Do you ever wonder if your sales reps have enough leads to work or if they have so many leads that some are going un-contacted or getting lost in the sales funnel. If so, you aren’t alone, many of our clients have come to us with these same questions, so we thought we’d produce a comprehensive guide to help sales managers better optimize their leads-to-reps ratio. In this guide, entitled “Guide to: Optimizing Your Leads-to-Rep Ratio,” you will benefit from a sales methodology to help determine optimal lead volume per rep, per day to achieve peak performance from your team. You’ll also gain insights into the recommended practices around the distribution of work assignments and the days and times that reps are most productive and effective in order to help optimize your sales engine. What you will learn: - How to calculate the optimal number of leads for maximum revenue and/or profit growth - Days of the week sales reps are most effective - Times of the day sales reps are busiest – morning, afternoon, or evening

1. OPTIMIZINGYOUR
GUIDETO:
RATIOLEADS
TO REP
SALES OPTIMIZATION STUDY

2. SALES OPTIMIZATION STUDY
01
Executive summary
Imagine a top sales rep underutilized by 50%. Any sales manager having
visibility into the rep s utilization level would most certainly look to
increase the volume of leads assigned. Often, however, the utilization
threshold ‒ where results and productivity are at their optimal level ‒ is
incredibly hard to identify. At Velocify, we are often asked by sales leaders
how many leads they should be sending to their reps, or if they should hire
more reps given the volume of leads generated. This guide presents a
methodology to help sales managers determine optimal utilization levels
to achieve peak performance.
The analysis of millions of sales calls and associated metrics allowed us to
create a framework that enables organizations to calculate an expected
conversion rate based on the number of new leads assigned per rep per
day. This calculation, coupled with a standard profit formula, can also be
used to find the optimal lead volume necessary to break even, maximize
profits, or maximize revenues, depending on an organization s
ultimate goal.
In this guide, we also highlight current practices from our research, around
the distribution of work assignments and the days and times that reps are
most productive and effective in order to help organizations optimize their
sales engine. The application of these formulas to the data analyzed
revealed that sales reps are often underutilized and that workload is not
evenly distributed throughout the day or week.

3. Study Methodology
This data reflects results aggregated across multiple industries
during a six month period. More than 5 million calls made by
more than 2,000 users were analyzed to arrive at the results
presented in this study.
In order to collect the most detailed call data possible, only
Velocify clients and users taking advantage of Dial-IQ,
Velocify s intelligent dialer, during the six month period
studied were included in this analysis. Additionally, in the
analysis of rep data, the numbers reported reflect only the data
for reps that appear to be active in the system, meaning that
they are being assigned leads and working them during a
given hour.
It is important to note that while these results and
recommendations are widely applicable, they may not reflect
the optimal strategy for some businesses.
SALES OPTIMIZATION STUDY
02
Many sales organizations experience struggles between their sales and
marketing teams. Sales might claim they aren t receiving enough leads,
while marketing might claim the leads they re generating aren t receiving
the proper attention from sales. So, who is right ‒ sales or marketing? How
many new leads should each sales rep get on a daily basis? Are they being
given more than they can handle? Is it better to give them a small number
of leads to make sure they are doing everything possible to convert every
one of those leads?
Finding the optimal operating level, given each organization s unique goals
and conditions, can be an art form and is usually a guessing game for sales
managers. Fortunately, we can use historical data from a large number of
sales organizations to predict possible outcomes as lead assignment levels
are changed so that each organization can find its optimal leads-to-rep
ratio. If changes are necessary to current lead assignment volumes, it is
important to understand the level of rep utilization, when reps are the
busiest, most effective, and most productive, and the factors that have the
greatest impact on those measures in order to identify the ideal days and
times to reduce or increase the number of new lead assignments.
BACKGROUND

4. SALES OPTIMIZATION STUDY
03
Identifyinga Sales Rep s Peak Performance Zone
One of the keys to arriving at an optimal rep utilization level is determining
how workload affects reps results. One of the most interesting insights
gleaned from this research was the predictability of sales rep performance
(measured in terms of conversion rate) using the number of brand new leads
assigned to that rep. Figure 1 shows the rate at which a rep s ability to
convert a high percentage of leads decreases as that rep is assigned a
higher number of new leads per day. In other words, reps assigned more
leads will likely convert more leads, but at a lower conversion rate as lead
count increases. There are many factors that influence conversion rate, but
this study suggests the number of new leads assigned per rep per day is a
valuable predictor.
Based on this data, Table 1 allows one to estimate expected conversion rates
based on the number of new lead assignments per rep per day
A
. The two
primary reasons this negative relationship exists between a rep s conversion
rate and the number of new leads assigned are: (1) as workload increases,
reps effectiveness is more likely to decrease and (2) in some cases,
larger lead volumes usually come from lower quality lead sources. The
more new leads reps are assigned, the less likely they are to respond to each
new lead quickly.
RESULTS
APlease see Appendix A for the formula used to create Table 1. One can also use the formula to calculate expected
conversion rates for different numbers of new leads assigned per rep per day that may not be shown in the table.
Table 1: Conversion rate estimates
Figure 1: Impact of lead volume on conversion
conversionrateperrep
new leads assigned per rep per day
60.0%
50.0%
40.0%
30.0%
20.0%
10.0%
0.0%
0 5 10 15 20 25 30 35
1
2
3
4
5
8
new leads per
rep per day
expected
conversion rate
10
12
15
20
25
30
24.5%
14.2%
10.3%
8.2%
6.9%
4.8%
4.0%
3.5%
2.9%
2.3%
1.9%
1.7%

5. SALES OPTIMIZATION STUDY
04
At some point, reps may receive so many new leads that efforts to contact
all of them would leave no time for follow-up attempts. Eventually, their
only conversions might come from those they are able to close on the first
call, which for most industries can be extremely difficult, if not impossible
(please refer to prior Velocify research on the Ultimate Contact Strategy,
which illustrates what methods to use and how often to contact a
prospect). Moreover, if lead volume were to increase even further, reps
would not have enough time to even attempt to contact all newly assigned
leads. At this point of oversaturation, any additional leads assigned would
be completely wasted.
These findings reveal something most sales managers already know: there
is both a minimum and maximum lead volume per rep that is
necessary to break even. If you operate with a lead volume below the
minimum number, the small revenues you may be able to generate will not
cover the costs of running your business. On the other hand, if you operate
with a lead volume above the maximum number, the cost of generating a
large number of leads will exceed the benefit gained from additional
revenue. Logically, the key to maximizing profits is finding the peak
performance point between the minimum and maximum lead volumes,
as illustrated in Figure 2A.
RESULTS
Figure 2A: Maximizing profit (example)
profitpersalesrepperday
new leads assigned per rep per day
$200.00
$150.00
$100.00
$50.00
$0
$(50.00)
$(100.00)
$(150.00)
0 5 10 15 20 25 30

6. SALES OPTIMIZATION STUDY
05
Obviously, finding those values is different for every organization and is
dependent on a number of factors, which include the Lifetime Value of a
customer (LTV), the Number of New leads assigned per rep per day (N), the
Expected Conversion Rate (ECR), the Commission per Sale (CPS), the Cost
per Lead (CPL), the Direct Cost per Rep per day (DCR), and the Other Costs
of Sales (OCS)
B
.
Figure 2 shows that for an organization with values similar to those used in
this example, each rep would need to be assigned an average of just over
two new leads per day in order to add value to the company and for the
company to be profitable. Also, the maximum profit contribution per sales
rep would be achieved at approximately 11 new leads per rep per day.
Finally, for an organization that is most interested in growth and not
necessarily profit without adding more reps, the highest volume that still
allows them to break even is shown to be about 28 new leads per rep per
day. The maximum value is not indicative of a rep s actual capacity, which
is dependent on an individual rep s skill level. Instead, it is just the value at
which most companies will begin to incur losses from a typical rep because
they re wasting away too many leads.
RESULTS
B
See Appendix B for the complete profit formula and sample values used to generate Figure 2
Figure 2B: Maximizing profit (example)
profitpersalesrepperday
new leads assigned per rep per day
$200.00
$150.00
$100.00
$50.00
$0
$(50.00)
$(100.00)
$(150.00)
0 5 10 15 20 25 30
Optimal
Minimum Maximum

7. SALES OPTIMIZATION STUDY
06
Table 2 summarizes these three key values for the example given. Just as
the expected conversion rate can be calculated using a formula based on
data from this research
A
, a detailed profit formula
B
, which is dependent on
the expected conversion rate, can be used to calculate expected profits
given a variety of different inputs, allowing organizations to find their
breakeven lead volumes and their optimal lead volume for maximum
profit. A little bit of calculus results in an optimal lead volume formula
C
that
is only dependent on LTV, CPS, and CPL, assuming all other factors stay
fixed as lead volume per rep changes.
RESULTS
A
Please see Appendix A
B
Please see Appendix B
C
Please see Appendix C
Table 2: Critical lead volumes (example)
10.6
28.2
new leads per
rep per day
expected
conversion rate
sales profit per
rep per day significance
3.81%
1.77%
2.1 13.6%
0.00
0.00
180.85
$
$
$
Minimum lead volume per rep to be profitable
Optimal lead volume for maximum profit
Maximum lead volume for highest revenue without profit losses

8. SALES OPTIMIZATION STUDY
07
The optimal lead assignment level can be calculated using the optimal lead volume formula
C
or it can be estimated using the values for CPL and LTV ‒ CPS along
with Table 3. For example, for a company with an LTV of $9,000, a CPS of $1,000, and a CPL of $50, we would need to look across the $50 row and down the $8,000
column (LTV-CPS=$8,000), and we would find that 15 is the optimal number of leads we should assign each rep per day for maximum profit. If this company were
currently assigning fewer than 15 new leads per rep, they should work on increasing the number of new lead assignments. On the other hand, if they were
RESULTS
C
Please see Appendix C
(cont. on next page)
Table 3: Finding the number of new leads to assign each rep per day to maximize profits
(CPL) $500 $1,000 $2,000 $3,000 $4,000 $5,000 $6,000 $8,000 $10,000 $15,000 $20,000 $25,000 $30,000
$5 8 20 48
$10 3 8 20 33 48
$15 2 5 12 20 28 38
$20 3 8 14 20 26 33
$30 5 8 12 16 20 28
$40 6 8 11 14 20 26
152 192 277 367 615 886 1176 1486
115 152 255 367 488 615
152 219 291 367
106 152 202 255
121 152
106
$50 6 8 10 15 20 33
$60 6 8 12 16 26 38
$80 6 8 11 18 26 35
$100 6 8 14 20 26 33
$150 5 8 12 16 20
$200
0
0
0
0 0
0 0
0 0 0
80 115
63 80
48 68 91
1 48 63
1 2 38 63 91
1 1 3 44 63 84
1 3 4 48 63 80
1 2 3 5 50 63
1 1 2 3 4 44
1 2 3 3 4
1 1 2 2 3 4
1 1 1 2 3 3 6 8 11 14
Cost per
Lead
Lifetime Value (LTV) minus Commission per Sale (CPS)

9. SALES OPTIMIZATION STUDY
08
exceeding that lead volume, they should probably consider hiring more
reps to reduce the workload at that lead volume because it is likely that the
cost of wasted leads is reducing their profits. Similarly, a company can
calculate how many reps they need by taking their daily lead volume and
dividing it by the optimal number resulting from Table 3. For example,
if the company in the example above generates 600 new leads per day,
the number of reps that will result in maximum profits is equal to
600/15= 40 reps.
For reference, and as a point of comparison, the average sales rep in our
study was assigned less than six new leads per day. Given the results
shown in Table 3, most organizations would likely benefit from
increasing the number of new leads they are assigning their reps each
day because most probably fall within the green operating range of Table
3, which generally suggests that optimal lead volumes should be at least
double what they are currently for maximum profit. At those volumes, the
expected conversion rates are between two and five percent. Comparably,
lead volumes should be even larger for maximum revenue growth.
One of the easiest and fastest ways to achieve larger lead volumes without
significantly impacting other costs of sales (OCS) is simply to purchase
more leads, but regardless of how new lead volumes are increased, it is not
advised that one just increase new lead assignments indiscriminately. As
the remainder of this study shows, there are clearly better and worse days
and times to increase or decrease the number of new leads assignments
based on rep availability, productivity, and effectiveness.
RESULTS

10. SALES OPTIMIZATION STUDY
09
Lead Volume Decreases Considerably onWeekends
One of the first set of factors that an organization should look at when
considering lead assignment changes is their current distribution of leads
throughout the different days of the week. Overall, the number of lead
assignments is pretty evenly distributed throughout the first four days of the
workweek. As Figure 3 illustrates, there is approximately a 30% drop in
lead volume on Fridays and about a 90% drop on Saturdays. However, the
average number of lead assignments per rep per hour remains about the
same Monday through Saturday, indicating that most companies reduce
the number of active sales staff and/or the number of hours worked on
Fridays and Saturdays in proportion to the drop in lead volume. Figure 3 also
reveals that the total number of lead assignments is clearly lowest on
Sundays. Additionally, sales reps that do actively work leads on Sundays, on
average, are assigned 20% fewer leads per hour than they are during the
other days of the week. The drop in total lead volume on weekends is
probably not a surprise given the majority of sales organizations do not
operate on weekends.
RESULTS
Figure 3: Total lead volume assigned
19.6%
22.0%
21.3%
20.1%
14.1%
Friday
Saturday Sunday
0.3%2.5%
Monday
Tuesday
Wednesday
Thursday

11. SALES OPTIMIZATION STUDY
10
Lead Assignments and Activity per Rep
Decrease throughout the Day
Although the average number of lead assignments per rep per hour is
evenly distributed throughout the different days of the week, except
Sunday, lead assignments per rep per hour are not evenly distributed
throughout each day. Figure 4 shows that the total number of newly
assigned leads per rep per hour is highest early in the day and declines as
the day progresses. Notice the total number of lead assignments is
comprised of both brand new leads and re-assigned leads. Re-assigned
leads, which typically outnumber brand new leads, are leads that have
been previously assigned to one rep, but for a variety of reasons are
re-assigned to a different rep.
RESULTS
Our research found that the bigger the sales team, the more likely reps will
receive a higher proportion of re-assigned leads. Lead re-assignments are
normally highest earlier in the morning as reps catch up on prospects
requiring follow-up that accumulated overnight. This is especially true in
cases where a number of reps start earlier in the day, before the rest of the
team, driving lead re-assignments when reps originally assigned to certain
leads have not started working yet. Consequently, the total number of
lead assignments per hour per rep decreases throughout the day,
primarily because the number of re-assigned leads decreases. But also, as
shown in Figure 4, the number of brand new leads assigned per rep is
slightly higher earlier in the day.
Figure 4: Lead volume by time of day
new leads re-assigned leads
averagenumberofassignedleads
perhourperrep
6.00
5.00
4.00
3.00
2.00
1.00
0.00
6:00 am
7:00 am
8:00 am
9:00 am
10:00 am
11:00 am
12:00 pm
1:00 pm
2:00 pm
3:00 pm
4:00 pm
5:00 pm
6:00 pm
7:00 pm
8:00 pm
after hours

12. SALES OPTIMIZATION STUDY
11
Our research found that for the most part, time spent on the phone and
the number of phone calls and actions taken on a lead were very much
in line with lead volume assignments. In other words, the more leads a
rep is assigned per hour, the more time one can expect the rep to be on
the phone and the higher the activity one can expect on leads.
Consequently, since reps typically have a larger number of lead
assignments earlier in the day (Figure 4), they tend to make more phone
calls, take more actions in the system, and spend a higher proportion of
their time on the phone earlier in the day, leaving them with more
available time in the afternoon and early evening.
ProductivityandEffectivenessPeakonWeekends
Similarly, since the average lead assignments per hour are fairly constant
across each day of the workweek, the average time spent on the phone
per hour is also fairly constant. Interestingly, Saturday and Sunday had
higher percentages of phone time per hour than Monday through Friday
even though the number of leads assigned per rep are the same on
Saturdays as they are during the workweek, and even lower on Sundays
than they are any other day. On average, sales reps spend approximately
20 minutes per hour on the phone on weekends versus only 15 minutes
on the phone per hour during the workweek.
The fact that sales reps are spending only a quarter, or at best a third, of
their time on the phone also suggests that most reps are probably being
underutilized from an overall capacity standpoint. Most sales
organizations would probably not want or need their sales reps to spend
100% of their time on the phone either, but these results indicate the
opportunity for added phone time per rep exists, further supporting the
earlier finding that most organizations would probably benefit from
assigning a higher number of new leads per rep.
RESULTS

13. SALES OPTIMIZATION STUDY
12
One of the main reasons reps tend to spend more time on the phone per
hour on weekends is that they spend a lower percentage of their time on
the phone waiting to connect and a higher percentage of their phone
time actually connected. Reps spend 25% of their phone time waiting
and trying to connect during the workweek but only about 20% of their
phone time on weekends. This is largely because reps are more
successful in contacting a higher percentage of their leads on the
weekends, with the greatest success rate on Sundays, when 11% of all
calls made successfully connect. That s almost double the 6% connection
rate of weekdays. For more information about the largely untapped
opportunities that exist for working on weekends, please see Velocify s
study on The Value of Weekend Leads Unveiled. Furthermore, Saturdays
are when reps are most productive, making 25% more calls than they
normally make during the workweek, as shown in Figure 5.
RESULTS
Figure 5: Average Calls per Hour per Rep
16
14
12
10
8
6
4
2
0
Monday
Tuesday
W
ednesday
Thursday
Friday
Saturday
Sunday

14. Note:
While these results may provide a benchmark and a point of
reference, the best way to make use of this information is to
actually compare them to your team’s specific metrics and
performance. Velocify’s solutions allow you to track and monitor
your team’s activity and effectiveness so that you too can optimize
your sales engine.
SALES OPTIMIZATION STUDY
13
Takeaways and Recommendations
While a rep s productivity usually increases as more leads are
assigned, conversion rate drops as reps are assigned a higher
number of new leads per day.
It is possible to calculate the expected conversion rate of a rep
based on the number of new leads assigned per rep per day
A
. This
calculation provides a higher degree of clarity around rep
utilization.
The expected conversion rate formula
A
coupled with a detailed
profit formula
B
can be used to calculate three key lead volume
operating levels for an organization.
• The first breakeven point can provide the minimum
number of new leads a rep needs to be assigned per day
in order to make profitable contributions.
• The second breakeven point provides the maximum
number of leads that can be assigned without losing too
much money on wasted leads- this is the optimal volume
for organizations interested in revenue growth rather
than maximum profit.
• The final key operating level is between the two
breakeven points, where the number of new leads
assigned per rep maximizes the rep s profit contribution
C
.
Data suggests that most organizations would likely benefit from
increasing the average number of new leads assigned per rep per
day.
Lead assignments per rep per day are fairly constant Monday
through Saturday but drop about 20% on Sundays.
Lead assignments per rep decrease throughout the day.
Reps typically make more calls, take more actions, and spend more
time on the phone when they are assigned more leads.
Reps are generally most productive on Saturdays and most
effective in contacting leads on Sundays, signaling an untapped
opportunity.
Ideally, organizations should try to increase the number of new
leads assigned to reps during the hours and days in which reps tend
to be most available, productive, and/or effective, which means in
the afternoons, for most companies, and on weekends, for those
companies whose industry and business conditions allow for that
option.
SUMMARY& CONCLUSIONS
A
Please see Appendix A
B
Please see Appendix B
C
Please see Appendix C

15. Call: (888) 843-1777
Email: sales@velocify.com
Visit our website: www.velocify.com
Visit our blog: velocify.com/blog
LIKETHISSTUDY?
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SALES OPTIMIZATION STUDY
14
About Velocify
Velocify is a market leading provider of cloud-based intelligent sales
automation solutions that drive more effective and efficient sales
processes and improved conversion rates. With unmatched expertise,
drawn from a dedication to helping more than 5,000 clients automate and
improve their lead response and selling processes, Velocify has become
the platform of choice for organizations focused on improving customer
acquisition practices and business performance. Velocify is a privately held
company, recently recognized as one of the fastest growing companies in
North America on Deloitte s 2012 Technology Fast 500. Please visit
www.velocify.com for more information.
CONTACT&SHARE

16. SALES OPTIMIZATION STUDY
15WPLM0313
Appendix A Expected Conversion Rate Formula:
The measure for reliability (R
2
) for the equation derived from the analysis of real performance data indicates that more than 43% of the variability of reps conversion rate can be
explained by the rate at which they are assigned brand new leads. Therefore, the following equation can be used to predict a rep s expected conversion rate:
Appendix B Detailed Profit Formula:
Appendix C Optimal Lead Volume Formula:
Optimal number of new lead assignments per rep per day =
Conversion rate = 0.245×(Number of new assigned leads per rep per day)-0.787
Profit per rep per day = (LTV×N×ECR)-(CPS×N×ECR)-(CPL×N)-DCR-OCS, where:
LTV = Lifetime Value of a Customer
= (Expected revenue over the lifetime of a customer-Cost of product or services) or
= (Expected revenue over the lifetime of a customer×Gross margin) = Used $4,000 in Figure 2
N = Number of New Leads Assigned per Rep per Day = Independent Variable
ECR = Expected Conversion Rate = 0.245×(N)-0.787 = Calculated using N values
CPS = Commission per Sale = Average $ amount paid to a rep for each closed sale = Used $300 in Figure 2
CPL = Cost per Lead = Average direct cost to generate or purchase a lead = Used $30 in Figure 2
DCR = Direct Cost per Rep per Day = Base salary and benefits for a rep per day = Used $200 in Figure 2
OCS = Other Costs of Sales per Rep per Day
= Other costs including supplies, telephone, facilities, marketing support, etc. broken down per rep per day = Used $800 in Figure 2
APPENDICES
.0235×
(LTV-CPS)
[ ]CPL
1.27