Common First Names by Companies

How to use?

  1. The list of first names is compiled by analyzing more than 50 million social networking profiles.
  2. To use this service, please FIRST click on one of the four buttons below; NEXT, select one company from the menu, and after you click 'submit', you will see the results.
  3. Statistics are reported in % form. For example, 1.43483 means 1.43483%.
  4. Rank is calculated within each company. For example, the most common female name may have a rank = 5, which means it is the 5th common name in that company.
  5. "Gender" column reports how many % of people who use that first name is female.
  6. "Proportion" column reports "the number of profiles with that first name" out of total number of profile in that company.
  7. Due to the nature of some social networking sites, this list has more male name counts.
  8. We only display companies with more than 20000 profiles analyzed and first names appear at least 25 profiles.
  9. Unisex names are defined as first names that are within 20%-80% range (i.e., less than 80% from one gender).

Results are sorted by p-ratio, which means how many times more likely to happen than an average case. For example, Marina has a p-ratio=0.492, implying Marina (in the USA) is 0.492 times more likely to work at IBM than an average person.

All Female Male Unisex Back to Start Page



Share via your favorite social networking service



List of First Names at IBM based on 324 Thousand profiles

  Rank     First Name       P-Ratio Proportion(%) Gender(%) Caucasian(%)   African(%)   Asian(%)   Hispanic(%)
614 Marina 0.49 0.01 99.85 73.33 2.64 12.16 19.41
720 Lucas 0.49 0.01 0.20 71.52 7.34 9.96 13.69
264 Phillip 0.49 0.03 0.44 72.71 13.90 9.58 5.08
498 Ricky 0.49 0.01 0.83 53.63 14.80 22.33 9.01
258 Helen 0.49 0.03 99.70 69.54 10.21 18.65 3.63
728 Dylan 0.49 0.01 2.73 74.31 15.09 5.27 6.05
198 Benjamin 0.49 0.04 0.34 68.62 12.08 15.54 5.43
742 Hank 0.49 0.01 0.00 68.78 20.97 12.97 1.85
239 Brett 0.48 0.03 2.03 86.77 10.26 0.67 2.23
339 Lance 0.48 0.02 0.34 77.97 12.35 5.57 4.27
666 Willie 0.48 0.01 24.61 64.11 31.87 1.59 5.02
790 Clayton 0.48 0.01 0.46 77.67 10.58 8.87 1.56
376 Luke 0.48 0.02 0.21 73.10 10.74 10.79 6.21
113 Pat 0.48 0.07 60.02 82.41 11.12 2.91 3.45
183 Jan 0.48 0.05 71.61 83.95 11.39 0.58 3.94
508 Lucy 0.47 0.01 99.67 48.08 9.04 45.04 5.99
109 Aaron 0.47 0.07 0.76 78.70 11.60 5.43 4.77
393 Curtis 0.47 0.02 0.90 76.48 19.22 1.62 1.96
269 Samuel 0.46 0.03 0.38 58.36 9.06 26.18 9.98
703 Ruben 0.46 0.01 0.60 26.09 4.05 1.68 67.55
686 Karin 0.46 0.01 99.53 87.33 11.44 0.63 1.65
347 Evan 0.46 0.02 1.54 77.62 15.20 5.18 1.94
592 Leonard 0.46 0.01 0.49 57.58 16.97 18.35 8.63
814 Lara 0.46 0.01 99.87 81.86 11.89 0.56 5.03
566 Marianne 0.46 0.01 99.92 89.56 6.87 1.16 1.84
314 Eddie 0.46 0.03 7.00 53.27 15.16 15.69 17.30
246 Maureen 0.46 0.03 99.77 79.89 13.74 2.68 3.93
625 Isaac 0.46 0.01 0.28 61.65 19.01 10.43 13.39
404 Yvonne 0.45 0.02 99.60 56.04 18.03 16.26 12.03
358 Corey 0.45 0.02 4.69 84.52 11.50 1.82 2.39
797 Dina 0.45 0.01 99.75 54.25 5.14 11.99 30.22
197 Jean 0.45 0.04 95.14 75.76 13.70 4.93 5.84
228 Joanne 0.45 0.04 99.76 79.81 10.83 5.43 5.69
541 Eva 0.44 0.01 99.61 43.02 6.26 48.29 3.74
548 Derrick 0.44 0.01 0.71 61.24 20.55 12.84 4.60
402 Seth 0.44 0.02 0.31 86.30 9.71 0.52 3.52
374 Caroline 0.44 0.02 99.85 78.40 11.33 9.29 2.74
123 Jeremy 0.44 0.06 0.54 80.98 12.37 3.38 3.67
770 Ethan 0.44 0.01 0.17 77.22 10.48 12.58 1.41
809 Julio 0.44 0.01 0.72 23.32 1.59 2.13 70.08
384 Grace 0.44 0.02 99.73 44.04 6.79 58.03 4.51
409 Johnny 0.43 0.02 1.18 27.60 7.89 47.64 17.34
483 Irene 0.43 0.02 99.62 62.16 7.72 27.19 5.76
698 Clint 0.43 0.01 0.17 81.13 16.56 0.49 1.44
203 Jose 0.43 0.04 0.75 16.94 2.98 6.30 73.09
451 Tricia 0.43 0.02 99.78 77.50 16.38 2.81 2.44
170 Nicholas 0.43 0.05 0.35 75.06 11.86 10.08 4.30
458 Bradley 0.43 0.02 0.46 73.09 15.30 11.65 4.04
461 Lynne 0.43 0.02 99.27 77.93 10.39 4.71 7.22
457 Nina 0.43 0.02 99.80 75.38 11.55 12.75 5.19
38 Karen 0.43 0.19 99.72 77.88 12.44 6.36 4.26
345 Jeanne 0.43 0.02 99.78 76.98 17.95 6.16 2.79
146 Wendy 0.42 0.06 99.64 69.33 12.08 16.10 3.83
142 Pamela 0.42 0.06 99.77 69.63 19.21 5.21 5.33
196 Suzanne 0.42 0.04 99.78 80.66 10.87 3.94 3.36
734 Adriana 0.42 0.01 99.52 65.96 1.12 3.14 43.14
398 Marcus 0.42 0.02 0.59 65.93 15.46 2.10 16.46
90 Patricia 0.41 0.09 99.69 74.39 13.06 3.21 10.44
153 Jane 0.41 0.05 99.69 66.83 14.76 17.65 2.25
813 Camille 0.41 0.01 97.88 75.81 19.01 1.11 3.31
359 Claudia 0.41 0.02 99.40 48.27 6.19 4.51 40.91
745 Raul 0.41 0.01 0.59 19.03 5.15 1.86 79.36
391 Rodney 0.41 0.02 0.48 71.33 17.28 5.16 4.92
50 Linda 0.41 0.16 99.74 77.77 13.25 7.40 2.64
191 Chad 0.41 0.04 0.43 82.56 14.10 0.50 1.77
799 Cecilia 0.41 0.01 99.80 56.23 8.90 12.04 25.15
58 Ryan 0.40 0.13 2.26 77.56 13.01 4.57 4.94
585 Darrell 0.40 0.01 0.75 77.37 22.24 1.03 1.47
143 Kyle 0.40 0.06 1.77 84.88 11.32 1.57 2.67
193 Paula 0.40 0.04 99.68 84.16 8.72 1.12 5.56
618 Spencer 0.40 0.01 2.65 63.88 15.08 20.10 1.72
630 Carole 0.40 0.01 99.76 79.89 12.77 4.18 1.84
477 Kenny 0.40 0.02 1.00 58.55 10.72 29.96 2.37
710 Vicky 0.40 0.01 99.18 50.04 7.24 41.51 3.69
304 Jimmy 0.40 0.03 0.77 44.61 8.35 36.08 9.67
162 Lynn 0.40 0.05 77.67 80.56 11.99 5.58 2.59
685 Lois 0.39 0.01 99.21 84.24 12.73 0.58 1.75
751 June 0.39 0.01 98.34 55.37 12.64 34.71 3.25
63 Nancy 0.39 0.12 99.71 75.44 12.15 8.54 4.92
299 Shane 0.39 0.03 1.83 78.29 14.77 3.39 2.50
97 Justin 0.39 0.08 0.49 74.42 12.96 10.17 3.14
528 Sheri 0.39 0.01 99.81 69.16 11.72 18.35 1.36
42 Susan 0.39 0.18 99.77 80.55 12.22 4.24 3.43
280 Elaine 0.39 0.03 99.75 64.26 11.07 20.04 5.20
91 Sharon 0.39 0.09 99.57 76.55 14.62 4.15 4.36
711 Esther 0.39 0.01 99.62 34.23 24.02 41.88 5.48
245 Travis 0.38 0.03 0.71 81.22 15.30 2.35 1.85
611 Yolanda 0.38 0.01 99.52 57.50 17.99 0.68 21.90
234 Terri 0.38 0.03 99.38 80.66 15.31 1.61 1.66
134 Robin 0.38 0.06 86.77 78.29 14.14 4.24 2.74
137 Janet 0.38 0.06 99.73 75.07 14.25 5.95 4.43
425 Maggie 0.38 0.02 99.75 60.42 9.44 22.06 9.65
135 Sue 0.38 0.06 99.64 78.10 11.31 7.35 3.32
315 Shirley 0.38 0.03 98.62 63.26 15.05 18.64 3.67
139 Joshua 0.38 0.06 0.41 74.98 14.38 6.34 4.38
354 Patti 0.38 0.02 99.90 77.40 16.15 1.61 4.26
188 Cathy 0.38 0.05 99.80 79.27 11.22 7.29 3.19
184 Diana 0.38 0.05 99.64 69.53 11.62 7.00 12.58
237 Ellen 0.37 0.03 99.73 80.92 11.64 5.70 2.03
324 Marilyn 0.37 0.02 99.71 71.98 24.25 0.53 4.36
All Female Male Unisex Back to Start Page

Related Products at Amazon.com



Related Articles on Parenting-Checkpoint.com

  1. Stop Using a Mobile Phone or Not During Pregnancy: What Research Shows Its Impacts on Children?
  2. Intake of chocolate during pregnancy? Is there any benefit of consumption of chocolate during pregnancy?
  3. Should pregnant women eat more fish or fish oil? What are the real benefits and are there any drawbacks?


What are the features of Parenting Checkpoint?

Under "Parenting Q&A": We cover the questions about parenting skills that are of most concern to parents

Under "Parenting Q&A": We provide quick and research proven answers ONLY

Under "Viral Myths Buster": We bust the Internet myths and rumors

Under "Baby Names": We provide the state-of-the-art data analytics about names



Follow us on your favorite social sites

Parenting-Checkpoint














Disclaimer: Parenting-Checkpoint.com is a participant in the Amazon Services LLC Associates Program, an affiliate advertising program designed to provide a means for sites to earn advertising fees by advertising and linking to Amazon.com.