no part of this publication may be reproduced, …...5 pipeline to understand and provide...
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EXECUTIVE SUMMARY
Sales development is one of the more misunderstood roles in sales. Many people debate
the definition of sales development while others argue which department it should report
into or how much sales development reps should be compensated. Either way, the sales
development role is here to stay. In an effort to understand the sales development
function and its role in the sales process, InsideSales.com Labs led a study in partnership
with Tenbound, SalesForLife, BridgeGroup, Drift, Datanyze, and OneMob. The study
focused on 1000+ companies and reviewed the structure, systems, people, and pipeline
of their respective sales development organizations. In addition, the report highlights the
typical four steps a sales development rep takes to be successful (identify, contact, qualify,
and pass).
STRUCTURE
Using US census data, the estimated number of professional sales people in the U.S. in
2017 is 5.7 million and that number is expected to grow to 5.9 million by 2024. According
to the research, inside sales professionals (reps who primarily sell remotely) represent
47.2% of the 5.7 million (2.7 million reps) and outside sales professionals (reps who
primarily sell face-to-face) represent 52.8% (3.1 million reps). Based on the survey
responses, sales development reps are 25.1% of the 47.2% inside sales professionals
making the ratio equal to one sales development rep for every three account executives.
The total number of sales development reps is estimated to be 677,479. Examining the
data revealed that not every sales development rep is the same. The primary difference in
sales development reps is the characteristic of inbound (reps who reach out to someone
who knows your company) and the characteristic of outbound (reps who reach out to
someone who doesn’t know your company). Of the 677,479, inbound sales development
made up 17.1% (115,849 reps), outbound made up 28.8% (195,114 reps) and 54.1%
(366,516 reps) were a blend of both. Another difference in sales development reps is the
go-to-market strategy of high-velocity versus account-based. 12.4% of companies
reported they run a high-velocity model while 43.0% reported they run an account-based
approach and 44.6% said they used both.
4
SYSTEMS
Because of the nature of the sales development role, it often lends itself to more
automation than other roles in the sales department. Examining the data revealed the
overall estimated spend on sales development technology is $1.4 billion of the overall
estimated 14.9 billion sales technology industry. Companies reported the average annual
spend on sales technology was $3,827 per rep per year or $318.92 per month – which is
19.7% lower than the spend on sales technology for account executives.
The $3,827 covers an average of 4.9 tools per rep with the most popular tools being:
1. CRM
2. Social prospecting
3. Data/list services
4. Email engagement
5. Phone
6. Sales Cadence
PEOPLE
The career path for sales development reps differs across companies and industries but
one thing is for sure, not understanding and paying market rates for top talent will hurt
companies in the long run. The study revealed the average base salary for sales
development reps is $43,499 with an average on-target-earnings (OTE) of $83,484 – a
60/40 split on average.
On average, companies used 2.6 metrics to calculate variable compensation. The most
common metrics used were closed revenue (37.3%) with an average quota of $89,333,
number of opportunities accepted (19.2%) with an average quota of 15.2 opportunities,
and number of appointments held (12.6%) with an average quota of 19.2 appointments.
Considering all quotas, companies report 63.8% attainment for SDRs. With these
compensation structures in place, the average tenure of a sales development rep is 2.7
years which includes a 4.0-month average ramp time.
5
PIPELINE
To understand and provide benchmarking capabilities, companies reported sales pipeline
numbers. Sales development reps did an average of 93.8 daily activities including an
average of 37.2 phone calls (39.7%), 36.2 emails (38.6%), 15.2 voicemail messages
(15.2%), and 7.7 social media touches (8.2%). These activities led to an average of 13.6
meaningful conversations a day—14.5% conversation rate. The 13.6 conversations per
day resulted in an average of 22.5 appointments set per month--5.5% appointment rate.
73.2% of appointments set become opportunities passed to account executives and the
typical sales development rep had 12.3 opportunities accepted per month--74.8%
opportunity acceptance rate. Of the opportunities accepted, 33.2% closed, which means
that the average sales development rep is responsible for about 12.3 deals per quarter.
6
SALES DEVELOPMENT STRATEGY
STRUCTURE
SALES DEVELOPMENT REPS MAKE UP 10.7% OF SALES REPS IN THE US
Overall, it is estimated that there are 611,933 SDRs in the US, making up 10.7% of the
5.7 million professional sales reps. The typical sales organization studied has 12.9 sales
development reps.
SDR10.7%
Inside AE32.8%
Outside AE56.5%
SDRs Percentage of Sales Organization
7
SDRS MAKE UP NEARLY A QUARTER (24.6%) OF THE INSIDE SALES ORGANIZATION
In the study, there were multiple types of SDRs identified.
• Inbound – a team that reaches out to someone who knows your company • Outbound – a team that reach out to someone who doesn’t know your company • Blended– a team that does both
Blended SDRs make up the biggest proportion of SDRs and represent nearly 1 in 10
remote sales reps (9.8%). SDRs in total make up nearly a quarter (24.6%) of remote or
inside sales reps.
Inbound SDR6.1% Outbound SDR
8.6%
Blended SDR9.8%
Inside AE75.4%
Inside Sales Roles
Total SDR24.6%
8
56.0% OF COMPANIES REPORTED USING A HIGH-VELOCITY SALES MODEL AND 86.9% OF
COMPANIES REPORTED USING AN ACCOUNT-BASED SALES MODEL
Respondents were not given a definition of different sales models but were simply asked
what type of sales model they operated. Account-based sales models were by far the
most popular option (86.9%), though a large portion (42.9%) reported having teams of
both a high-velocity and account-based models depending on need.
High-velocity13.1%
Account-based44.0%
Both42.9%
Inside Sales Models
9
38.3% OF COMPANIES WHO HAD SMALL DEAL SIZES REPORTED HAVING AN ACCOUNT
BASED SALES MODEL WHILE 8.15% OF COMPANIES WITH LARGE DEAL SIZES REPORTED
HAVING A HIGH-VELOCITY MODEL
Generally, account-based sales models should be reserved for companies who close large
deals with multiple decision makers. However, with the popularity of account-based sales,
many teams have switched models potentially prematurely as 38.3% of companies who
have small deal sizes report using an account-based model. On the other hand, 8.15%
companies working larger, more complex deals have implemented a high-velocity sales
model, an approach normally best suited for companies who close small deal sizes with
only a few decision makers.
Account-Based38.3%
Account-Based46.7%
High-Velocity18.1%
High-Velocity8.1%
0%
10%
20%
30%
40%
50%
60%
Small Deal Sizes Large Deal Sizes
% o
f re
spo
nd
en
ts
Sales Model by Deal Type
10
COMPANIES WITH HIGH-VELOCITY SALES MODELS RELY MORE HEAVILY ON MARKETING TO
GENERATE PIPELINE (39.4% OF PIPELINE) THAN ACCOUNT-BASED SALES TEAMS (26.6% OF
PIPELINE)
While SDRs contributed a similar proportion of pipeline in each sales model, high-velocity
sales models received 48.1% more pipeline from marketing than teams who operated an
account-based model. The role of marketing has been traditionally one of the key
differences in an account-based model versus a high-velocity model. Because of the lower
production of marketing in an account-based model, sales reps must make up the
difference accounting for 36.1% more pipeline in an account-based approach versus high-
velocity.
30.8% 29.3%
26.6%39.4%
42.6%31.3%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Account-based High-velocity
% o
f p
ipelin
e
Source of Pipeline by Sales Model
Sales
Marketing
SDR
11
A MAJORITY OF COMPANIES (61.1%) HAD A TEAM THAT HANDLED THE ROLES OF BOTH
INBOUND AND OUTBOUND SDRS
Having a dedicated inbound team was the least common type of sales development
structure at 28.7%. Outbound teams were the second most common with 36.9%. Blended
teams were by far the most common with 61.1% of companies reporting having this team.
28.7%
36.9%
61.1%
0%
10%
20%
30%
40%
50%
60%
70%
Inbound Outbound Blended
% o
f re
spo
nd
en
ts
SDR Teams
12
HAVING ONE TYPE OF AN SDR TEAM WAS THE MOST COMMON PRACTICE (78.8%), BUT
21.2% OF COMPANIES HAD TEAMS OF AT LEAST TWO TYPES
While it was very common to have teams that served inbound and outbound SDR
functions, it wasn’t as common to have both as separate teams. The majority of
companies (78.8%) had only one type of SDR team.
78.8%
15.7%
5.5%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
1 Team 2 Teams 3 Teams
% o
f re
spo
nd
en
ts
Number of SDR Team Types
13
SYSTEMS
COMPANIES SPEND AN AVERAGE OF $2,027 PER SDR PER YEAR ON SALES TECHNOLOGY
Companies spend an average of $2,027 per SDR per year on sales technology but this
does not include CRM spend. Companies report they expect the overall amount to
increase by 3.8% in 2018. This equates to $169 per month per rep in 2017 and $175 per
month per rep in 2018.
The average sales development rep uses an average of 4.9 sales technologies for their
SDRs.
$2,027.00 $2,103.00
$0.0
$500.0
$1,000.0
$1,500.0
$2,000.0
2017 2018
SDR Tech Spend Growth
14
COMPANIES WITH BLENDED SDR TEAMS UTILIZE 20.7% MORE SALES TOOLS THAN THOSE
WHO ONLY HAVE INBOUND OR OUTBOUND TEAMS
A blended sales development team means the reps respond to inbound leads and reach
out to ‘cold’ prospects. These blended teams adopt 29.7% more technology (1.1 more
tools) than inbound focused teams and 11.6% more technology (0.5 more tools) than
outbound teams.
3.7
4.3
4.8
0
1
2
3
4
5
Inbound Outbound Blended
Nu
mb
er
of
too
ls
Technology Tools Adopted by Team Type
15
BIGGER DEALS ARE ASSOCIATED WITH A 17.0% HIGHER AVERAGE TECHNOLOGY
UTILIZATION COMPARED WITH COMPANIES WITH SMALLER DEAL SIZES
Companies who focused on larger deals utilize more technology than companies who
focus on smaller deals by 17% (.8 more tools). Larger deals often come with more decision
makers and more complexity, so companies may be more inclined to use sales
technologies to assist their SDRs.
4.7
5.5
0
1
2
3
4
5
6
Small Deal Sizes Large Deal Sizes
Nu
mb
er
of
too
ls
Technology Tools Adopted by Team Type
17.0%
16
SOCIAL PROSPECTING (82.5%) IS THE HIGHEST ADOPTED TOOL FOR SALES DEVELOPMENT
REPS AND GAMIFICATION IS THE TOOL WITH HIGHEST EXPECTED GROWTH IN 2018 (83.1%)
The highest adopted sales technologies for SDRs were social prospecting (82.5%) tools
like LinkedIn Navigator, data and list services (58.5%) like ZoomInfo, and email
engagement (55.3%) like InsideSales.com. New to the list was sales cadence tools (37%
adoption) that combine phone and email to allow reps to manage their follow up strategy
effectively.
The expected growth of sales technologies for sales development reps provided many
interesting findings. Although gamification has been available to reps for years, it is one of
the lowest-adopted technologies (12.0%) but it expected to see the biggest growth
(84.1%). Video capability in emails (30.9%) as well as direct mailers (11.4%) as part of the
prospecting strategy are both relatively new to the sales development world round out
the top five tools expected to see the biggest growth in 2018. These two tools provide
reps the ability to differentiate and fit nicely into the popular account-based approach, so
it may not be surprising to see them high on the growth list.
Adoption
Tool Categories 2017
Social Prospecting 82.5%
Data/list services 58.5%
Email Engagement 55.3%
Phone 43.4%
Sales Cadence 37.0%
Chat 28.7%
Lead/Account Scoring 28.5%
Sales Intelligence 28.2%
Reporting 22.9%
Lead Routing 19.2%
Sales Coaching 16.5%
Video Outreach 16.0%
Direct Mailer 13.8%
Gamification 12.0%
Sales Signals 9.6%
SMS 9.3%
Growth
Tool Categories 17-18 Growth
Gamification 83.1%
Video Outreach 30.9%
Sales Coaching 22.5%
Sales Signals 14.5%
Direct Mailer 11.4%
Lead/Account Scoring 4.7%
SMS -0.7%
Sales Cadence -0.9%
Reporting -1.2%
Lead Routing -5.2%
Chat -8.2%
Email Engagement -9.0%
Social Prospecting -9.9%
Phone -11.5%
Data/list services -11.6%
Sales Intelligence -15.0%
17
18
TEAM TYPE AFFECTED WHICH SALES TOOLS HAD THE HIGHEST ADOPTION RATE
The highest-adopted sales tools were different depending on the type of team a company
used. Inbound teams focused on data/list services while outbound teams and blended
teams had the highest adopted in social prospecting tools.
Adoption
Tool Categories Inbound Outbound Blended
Data/list services 93.2% 91.4% 89.7%
Social Prospecting 92.8% 93.8% 94.2%
Email Engagement 91.7% 93.2% 92.6%
Phone 89.7% 88.7% 92.7%
Sales Intelligence 88.6% 86.7% 79.7%
Sales Cadence 86.4% 88.2% 77.8%
Reporting 84.1% 85.7% 85.0%
Lead/Account Scoring
80.0% 79.3% 73.8%
Lead Routing 77.8% 75.0% 86.5%
SMS 76.5% 81.0% 74.1%
Sales Coaching 71.4% 75.7% 66.7%
Sales Signals 68.8% 80.0% 65.6%
Direct Mailer 68.0% 74.2% 72.7%
Video Outreach 65.5% 71.1% 57.9%
Gamification 63.6% 61.5% 45.8%
19
WHILE SOCIAL PROSPECTING WAS THE HIGHEST ADOPTED TOOL FOR BOTH SMALL AND
LARGE DEALS, ADOPTION WAS 7.8% HIGHER IN COMPANIES WITH LARGER AVERAGE DEAL
SIZES
Adoption of technology tools was generally higher for companies with larger deal sizes.
The only exception was sales coaching, which had 10.9% higher adoption in companies
with smaller deal sizes.
The biggest difference between companies that focus on small deal sizes and large deal
sizes, is the use of sales intelligence tools (18.5% higher adoption for larger deal sizes) and
direct mail tools (20.2% higher adoption for larger deal sizes).
Adoption
Tool Categories Smaller Deal Sizes Larger Deal Sizes % Difference
Social Prospecting 89.6% 96.6% 7.8%
Data/list services 89.2% 89.2% 0.0%
Email Engagement 89.2% 94.0% 5.4%
Phone 86.2% 91.8% 6.5%
Chat 83.1% 85.7% 3.1%
Sales Cadence 80.0% 84.1% 5.1%
Reporting 76.9% 90.5% 17.7%
Lead Routing 73.8% 87.2% 18.2%
SMS 73.3% 75.0% 2.3%
Sales Intelligence 72.1% 90.6% 25.7%
Lead/Account Scoring 71.3% 72.5% 1.7%
Sales Coaching 68.0% 61.3% -9.9%
Direct Mailer 63.6% 83.9% 31.9%
Video Outreach 63.3% 55.6% -12.2%
Sales Signals 61.3% 63.2% 3.1%
Gamification 45.2% 53.1% 17.5%
20
PEOPLE
THE AVERAGE BASE SALARY FOR SALES DEVELOPMENT REPS WAS $43,499 WITH AN
AVERAGE OTE OF $83,484.
Salary for sales reps varies significantly by location but across all companies surveyed, the
average base salary was $43,499 with an OTE of $83,484.
The balance between base and variable salary averaged close to 60/40 split (56%
base/44% variable).
$43,499
$83,484
$-
$25,000
$50,000
$75,000
$100,000
Base Salary OTE
Average Salary
Base Salary
OTE
56%
21
BLENDED SDR TEAMS TENDED TO HAVE HIGHER BASE AND VARIABLE SALARIES THAN BOTH
INBOUND AND OUTBOUND TEAMS
The on-target-earnings (OTE) of blended SDR teams was 16.2% higher than the average
OTE for inbound and outbound teams.
$41,238
$33,524
$48,027
$75,510 $77,049
$88,319
$0
$25,000
$50,000
$75,000
$100,000
Inbound Outbound Blended
Average Salary by Team Type
Base Salary
OTE16.2%
22
OTE FOR SDRS IN AN ACCOUNT-BASED SALES MODEL IS 10.9% HIGHER THAN FOR THOSE
IN A HIGH-VELOCITY MODEL
Companies who practice an account-based approach pay their reps more than companies
who operate a high-velocity model both on base (12.5% higher) and overall OTE (10.9%
higher).
While account-based SDRs tend to make more money on average, the mix of base and
variable is similar (around a 60/40 split).
$43,680 $38,835
$83,950
$75,669
$0
$25,000
$50,000
$75,000
$100,000
Account-Based High-Velocity
Average Salary by Sales Model
Base Salary
OTE
10.9%
23
WORKING BIGGER DEALS MEAN 4.3% BIGGER PAYCHECKS FOR SDRS ON AVERAGE
This statement may seem obvious in most compensation structures, but it isn’t just saying
that an individual SDR closing bigger deals will earn more commission. On average, if a
company has larger deals, SDR salary—both base and variable—tends to be higher by an
average of 4.3%.
$39,960 $44,549
$80,394 $83,921
$0
$25,000
$50,000
$75,000
$100,000
Small deal sizes Large deal sizes
Average Salary by Deal Type
Base Salary
OTE
4.3%
24
AMOUNT OF CLOSED REVENUE IS BY FAR THE MOST COMMON FACTOR IN DETERMINING
SDR VARIABLE COMPENSATION
In general, it seems that metrics further down the pipeline were more popular for
determining SDR compensation. Close revenue (37.3%) and opportunities accepted
(19.2%) were the most popular metrics. Activities (5.3%) and contacts (2.0%) were the
least common factors used.
There is a big differentiation between appointments being held and appointments being
set. Held appointments were used 96.9% more often than appointments’ being set.
37.3%
19.2%
12.6%9.4% 7.8% 6.4% 5.3%
2.0%
0%
5%
10%
15%
20%
25%
30%
35%
40%
% o
f R
esp
on
den
ts
Variable Compensation Factors
25
44.8% OF COMPANIES REPORTED ONLY USING ONE FACTOR IN THEIR VARIABLE
COMPENSATION FOR SDRS
44.8%
24.2%
8.8%6.2%
0.5% 1.0% 1.0%
13.4%
0%
5%
10%
15%
20%
25%
30%
35%
40%
45%
50%
1 2 3 4 5 6 7 8
% o
f re
spo
nd
en
ts
Number of Factors in Variable Compensation
26
OUTBOUND SDR TEAMS TENDED TO HAVE 55.6% MORE COMPENSATION FACTORS THAN
INBOUND TEAMS
Inbound variable compensation structures tended to be simpler, only employing one to
two factors while outbound and blended teams tended to average closer to three factors.
1.8
2.82.6
0
1
2
3
Inbound Outbound Blended
Number of Variable Compensation Factors by Team Type
55.6%
27
INBOUND TEAMS HAD THE HIGHEST AVERAGE QUOTA ATTAINMENT—16.5% HIGHER THAN
OUTBOUND TEAMS
The overall quota attainment was 63.5% across all SDRs with both outbound and blended
teams close to that average, but inbound teams had a significantly higher attainment rate
(16.5%).
76.4%
65.6%61.8%
0%
10%
20%
30%
40%
50%
60%
70%
80%
Inbound Outbound Blended
Quota Attainment by Team Type
16.5%
28
SDRS WORKING ON LARGER DEAL SIZES HAD A QUOTA ATTAINMENT RATE 4.6% HIGHER
THAN SDRS WHO WORK ON SMALLER DEALS
Whether this is a result of different quota strategies or rep ability is unclear, but larger
deal sizes did tend to be associated with higher quota attainment.
63.3%66.2%
0%
10%
20%
30%
40%
50%
60%
70%
Smaller Deal Sizes Larger Deal Sizes
Quota Attainment by Deal Type
4.6%
29
OUTBOUND SDRS TEND TO HAVE THE LONGEST TIME AT FULL PRODUCTIVITY IN THEIR
POSITION
The overall average tenure for SDRs was 2.8 years with an average ramp time of 4.0
months.
Outbound teams tended to have a slightly longer average tenure (3.0 years) with a slightly
shorter ramp time (3.8 months) than other types of SDR teams, meaning that outbound
SDRs may have a significantly longer time at full productivity in their role than other SDRs.
Inbound teams were the opposite—they had the longest ramp time (6.4 months) and the
shortest average tenure (2.6 years).
2.6 years
3.0 years2.9 years
6.4 months3.8 months 4.0 months
0
1
2
3
Inbound Outbound Blended
Tim
e (Y
ear
s)
SDR Tenure by Team Type
Tenure
Ramp
30
SDRS IN AN ACCOUNT-BASED MODEL HAVE A LONGER TENURE (BY TWO MONTHS) BUT
ALSO A LONGER RAMP TIME (BY TWO MONTHS)
Because the tenure (2.7 years) and ramp time (4.6 months) are both longer for account-
based SDRs than high-velocity SDRs (2.5-year tenure, 2.6-month ramp time), the time at
full productivity ends up being similar for the two sales models.
2.7 years2.5 years
4.6 months2.6 months
0
1
2
3
Account-Based High-Velocity
SDR Tenure by Sales Model
31
PIPELINE
Sales development reps did an average of 93.8 daily activities including an average of 37.2
phone calls (39.7%), 36.2 emails (38.6%), 15.2 voicemail messages (15.2%), and 7.7 social
media touches (8.2%). These activities led to an average of 13.6 meaningful conversations
a day—14.5% conversation rate. These 13.6 conversations per day resulted in an average
of 22.5 appointments set per month—a 5.5% appointment rate. 73.2% of appointments
set become opportunities passed to account executives and the typical sales development
rep had 12.3 opportunities accepted per month--74.8% opportunity acceptance rate. Of
the opportunities accepted, 33.2% closed, which means that the average sales
development rep is responsible for about 12.3 deals per quarter.
From start to finish of the sales pipeline, it’s interesting to note that it takes roughly 458
activities on average to close 1 deal per quarter (assuming 60 work days per quarter). This
is an interesting benchmark for SDRs to see how the potential clients they’re pursuing are
moving through the pipeline.
32
PHONE CALLS ARE THE MOST POPULAR ACTIVITY PERFORMED BY SALES DEVELOPMENT REPS
(37.2 PER DAY)
Using the phone is slightly more popular than using email (37.2 calls per day versus 36.3
emails per day). While email is used by 96.0% of SDRs, it only represents about a third
(37.6%) of SDR’s activities. 63.9% reported using social media for prospecting in their daily
routine, but it only represented 8.0% of daily activities.
Emails36.2
Calls37.2
Voicemails15.2
Social touches7.7
Total Daily Activities
33
OUTBOUND TEAMS DID 61.7% MORE ACTIVITIES PER DAY THAN INBOUND TEAMS ON
AVERAGE
Outbound and blended teams had a similar number of activities per day (94.4 and 91.2
respectively). Inbound teams did much fewer prospecting activities each day. In fact,
outbound teams reported doing 61.7% more activities per day than inbound teams.
59.0
95.491.2
0
20
40
60
80
100
120
Inbound Outbound Blended
Nu
mb
er
of
acti
vit
ies
Total daily activities by Team Type
61.7%
34
SDRS IN A HIGH-VELOCITY SALES MODEL TENDED TO DO 15.5% MORE ACTIVITIES THAN
THOSE IN AN ACCOUNT-BASED MODEL
High-velocity models are models where ‘quantity’ is very important while account-based
models pride themselves on focusing on ‘quality’. It’s not surprising that high-velocity
models produce 15.5% more activities per day than account-based models.
83.1
96.0
0
10
20
30
40
50
60
70
80
90
100
Account-Based High-Velocity
Nu
mb
er
of
acti
vit
ies
Total Daily Activities by Sales Model
15.5%
35
INBOUND SDR TEAMS HAD 98.8% MORE CONVERSATIONS PER DAY ON AVERAGE THAN
OUTBOUND TEAMS
Outbound SDRs teams report doing 61.7% more activities than inbound teams but
inbound teams report having 98.8% more conversations than outbound teams. The higher
amount of time spent having conversations may also explain the lower numbers of overall
activities for inbound teams.
31.4
17.8
13.8
0
5
10
15
20
25
30
35
Inbound Outbound Blended
Nu
mb
er
of
con
vers
atio
ns
Total Daily Conversations by Team Type
98.8%
36
SDRS WORKING SMALLER DEALS TEND TO HAVE 75.8% MORE CONVERSATIONS PER DAY
THAN THOSE WORKING LARGER DEALS
Smaller deals are more transactional in nature and have a shorter sales cycle. SDRs who
focus on smaller deals have 75.8% more conversations per day than those working larger
deals.
16.7
9.5
0
2
4
6
8
10
12
14
16
18
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
con
vers
atio
ns
Total Daily Conversations by Deal Type
75.8%
37
BLENDED TEAMS SET THE HIGHEST NUMBER OF APPOINTMENTS PER MONTH, FOLLOWED
CLOSELY BY INBOUND TEAMS
Blended and inbound teams were able to set a higher number of appointments per month
than outbound teams. For comparison, blended teams set 61.0% more appointments on
average than outbound teams.
23.0
15.4
24.8
0
5
10
15
20
25
30
Inbound Outbound Blended
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Set per Month by Team Type
61.0%
38
SDRS WORKING SMALLER DEALS SIZES TEND TO SET 75.1% MORE APPOINTMENTS PER
MONTH THAN THOSE WORKING LARGER DEALS
As smaller deals tend to be less complex and don’t require as high-level of decision
makers, SDRs are able to set appointments more easily than those who are focused on
larger deals.
29.6
16.9
0
5
10
15
20
25
30
35
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Set per Month by Deal Type
75.1%
39
HIGH-VELOCITY SALES MODELS ALLOWED SDRS TO SET 14.8% MORE APPOINTMENTS
EACH MONTH THAN THOSE WORKING IN AN ACCOUNT-BASED SALES MODEL
As account-based sales tends to target more decision makers per account, appointments
are more difficult to set than for SDRs in a high-velocity model.
27.0
31.0
0
5
10
15
20
25
30
35
Account-Based High-Velocity
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Set per Month by Sales Model
14.8%
40
APPOINTMENTS HELD
19.2
12.9
20.5
0
5
10
15
20
25
Inbound Outbound Blended
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Held per Month by Team Type
%
41
Deal type: T: 23.9, R: 14.3
23.9
14.3
0
5
10
15
20
25
30
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Held per Month by Team Type
%
42
Sales model: AB: 18.6, HV: 26.8
18.6
26.8
0
5
10
15
20
25
30
Account-Based High-Velocity
Nu
mb
er
of
app
oin
tmen
ts
Total Appointments Held per Month by Team Type
%
43
BLENDED TEAMS HAVE THE HIGHEST APPOINTMENT HELD PERCENTAGE (77.9%)
While inbound SDRs were able to do more activities per day and have more
conversations, they had a lower appointment held percentage in comparison with other
teams. Blended teams (77.9%) had a 13.1% higher hold rate than inbound teams (68.9%).
68.9%73.7%
77.9%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Inbound Outbound Blended
Appointment Hold Rate by Team Type
44
SDRS WHO WORK LARGER DEALS HAVE 6.8% HIGHER HOLD RATES THAN SDRS WHO
WORK SMALLER DEALS
The hold rate between SDRs who work small and large deals is minimal. SDRs who focus
on larger deals have hold rates that are 6.8% higher than SDRs who focus on smaller
deals.
76.2%81.4%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Smaller Deal Sizes Larger Deal Sizes
Appointment Hold Rate by Deal Type
6.8%
45
OPPORTUNITIES PASSED
INBOUND AND BLENDED SDR TEAMS PASSED ABOUT 75% MORE OPPORTUNITIES PER
MONTH THAN OUTBOUND SDR TEAMS
Having SDRs performing an inbound motion—whether or not it’s their only focus—tends
to yield more opportunities being passed to AEs.
17.7
10.1
17.5
0
5
10
15
20
Inbound Outbound Blended
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Passed per Month by Team Type
75.2% 73.3%
46
SDRS WHO SELL SMALLER DEALS TEND TO PASS 34.3% MORE OPPORTUNITIES THAN THOSE
WHO SELL LARGER DEALS
Smaller deals tend to move more easily through the pipeline as they’re simpler deals with
shorter sales cycles. This difference in complexity led to a 34.3% difference in number of
opportunities passed per month.
18.8
14.0
0
5
10
15
20
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Passed per Month by Deal Type
34.3%
47
IN HIGH-VELOCITY SALES MODELS, SDRS PASS MORE THAN DOUBLE THE NUMBER OF
OPPORTUNITIES THAN THOSE IN ACCOUNT-BASED SALES
High-velocity SDRs pass 119.0% more opportunities to AEs than account-based SDRs on
average each month.
11.6
25.4
0.0
5.0
10.0
15.0
20.0
25.0
30.0
Account-Based High-Velocity
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Passed per Month by Sales Model
119.0%
48
AES ACCEPT 50.5% MORE OPPORTUNITIES FROM INBOUND TEAMS THAN FROM
OUTBOUND TEAMS
Inbound teams had an average of 50.5% more opportunities accepted by AEs. Blended
teams were in between inbound and outbound teams in their number of opportunities
accepted.
14.3
9.5
12.7
0.0
2.0
4.0
6.0
8.0
10.0
12.0
14.0
16.0
Inbound Outbound Blended
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Accepted per Month by Team Type
50.5%
49
COMPANIES WITH SMALLER DEALS TEND TO HAVE 71.6% MORE OPPORTUNITIES ACCEPTED
BY AES
As deals get larger, there are more moving parts with more decision makers, and it’s easier
for them to fall out of the pipeline at the handoff between SDRs and AEs. SDRs with
smaller deal sizes reported having 16.3 opportunities accepted per month while those
with larger deal sizes reported only having 9.5 accepted each month.
16.3
9.5
0
5
10
15
20
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Accepted per Month by Deal Type
71.6%
50
SDRS WORKING IN A HIGH-VELOCITY MODEL HAD 61.7% MORE OPPORTUNITIES ACCEPTED
THAN THOSE IN AN ACCOUNT-BASED MODEL
SDRs focus on simpler accounts in high-velocity sales models and a higher number of
deals move through the pipeline. 61.7% more opportunities were accepted by AEs in
high-velocity models than in account-based models.
11.5
18.6
0
5
10
15
20
Account-Based High-Velocity
Nu
mb
er
of
op
po
rtu
nit
ies
Total Opportunities Accepted per Month by Deal Type
61.7%
51
BLENDED TEAMS REPORT HAVING 28.6% BETTER OPPORTUNITY ACCEPTED RATES THAN
INBOUND TEAMS
Blended teams had 83.6% of opportunities passed be accepted by account executives
compared with inbound SDRs that averaged only a 65.0% opportunity acceptance rate.
This is 28.6% better acceptance rate for blended teams compared to inbound teams.
65.0%
74.5%
83.6%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Inbound Outbound Blended
Opportunity Acceptance Rate by Team Type
28.6%
52
OPPORTUNITIES WERE 7.3% MORE LIKELY TO BE ACCEPTED FROM SDRS WHEN DEAL SIZES
ARE SMALLER
Deal size had a minimal effect on opportunity acceptance rates. SDRs who work on
smaller deals have a slightly higher acceptance rate than SDRs who worked on larger deals
(7.3%).
84.1%78.4%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
Smaller Deal Sizes Larger Deal Sizes
Opportunity Acceptance Rate by Deal Type
7.3%
53
OPPORTUNITIES SOURCED FROM OUTBOUND TEAMS WERE 91.2% MORE LIKELY TO CLOSE
AS THOSE FROM INBOUND TEAMS
The average close rate overall was 29.3%. Outbound team’s opportunities close 91.2%
higher rate than inbound teams.
17.0%
32.5%
21.5%
0%
5%
10%
15%
20%
25%
30%
35%
Inbound Outbound Blended
Close Rate by Team Type
91.2%
54
HIGH-VELOCITY SALES TEAMS TENDED TO HAVE A 5.1% HIGHER CLOSE RATE THAN THOSE
THAT WERE ACCOUNT-BASED
The close rates weren’t dramatically different by sales model, but it’s interesting to note
that high-velocity sales models yielded a slightly higher close rate (5.1%).
27.4%28.8%
0%
5%
10%
15%
20%
25%
30%
Account-Based High-Velocity
Close Rate by Sales Model
5.1%
55
SALES DEVELOPMENT PROCESS
IDENTIFY
HIGH-VELOCITY SDRS HAD 68.9% MORE ACCOUNTS AT A TIME ON AVERAGE THAN
ACCOUNT-BASED SDRS
Overall, the average number of accounts an SDR works was 74.2. SDRs working in an
account-based system tend to have much fewer accounts at a time (63.5) in comparison
with high-velocity SDRs (107.3).
63.5
107.3
0
20
40
60
80
100
120
Account-Based High-Velocity
Nu
mb
er
of
acco
un
ts
Accounts per SDR by Sales Model
68.9%
56
NEARLY A QUARTER OF ACCOUNTS THAT SDRS WORK (22.8%) HAVE 7 OR MORE
CONTACTS
The average account had 4.0 decision makers1 with a mode of 3 decision makers per
account. Over half of respondents (53.7%) reported working accounts with 3 decision
makers or less.
1 This is a trimmed mean, counting anyone who selected “7 or more” as 7
9.3%
17.9%
26.5%
10.6%12.3%
0.7%
22.8%
0%
5%
10%
15%
20%
25%
30%
1 2 3 4 5 6 7 or more
% o
f re
spo
nd
en
ts
Number of Contacts
Number of Decision Makers Per Account
57
WHEN DEALS ARE LARGER, THE NUMBER OF DECISION MAKERS IS 13.1% HIGHER
While not drastically different, it’s interesting to note that when SDRs are working larger
deals, they tend to need to work with more decision makers than those who work smaller
deals (13.1%).
3.8
4.3
0
1
2
3
4
5
Smaller Deal Sizes Larger Deal Sizes
Nu
mb
er
of
con
tact
s
Contacts per Account by Deal Type
13.1%
58
64.0% OF RESPONDENTS SAW LINKEDIN AS AN EFFECTIVE WAY TO RESEARCH TARGET
COMPANIES
SDRs saw LinkedIn as a research tool more than anything else (64%). Research and direct
communication like InMail were seen as more effective than traditional “social” features
like commenting and sharing posts.
64.0%
50.8%
41.4%
34.3%
19.2%
8.1%
1.0%0%
10%
20%
30%
40%
50%
60%
70%
Research ontarget
companiesand contacts
SendingLinkedInInMail
Sharingrelevant
content withnetwork
Creating andpostingrelevantcontent
Commentingon prospects'
posts
Likingprospects'
social posts
Recording andposting video
% o
f re
spo
nd
en
ts
Most Effective LinkedIn Activities
59
OUTBOUND SDRS SPEND 32.1% MORE TIME ON RESEARCH PER ACCOUNT THAN INBOUND
TEAMS
Researching a company before reaching out is important. Inbound SDRs spend an average
of 4.2 fewer minutes than outbound SDRs researching before calling.
13.1
17.3 16.8
0
2
4
6
8
10
12
14
16
18
20
Inbound Outbound Blended
Tim
e (m
inu
tes)
Account Research Time by Team
60
SDRS WORKING LARGER DEALS SPEND 27.6% MORE TIME PREPARING THAN THOSE
FOCUSED ON SMALLER DEALS.
The larger potential size of the deals justified more SDR time spent doing research, so the
higher research time makes sense.
13.4
17.1
0
2
4
6
8
10
12
14
16
18
Smaller Deal Sizes Larger Deal Sizes
Tim
e (m
inu
tes)
Account Research Time by Deal Type
27.6%
61
A COMPANY’S SALES MODEL MADE THE BIGGEST DIFFERENCE ON ACCOUNT RESEARCH
TIME. ACCOUNT-BASED MODELS SPENT MORE THAN DOUBLE THAN HIGH VELOCITY
As companies with account-based sales models tend to have more decision makers
involved in each deal, more research is warranted. On average SDRs in account-based
models spend 130% more time preparing for a call than high velocity.
18.4
8.0
0
2
4
6
8
10
12
14
16
18
20
Account-Based High-Velocity
Tim
e (m
inu
tes)
Account Research Time by Sales Model
10 minutes,24 seconds
62
CONTACT
THE AVERAGE REPORTED CADENCE OF AN SDR IS 15.4 ATTEMPTS PER CONTACT, AND IS
DOMINATED BY PHONE CALLS AND EMAILS
SDRs reported that, on average, their cadences included 15.4 attempts over an average of
29.3 days, so the average spacing between each attempt was 1.9 days.
On average, SDRs made 4.7 calls, sent 4.6 emails, left 2.9 voicemails, made 1.8 social
touches, sent 0.8 mailers, and 0.7 text messages.
Dials30.3%
Emails29.7%
Voicemails18.7%Social Touches
11.6%
Mailers5.2%
Text Messages4.5%
Breakdown of Cadence Media
63
SDRS ON BLENDED TEAMS WERE THE MOST PERSISTENT IN THEIR CADENCES WITH 15.7
ATTEMPTS
Teams that exclusively worked inbound leads tended to only make 10.7 attempts to
contact each lead (46.7% less).
10.7
14.815.7
0
2
4
6
8
10
12
14
16
18
Inbound Outbound' Blended
Nu
mb
er
of
atte
mp
ts
Average Attempts in Cadence by Team
46.7%
64
SDRS WORKING LARGER DEALS TENDED TO BE 14.9% MORE PERSISTENT IN THEIR SALES
CADENCE THAN THOSE WORKING SMALLER DEALS
Deal size makes a difference in how much effort an SDR is willing to put into contacting a
lead. SDRs with bigger deals tended to make 16.9 attempts while those with smaller deals
only made 14.7 attempts.
14.7
16.9
0
2
4
6
8
10
12
14
16
18
Small Deal Sizes Large Deal Sizes
Nu
mb
er
of
atte
mp
ts
Average Attempts in Cadence by Deal Type
14.9%
65
SDR TEAMS THAT EMPLOY AN ACCOUNT-BASED SALES MODEL MAKE 12.4% MORE
CONTACT ATTEMPTS PER LEAD THAN THOSE WHO USE A HIGH-VELOCITY MODEL.
Account-based SDRs team makes 12.4 more attempts than high-velocity sales teams. This
lines up with the similar trend that larger deals merited more attempts than smaller deals.
The increased number of contacts being targeted in each account in an account-based
sales model makes reaching the right decision makers even more important.
16.3
14.5
0
2
4
6
8
10
12
14
16
18
Account-Based High-Velocity
Nu
mb
er
of
atte
mp
ts
Average Attempts in Cadence by Sales Model
12.4%
66
SDRS TEND TO CONTINUE ATTEMPTING TO REACH A CONTACT 5.4 DAYS LONGER (20.2%)
FOR LARGER DEALS THAN FOR SMALLER DEALS.
While the average cadence duration was 29.3 days, it was a few days longer for larger
deals and a few days shorter for smaller deals. The difference in cadence duration
between larger and smaller deals was 20.2%.
26.7
32.1
0
5
10
15
20
25
30
35
Smaller Deal Sizes Larger Deal Sizes
Du
rati
on
(d
ays)
Cadence Duration by Deal Type
20.2%
67
ACCOUNT-BASED SALES TEAMS TEND TO PURSUE CONTACTS FOR AN AVERAGE OF 10.2
DAYS LONGER (46.6%) THAN HIGH-VELOCITY SALES TEAMS
Along with being more persistent in number of attempts to make contact with potential
clients, account-based sales teams tended to also be more patient and spend 10 days
longer trying to get in contact than high-velocity teams.
32.1
21.9
0
5
10
15
20
25
30
35
Account-Based High-Velocity
Du
rati
on
(d
ays)
Cadence Duration by Sales Model
46.6%
68
QUALIFY
BANT IS THE MOST COMMONLY USED QUALIFICATION MODEL USED BY SDRS, FOLLOWED
CLOSELY BY AN
BANT (Budget, Authority, Need, Timing) is the most traditional qualification model and still
reigns, but ANUM (Authority, Need, Urgency, Money) and its abbreviated form, AN
(Authority, Need) have become popular.
16.1% indicated that they used a qualification model not included in the survey. A
majority were variations of BANT and ANUM such as BANT-PEC (Partner, Environment,
Competition) and ANU. MEDDIC (Metrics, Economic buyer, Decision criteria, Decision
process, Identify pain, Champion) and similar models were also common responses.
BANT29.6%
AN22.7%
No qualification model21.8%
Other qualification model16.1%
ANUM9.8%
Qualification Model
69
SDRS WITH SMALLER DEAL SIZES WERE LESS LIKELY TO HAVE AN ESTABLISHED MODEL FOR
QUALIFYING LEADS
24.1% of SDRs in companies with smaller deal sizes don’t have a qualification model while
only 15.7% of SDRs in companies with larger deal sizes reported not using one. BANT was
the most common model for both large and small companies, but had 36.5% higher
adoption in large companies. Adoption for the other qualification models were roughly the
same between small and large deal sizes.
BANT25.5%
AN23.4%
No qualification model24.1%
Other qualification model17.2%
ANUM9.7%
Smaller Deal Sizes
BANT34.8%
AN22.5%
No qualification model15.7%
Other qualification model16.9%
ANUM10.1%
Larger Deal Sizes
70
PASS
78.3% OF SDRS MEET WITH AES AT LEAST ONCE A WEEK
Nearly 80% of companies (78.3%) of respondents reported that SDRs in their sales
organization meet and coordinate with account executives at least once a week.
17.9%
28.3%
32.1%
6.6% 7.6% 7.6%
0%
5%
10%
15%
20%
25%
30%
35%
Daily 2-3 times a week Once a week Every otherweek
Once a month Never
% o
f re
spo
nd
en
ts
How Often SDRs Meet with AEs
71
COMPANIES WHOSE SDRS MEET WITH AES DAILY HAVE HIGHER APPOINTMENT HOLD
RATES, OPPORTUNITY ACCEPTANCE RATES, AND QUOTA ATTAINMENT THAN THOSE WHO
DON’T MEET AS OFTEN
Naturally, better coordination between SDRs and AEs tended to show higher rates of
appointments holding and opportunities successfully passing. Appointment hold rate for
SDRs and AEs who meet daily is 17.7% higher than for those who only meet once a week.
More importantly, quota attainment is 7.2% higher for those companies with daily
communication between SDRs and AEs.
73.0%
77.9%
72.2%
79.8%82.7%
70.3%
85.9%
92.2%
77.4%
50%
55%
60%
65%
70%
75%
80%
85%
90%
95%
100%
Appointment Hold Rate Opportunity Accept Rate Quota Attainment
Success Rates by Meeting with AEs
Once a week 2-3 times a week Daily
17.7%7.2%
72
ABOUT THE RESEARCH TEAM
KEN KROGUE
Ken Krogue founded InsideSales.com with Dave Elkington in 2004. Ken has been
intimately involved in the research performed by InsideSales.com since the first landmark
speed-to-response study done with Dr. James Oldroyd while at MIT in 2007 and with
Harvard Business Review in 2011. Ken is a prominent thought leader in the inside sales
space and second ranking person nationally in social selling strategies. Ken had been out
of the research role for over a year with health concerns due to an automobile accident,
but prior to that was a weekly columnist for Forbes.com and an international speaker. Ken
attended the United States Naval Academy and holds a Bachelors of Science degree in
Psychology from the University of Utah. Ken has two new books due out.
GABE LARSEN
Gabe joined InsideSales.com with over 15 years of experience in revenue generation,
from helping financial clients price and trade complex derivatives at Goldman Sachs to
helping multinational organizations penetrate new markets at Accenture and Gallup. Gabe
co-hosts the award-winning Playmakers podcast and acts as Vice President of InsideSales
Labs, where his expertise and research have helped more than 200 clients solve their
biggest problems in the sales acceleration space.
BRYAN PARRY
Bryan Parry joined InsideSales in January 2016 as a Research Analyst. In this role, he is
responsible for performing analysis to discover insights related to sales acceleration and
the sales industry in general in order to support InsideSales’s position of innovation. Bryan
graduated with a bachelor of science in statistics from Brigham Young University.