred or what special circumstances led to that. Such a policy re-enforces a mindset that if a company was able to achieve something once, not only can it achieve it again, but can also surpass it next time.
With the benchmark set at the highest historical revenue, the next step is to decide the rate of increase over that revenue base to discover your effective revenue target.
For discussion purposes, let’s say that a Company ABC did $50 million in its best year some years back, and the executive team decided to surpass that by 20% this year, or target $60 million in revenues.
Define Key Market Segments
Most companies sell a wide variety of products to a wide range of customer. At the same time, they tend to see these customers as a single large market.
We can usually tell that a company sells to a number of different market segments when we tend to get ambiguous answers to simple questions. For example, when we ask, “What is your average selling price?” and the response is, “It depends. It can vary anywhere from $10,000 to $500,000”; or “What is your average sales cycle?” and we hear responses like, ”Well that depends too. It can vary from 3 months to 24 months…” we know the customer base is made of more than one segment.
This typically happens because, initially, the company built a capability aimed at a specific group of customers, but later sees that the same capability can be sold to more customers outside of the original customer group. From the company’s point of view, it is essentially the same capability. However, customers use that capability for different purpose, have different levels of need for it (for some it is mission critical while for others it is back-up, and still others use it for convenience), and even different buyer roles. Hence the wide range of average sales price, sales cycles, and closing ratios.
A firm should to be able to confidently say, “For customer group A, we will target our average deal size to be X, and our average selling cycle to be Y, and our closing ratio to be Z”. Segmentation of its market is the key to such precision.
SOMAmetrics helps companies analyze their data and arrive at clear segmentation of their market.
Determine the Foundational Targets for Each Segment
The next task is to set the foundational targets for each market segment. Below is a sample list of foundational assumptions:
| Segment | A | B | C | Total |
| Targeted Revenue ($) | 30,000,000 | 22,000,000 | 8,000,000 | 60,000,000 |
| Avg. Selling Price ($) | 100,000 | 50,000 | 10,000 | 53,333.33 |
| Avg. Sales Cycle (months) | 9 | 6 | 4 | 6.33 |
| Avg. Closing Ratio | 25% | 20% | 30% | 25% |
| Sales needed | 300 | 440 | 800 | 1,540 |
| Sales Qualified Leads needed | 1,200 | 2,200 | 2,667 | 6,067 |
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From the above chart, the company knows it will need 1,200 sales opportunities or Sales Qualified Leads (SQLs) for Segment A in order to reach its $30million effective revenue target based on a $100K average sales price and 25% closing ratio.
The question here is where will these 1,200 new SQL’s come from.
Determine Operational Numbers
For most b2b companies, revenue has long lead-time measured in months if not years. The longer the sales cycle time, the more a company must frequently track and know its operational numbers so it can make adjustments early enough to make any difference.
Revenue is the final output that results from the interactivity of number of chained input factors. Before revenues happen, many other output factors must happen—each with its own interacting chain of events.
The tough part is usually getting the right quantity and type of the input factors at the right time at each link of the chain. For example, if the company doesn’t get the right amount of SQL’s, it will not make enough sales to reach its effective revenue target. SOMAmetrics uses the Four Funnels Framework to manage these operational numbers.
Traditionally, companies try to reach their SQL numbers with the combination of leads sent from Marketing, and sales reps doing their own phone prospecting. The hope is that somehow, from these two activities, the sales reps would generate their own Sales Qualified Leads to stoke their sales pipelines.
Both of these approaches tend to have shortcomings. Marketing should and will generate leads. However, there is very little to indicate whether these leads are hot, warm, or cold. It now becomes the sales reps responsibility to first determine that before proceeding.
At the same time, most sales people we know hate making cold calls and avoid doing so. They are even reluctant to call on leads provided by Marketing because many of these are rather cold.
Contrast that with a professional Teleprospector who actually loves making 60-90 dials a day, sees it as a challenge to break into an account, find the decision maker, engage her in a two-minute conversation to get her attention and interest, schedule a call with the sales rep, and then moves on to the next call.
Now, this is very different. This is a warm or even hot lead and the sales rep will jump on it, preferably within the next 48 hours.
The ideal best practices would be for Marketing to send warm leads to the professional Teleprospector whose main job now is to qualify these warm leads and makes sure it is a Sales Qualified Lead before passing on to the sales rep. Now, sales reps have a steady, well-stocked pipeline of qualified prospects on which to call at any given time.
Assuming that only 10% of the leads that Marketing provide turn out to be Sales Qualified Leads (SQL’s) ready to be passed on to sales reps, then the company must generate five (5) Marketing qualified Leads for each SQL.
The completed operational numbers look like this:
| Segment | A | B | C | Total |
| Targeted Revenue ($) | 30,000,000 | 22,000,000 | 8,000,000 | 60,000,000 |
| Avg. Selling Price ($) | 100,000 | 50,000 | 10,000 | 53,333.33 |
| Avg. Sales Cycle (months) | 9 | 6 | 4 | 6.33 |
| Avg. Closing Ratio | 25% | 20% | 30% | 25% |
| Sales needed | 300 | 440 | 800 | 1,540 |
| Sales Qualified Leads needed | 1,200 | 2,200 | 2,667 | 6,067 |
| Marketing Qualified Leads needed | 12,000 | 22,000 | 26,667 | 60,667 |
| Marketnig Impressions needed | 600,000 | 1,100,000 | 1,333,333 | 3,033,333 |
