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22%
of reps with 1,000+ dials booked 0 meetings
Share of payroll Share of meetings Top 20% Bottom 25% Top 20% Bottom 25% 19% 20% 57% 3.5%
57% vs 3.5%
Same payroll. Very different output.
1.7x 1.3x 17.3x Per dial Per conversation Per meeting
17.3x
gap in cost per meeting between top and bottom reps
48%
of reps average fewer than 2.5 calls per prospect
Group A · 22 reps Group B · 53 reps 256 0 $603K $1.45M Dials Connects Meetings Cost
256 vs 0
meetings booked by 2 groups of reps at the same company over the same 100 days
52 207 Top cohort Bottom cohort unique prospects per meeting
4x
more of the market used up per meeting by the bottom cohort

Half of scored records have no traceable source

Four independent hygiene measures (categories overlap; not a breakdown). Industry-label share measured covered vendors (n=918,911).

List source could not be validated

% of all records (N=1.04M)

0.0%

Job-title label missing or unusable

0.0%

Industry label missing (covered vendors)

0.0%

Needs Attention (derived bad data)

0.0%

Source: TitanX Phone Intent™ scoring data (Titan and Enrich+Titan models), Oct 2025–May 2026. Records as submitted by TitanX customers; labels as supplied in source data. Needs Attention derived as records minus P1+P2+P3.

Tier shares held steady across seven months

Monthly P1 and Needs Attention shares, Nov 2025–May 2026 (Oct ramp-up month: data companion only).

Share of records (%)

P1 High Intent
Needs Attention

Source: TitanX Phone Intent™ scoring data (Titan and Enrich+Titan models), Oct 2025–May 2026. Needs Attention derived as records minus P1+P2+P3. Tier shares are propensity scores assigned at scoring time, not measured connect rates.

Same rep, same list: power dialing connects 2.1x more

10.63%

power / single-line

vs

5.04%

parallel

20% 15% 10% 5% 0% 0% 5% 10% 15% 20% Same rep’s power connect rate Same rep’s parallel connect rate y = x · no difference 96 of 126 reps above the line: better on power 30 reps below: better on parallel

Parallel share

The more you parallel dial, the worse it gets: 81 connects per 1,000 dials at 0% parallel, 46 at 96%+.

Connects Per 1,000 Dials

100

80

60

40

20

0

0%

1-25%

26-50%

51-75%

76-95%

96%+

Reps sorted into 6 groups by the share of their dials placed in parallel. Every group includes reps from 8 to 13 teams.

Reach (21.67% → 11.69%) and meeting rate (1.02% → 0.28%) fall the same way across the groups.

81 dials to book a meeting on power. 2,400 on parallel.

Metric

Power

Parallel

Gap

Connect rate

9.7%

2.0%

4.9x

Connect to meeting

12.8%

2.1%

6.1x

Dials per meeting

↓ lower is better

81

2,400

30x

Same company, same team, same numbers, 12 months.

Results from a single company.

at 61 dials per rep per day at 260 days per year at $100K OTE 649,639 dials 11,000 rep-days 43 rep-years $4.3M payroll

Cost per meeting

Moving off parallel dialing produced the biggest single drop in cost per meeting.

Step

Action

Cost per meeting, from $0

Change

New Value

Cumulative

00

Baseline

—

$9,311

—

01

Remove reps producing zero meetings

-$2,069

$7,242

1.3x

02

Move everyone else off parallel

Biggest single drop

-$4,738

$2,504

3.7x

03

Clean out flagged numbers

-$212

$2,292

4.1x

Modeled on the same dataset, using what it cost these teams on average to book one meeting.

Modeled outcome, not an observed result.

1 in 4 parallel dials were ended before anyone could answer.

1 in 4

≈ 48,000 parallel dials. They still paid for every one of them.