Overall Context

There is a two-fold purpose to the analyses contained herein:

First, we want to understand if there are parts of the market are more performant than others, even if we don’t know why.

Second, we want to understand if there are any particular factors which increase the likelihood of a visit, to help find other places where we should expect a visit. Basically, can we explain why certain parts of the market are more performant.

Data Set Description:

  1. Looking at visits from FY23 forward
  2. The main factors we looked at - Geographic (State), Company Structure (Public/Private), Industry, Revenue, Employees, and DEI Contacts

Takeaways:

Inspect Our Factors

Before we get into anything more complex, we need to understand how our factors are distributed and how the visits are distributed within them.

Starting with the structure of the company.

Visits by Company Structure

  1. Are visits are roughly even between public and private companies.
  2. HOWEVER, the Private market is substantially larger, so our penetration here has been significantly less.
Visits by Company Strucrture
Structure N Visits Percent_Visited
Private 11715 159 1.4%
Public 2507 165 6.6%
Unknown 3 0 0.0%
NA 134 13 9.7%

Visits by Industry

  1. You see some peaks and valleys when we look at the distribution by industry: Manufacturing, Retail, & Hospitals account for 40%+ of visits.
  2. Hospitality and Business Services are particularly low penetration given their market size.
  3. Insurance, Software, and Finance have relatively higher penetration, albeit not the largest markets.
Visits by Industry
Industry N Visits Percent_Visited
Manufacturing 3042 62 2.0%
Business Services 1922 27 1.4%
Retail 1426 42 2.9%
Hospitality 1029 16 1.6%
Finance 672 28 4.2%
Hospitals & Physicians Clinics 662 43 6.5%
Construction 627 9 1.4%
Software 555 18 3.2%
Transportation 510 10 2.0%
Government 458 8 1.7%
Energy, Utilities & Waste 456 12 2.6%
Real Estate 401 6 1.5%
Insurance 367 21 5.7%
Media & Internet 345 10 2.9%
Consumer Services 288 1 0.3%
Holding Companies & Conglomerates 277 5 1.8%
Organizations & Non-Profits 274 8 2.9%
Healthcare Services 238 3 1.3%
Telecommunications 217 2 0.9%
NA 216 0 0.0%
Law Firms & Legal Services 134 4 3.0%
Agriculture 121 0 0.0%
Metals, Minerals, and Mining 82 1 1.2%
Education 40 1 2.5%

Visits By DEI C Level Presence

  1. I think we can definitively say that if there is a C level DEI person at a firm, we have a significantly higher probability of securing a visit.
  2. BUT NOTE, C Level DEIs live in only 5% of your market.
Visits by # of DEI C Level Contacts in SF
DEI_C_Level_Binary N Visits Percent_Visited
0 13589 215 1.6%
1 770 122 15.8%

Looking at DEI Contact Volume in SF

Besides looking at C-Level contacts, we can try to get at commitment / size of DEI at a firm by looking at all of the DEI contacts we have in sF.

In this case:

  1. 2+ DEI contacts at an account is a positive indicator.
  2. Even having 1 DEI contact is much better than having none.
  3. We still get visits at firms without a DEI contact, but our penetration needs to be much better here.
Visits by # of DEI Contacts in SF
DEI_Contacts_Bin N Visits Percent_Visited
0 11643 20 0.2%
1 1401 96 6.9%
2 580 76 13.1%
3 295 48 16.3%
4 165 24 14.5%
5+ 275 73 26.5%

Geographic Considerations

  1. You’d expect industry to be correlated pretty closely with state (e.g. finance & NY), so that might be driving the below.
  2. Still, you’d say NY, CA, TX are producing a lot of visits, but FL - No Bueno.
Visits by State
PrimaryState N Visits Percent_Visited
CA 1843 45 2.4%
TX 1175 27 2.3%
NY 990 52 5.3%
FL 849 3 0.4%
IL 635 12 1.9%
PA 549 16 2.9%
OH 493 13 2.6%
GA 491 9 1.8%
NJ 450 13 2.9%
MA 442 14 3.2%
MI 395 5 1.3%
NC 377 6 1.6%
VA 355 13 3.7%
WA 296 8 2.7%
MN 293 10 3.4%
CO 277 3 1.1%
MO 264 8 3.0%
WI 262 10 3.8%
AZ 255 1 0.4%
MD 249 6 2.4%
TN 246 6 2.4%
IN 226 4 1.8%
CT 186 7 3.8%
SC 147 2 1.4%
UT 146 0 0.0%
DC 138 3 2.2%
OR 124 1 0.8%
KY 119 3 2.5%
KS 112 0 0.0%
AL 105 0 0.0%
IA 101 4 4.0%
NV 100 0 0.0%
LA 94 3 3.2%
OK 94 1 1.1%
NE 87 1 1.1%
AR 68 1 1.5%
DE 60 1 1.7%
ID 52 2 3.8%
NH 50 1 2.0%
MS 39 0 0.0%
RI 38 2 5.3%
ME 30 1 3.3%
HI 27 0 0.0%
NM 25 0 0.0%
SD 23 0 0.0%
ND 21 1 4.8%
PR 21 0 0.0%
WV 20 0 0.0%
MT 19 0 0.0%
AK 17 0 0.0%
VT 17 0 0.0%
WY 14 0 0.0%
New York 7 0 0.0%
California 5 0 0.0%
Texas 5 0 0.0%
Florida 3 0 0.0%
Ohio 3 0 0.0%
Illinois 2 0 0.0%
New Jersey 2 0 0.0%
Puerto Rico 2 0 0.0%
Virginia 2 0 0.0%
0 1 0 0.0%
Connecticut 1 0 0.0%
IO 1 0 0.0%
Iowa 1 0 0.0%
Louisiana 1 0 0.0%
Maryland 1 0 0.0%
Massachusetts 1 0 0.0%
North Carolina 1 0 0.0%
Pennsylvania 1 0 0.0%
Tennessee 1 0 0.0%
Wisconsin 1 0 0.0%
NA 1 0 0.0%

Closer Look at FL - because why not.

The smattering across industries doesn’t suggest an industry driven explanation.

Visits by FL
Industry N Visits Percent_Visited
Business Services 130 0 0.0%
Hospitality 106 1 0.9%
Manufacturing 96 0 0.0%
Retail 81 0 0.0%
Real Estate 45 0 0.0%
Hospitals & Physicians Clinics 43 2 4.7%
Construction 38 0 0.0%
Government 34 0 0.0%
Finance 30 0 0.0%
Insurance 30 0 0.0%
Transportation 30 0 0.0%
Consumer Services 22 0 0.0%
Healthcare Services 22 0 0.0%
Media & Internet 22 0 0.0%
Energy, Utilities & Waste 19 0 0.0%
Software 18 0 0.0%
Telecommunications 16 0 0.0%
NA 16 0 0.0%
Holding Companies & Conglomerates 14 0 0.0%
Organizations & Non-Profits 13 0 0.0%
Law Firms & Legal Services 10 0 0.0%
Agriculture 9 0 0.0%
Education 3 0 0.0%
Metals, Minerals, and Mining 2 0 0.0%

Scatterplots - Looking at Bivariate Relationships

Looking at the relationship between annual revenue and employees, we note a few data trends:

  1. Most of the data lives in the bottom left of the graph - log 5 to log 6 is about 100M to 1Bn, with 100-10000 employees.
  2. Most of the visits appear above a line that says if the ratio of your revenue to employees is below 1 (on a log scale) then we are less likely to get a visit.
  3. Above the line, the visits are relatively scattered…see next plot.

What if we look only at the companies at which we are getting visits. What does that tell us?

  1. It becomes quite apparent that we have a sweet spot: companies with between 1Bn (but really closer to 100Bn) and employees between 10K-30K
  2. We aren’t getting most of our visits in the most densely populated part of the market!

#### Scatterplot- Manufacturing

  1. You can see by the elliptical shape, there is a lot spread across Manufacturing.
  2. The lower left is where we see most of the density.
  3. It looks like the visits are scattered mostly toward the right end of the graph.

### Where do we get manufacturing visits?

  1. 10-30K employees, 3Bn - 10Bn

Boxplots

Looking at the distribution of employees by industry and visit.

  1. What we see across all of the industries is that we tend to get visits at firms with higher number of employees.

Visits by Revenue and Industry

Similar to what we found from the above viz, we are consistently sourcing visits from