Top Analyst Tweeters

21Jul10

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Edit (23 July 2010) – updated with extra 150 names – only showing top 1,000

Who are the analysts who use Twitter the most effectively?

In my regular call for analysts to be more competitive with each other in this mock top trumps scenario, it easy to forget that I don’t care who is number 1. What is crucial is:

who are the analysts that important for my topic area?

If semi-conductors or telecoms is your game then talking with Jeremiah Owyang will be interesting but not a good use of time. The way I would use this list is to focus on those analysts that are important by category. Nevertheless kudos must be given to those analysts who have excelled – they have understand that business models are changing, conversations in the online space are moving at a pace and enabling connections that were previously impossible. These analysts understand that if they are not part of the conversation, then the analysts that are influencing (and probably gaining the revenue) are their competitors.

Using SageCircle’s excellent database combined with a good number of my own I have used TweetLevel to understand who are the most important analysts on Twitter.

The majority of the top 500 names are included on this Twitter list.

The tool I have used to compile this league table (also now being used by MTV in their apprentice style reality show) compiles twitter data from over 30 sources and feeds the data through an algorithm to rank an individual according to four weightings:

  1. Popularity (i.e. How many people follow you)
  2. Influence (i.e. What you say is interesting, relevant and many people listen)
  3. Engaged (i.e. You actively participate within your community)
  4. Trusted (i.e. People believe what you say)

Of course, the explanation above is a simplified definition of a complex algorithm(the full methodology of this is shown at the bottom of this post).

 

imageRanking Criteria The primary ranking metric is influence. However, it is interesting to see that when we analyse the same 1,000names by influence we get a completely different top 10 list.

Findings Once again a huge hat tip and pat on the back to Jeremiah Owyang who leads the way by a country mile. Everyone should take note how he uses Twitter to engage with his community and provide real value. For the first time I have now seen a larger number of brands in the top five than individuals.

eMarketer, Forrester, EConsultancy and Altimeter Group all fair extremely well. We should therefore recognise other people who punch well above their weight scoring exceptionally highly even though they are only in smaller firms.

Common complaints Whenever these lists are published, there are several points that always get raised which I will address now…

  1. This twitter account is not from an analyst. The argument as to whom is an analyst or a consultant is becoming largely moot. In my opinion if someone is independent and directly influences technology procurement then they are an analyst – I for one therefore see Vinnie Mirchandani as an analyst (as well as all the enterprise irregulars and Stowe Boyd who mailed me to tell me he is one too).  I know this will cause a huge amount of disagreement but as an outsider looking in this is the way I see the market. This is not to say that some analysts have different strengths over others, it is more a case that I think as an AR pro, I need to monitor the lot of you.
  2. The twitter handle is written by multiple authors. Some twitter accounts have several analysts writing them whereas others do not. The merits of a single twitter account author is something that I personally favour as this allows me to understand the tone of author without having to understand the many personalities that are associated with it. Regardless, for this table, my view has not been to argue this but merely to present the data.
  3. It is irrelevant showing all the tweeters as I am only interested in a specific topic– bingo, that is exactly right. My suggestion to all AR pros is to identify which of your analysts are on this and only look at those. If you would like to understand who is important for a particular micro-topic area, please let me know.
  4. Hey – you have forgotten to include this list. Please let me know the name and if I will include it as an edit.

Top Analyst Tweeters (ranked by Influence on TweetLevel)
These names are included on this Twitter List

    Account Influence Popularity Engagement Trust
1 jowyang 76.6 72.8 54.1 67.6
2 eMarketer 75.3 67.9 45.4 70.7
3 Econsultancy 70.3 65 41.1 63.2
4 Gartenberg 69.4 58.5 68.6 58.5
5 forrester 69.2 69.2 48.4 57.8
6 rwang0 66.8 58 57.5 54.7
7 augieray 65.3 56.3 61.1 51
8 monkchips 65.2 58.2 61 53
9 bfeld 64 61.8 50.7 52
10 Gartner_inc 61.9 66.4 40.3 49.8
11 charleneli 61.2 68.8 55.2 43.9
12 TomRaftery 61 56.4 60.9 44.8
13 VanessaAlvarez1 60.3 50.5 59.2 46.6
14 stoweboyd 60.2 61.2 58.5 41.4
15 mfauscette 59.4 55.9 10.6 47.7
16 bmichelson 59.3 47.9 58.1 45.6
17 hharteveldt 59.2 52.9 55.4 45
18 ekolsky 59.2 49.9 71.7 42.7
19 pgreenbe 59.1 52.7 46.3 43.4
20 dhinchcliffe 59 59.5 47.1 43.3
21 maggiefox 59 58.1 49.5 43.1
22 jesus_hoyos 58.8 55.2 48 44.7
23 Ross 58.7 61.2 40.6 43.5
24 mkrigsman 58.6 56.3 48.5 43.8
25 CurtMonash 58.5 50 60.7 42.6
26 Enderle 58.2 57.7 55.1 42.9
27 mgualtieri 57.6 53 45.6 44.1
28 rossrubin 57.5 48.5 66.3 42.1
29 bobegan 57.5 46.4 66 40.2
30 cote 57.5 52.9 50.5 39.8
31 merv 57.4 49.6 55.8 42.2
32 CRMStrategies 57.4 52.2 54.3 42.5
33 ITSinsider 57.4 55.7 59.7 38.8
34 jameskobielus 56.9 48.6 48.2 41.6
35 DT 56.7 46.7 58.7 44.1
36 cselland 56.7 48 54.7 41.4
37 debs 56.5 56.5 59.7 34.6
38 denschaal 56.3 50.9 48.2 41.8
39 jbernoff 56.2 59.8 50 39.4
40 rshevlin 56.2 44.6 72.5 38
41 dealarchitect 55.9 46 64 40.3
42 wood83 55.2 48.2 60.5 35.7
43 lehawes 55.2 46 56.3 39.2
44 rmogull 55.1 49.2 50 40.3
45 gyehuda 55.1 50.3 51 38.2
46 carterlusher 54.9 49.3 46.9 36.5
47 ccmehil 54.8 46.8 67.3 33.4
48 storageio 54.3 47.2 69.7 33.4
49 InFullBloomUS 54.3 48.4 51.7 39.7
50 SethGrimes 54.2 48.8 60.6 35.7
51 sogrady 54.2 48.9 59.7 35.5
52 jclarey 54.2 52.8 50.1 36.9
53 steven_noble 54.2 47.7 58.3 35.8
54 drnatalie 53.9 57.6 49.1 32.9
55 ZoliErdos 53.9 45.4 62.5 36.9
56 richi 53.6 53.2 56.2 32.2
57 stiennon 53.6 60.9 51.9 30.2
58 PhoCusWright 53.4 52.1 35.3 39.3
59 jeffnolan 53.4 49 44.9 39
60 graemethickins 53.4 51.5 42.7 36
61 stylishidea 53.2 46.9 45.2 38.1
62 dankeldsen 53.1 53.4 54.3 33.3
63 stephenodonnell 52.9 60.1 52.1 33.1
64 sig 52.8 39.2 59.4 45.8
65 blairplez 52.8 44.4 56.6 37.8
66 AndreaDiMaio 52.6 46.3 51.4 42.2
67 skemsley 52.6 48.1 48.1 35.6
68 AndiMann 52.4 47.6 54.4 37.1
69 JEBworks 52.1 48.1 52 34.8
70 ggheorghiu 52 44.3 49.3 34.1
71 tomcummings 51.9 47.9 57.8 30.6
72 SteffWatson 51.5 40.1 55.1 32.2
73 JimLundy 51.2 46.7 49.6 31.6
74 samirb 51.2 47.6 58.1 30.2
75 bkwalker 51.1 48.1 36.9 35.8
76 NeilRaden 51 46.5 67 27.7
77 Wikibon 50.9 50.8 46.4 33.7
78 dbmoore 50.9 46.3 37.9 38.1
79 fscavo 50.8 45.1 52.6 36.2
80 Dana_Gardner 50.8 49.6 7 39.5
81 Jake_Hird 50.4 44.5 36.2 37.3
82 randygiusto 50.4 44.1 51.7 30.9
83 jhammond 50.3 44.1 43.6 37
84 dahowlett 50.2 55.1 52.1 27.5
85 jonathaneunice 50.2 46.2 61.1 28.3
86 SimonBramfitt 49.9 37.5 53.5 39.2
87 jevon 49.7 48.7 58.8 26.9
88 jyarmis 49.7 50.5 53.4 25.7
89 nenshad 49.4 47.4 47.4 28.2
90 Mark_Mulligan 49.4 50.4 48.2 28.7
91 bevelson 49.3 43.4 40.7 38.7
92 juliebhunt 49.3 39.2 53.5 30.1
93 jberkowitz 49.1 50 37.2 30.8
94 rgruia 49.1 46.6 50.6 26.3
95 markmadsen 49.1 44.7 55.7 28.1
96 passion4process 49 44.1 50.4 35
97 biz_mobility 48.9 41.8 48.2 31.5
98 billtrippe 48.9 46.5 49 29.1
99 vendorprisey 48.8 47.4 50.4 26.4
100 stephenmann 48.7 43.5 54.6 27.3
101 Hitwise_UK 48.7 58.2 44.6 27
102 Claudia_Imhoff 48.6 47.9 48.5 25.1
103 dvellante 48.6 45.5 48.6 24.8
104 iglazer 48.5 42.1 47.5 29.9
105 timbo2002 48.4 43.1 48.3 29.7
106 slmader 48.3 45 43.4 31.6
107 cswolf 48.2 46 53 29.2
108 JoshNursing 48.2 39.8 56.1 27.7
109 lcecere 48.2 44.4 39 34.8
110 rbkarel 48.1 41.9 42.4 36.3
111 nate_elliott 48 49.8 46.2 26.7
112 Hitwise_US 48 59.1 37.4 27.9
113 arj 48 44.7 43.6 34.9
114 jonno 47.8 44.2 52.2 23.8
115 KarenYetter 47.5 60.2 11 25.9
116 fiberguy 47.4 41 51.7 26.6
117 tebbo 47.3 42.1 54.5 27.1
118 s_crawford 47.2 43 51.7 26.7
119 idarose 47.2 47.5 52 24.1
120 NigelFenwick 47.2 46.4 49.2 25.4
121 ghaff 47 42.4 50.7 29.4
122 infotrends 46.9 45.3 35.5 34.1
123 andreascon 46.6 46 39.1 36.4
124 jblock 46.5 50.9 40.5 29.9
125 Staten7 46.5 44.3 36.1 31.9
126 MaribelLopez 46.5 45 48.5 25.2
127 nielr1 46.4 39.7 47.1 33.6
128 bitterer 46.4 46.4 42.7 26.8
129 jcorsello 46.4 46.5 37.1 25.1
130 Zak_Kirchner 46.4 38.6 50.1 26.8
131 john_chilmark 46.4 48.5 41.5 25.6
132 visionmobile 46.3 46.4 42.9 36.3
133 btudor 46.3 39.5 51.2 32.8
134 znh 46 46.6 44.4 23.7
135 gilbane 45.9 48.7 39.7 28.6
136 gilbaneboston 45.9 48.5 44.5 31.2
137 mosterman 45.9 41.3 36.6 25.6
138 caostheory 45.8 43.3 0 37.8
139 oliviepaul 45.8 40.8 47.4 22.6
140 lisarowan 45.8 43.4 36.3 30.4
141 stevedupe 45.7 46.4 40.3 28.6
142 christineptran 45.6 42.9 44.3 26.1
143 YankeeGroup 45.6 48.3 28.7 33.4
144 gilliatt 45.6 48.8 49.8 23.5
145 gleganza 45.6 42.5 45.6 27.5
146 kasthomas 45.4 60.1 32.3 26.8
147 JeffreyBreen 45.4 43.4 45.5 25.4
148 paulhamerman 45.4 43.1 31 32.3
149 abnerg 45.4 45.1 49.1 27
150 Dale_Vile 45.3 42.9 52.6 22.7
151 apoorv 45.3 40.3 49.6 26.8
152 vgtero 45.3 42.7 37.1 28.2
153 megheuer 45.2 48.6 44.2 23.3
154 PhilippBohn 45.1 39.9 47.7 31
155 TonyByrne 45 47.2 41.5 26.8
156 CurrentAnalysis 45 44.5 7.3 28.7
157 shawnrog 44.9 44.3 37.9 22.8
158 cwood 44.8 38 46.4 23.5
159 OvumICT 44.8 41.6 39.9 34.6
160 IDC 44.6 56.6 5.5 32.9
161 storageswiss 44.6 44.2 38.1 30.8
162 hyounpark_AG 44.4 41.7 46.6 26.5
163 the451group 44.4 50.2 24.8 33.9
164 erainge 44.4 42.2 39.4 31.2
165 nyuhanna 44.2 52.2 9.9 24
166 pnjarich 44.2 36 45.9 27.5
167 omriduek 44.1 38.8 53.8 24.3
168 johnrrymer 44 47 41.1 23.3
169 neilwd 43.8 41.6 36.7 26.5
170 robinbloor 43.8 52.5 36.5 23
171 clivel_98 43.8 41.9 51.2 23.2
172 pjtec 43.6 39.9 37.8 26.9
173 adriaanbloem 43.5 39.5 51.1 23.4
174 janovum 43.5 39.3 52.9 24.5
175 cmooreforrester 43.5 46.1 36 25.3
176 ironick 43.5 38.5 52.4 21.9
177 ianfogg42 43.4 42.5 36.4 21.9
178 seuj 43.3 32 64.3 20.4
179 cmswatch 43.3 52.3 32.7 26.5
180 stevemann 43.3 46.7 49.9 21.9
181 itworks 43.2 40.8 44.2 22.9
182 kmcpartland 43.2 35.7 34.6 32.7
183 cmendler 43.1 43.8 49 23.4
184 ARC_Advisory 43.1 44.6 30.9 27.6
185 nselby 43.1 45 49.7 21.8
186 Teresacottam 42.9 38.2 48.6 29.9
187 cuttertweets 42.8 44.9 36.6 21.9
188 rreitsma 42.8 42.9 37.4 28.4
189 bryanyeager 42.7 36.7 36.9 26.3
190 dnm54 42.7 37.7 41.2 22.4
191 pfersht 42.6 44.4 39.6 26.2
192 lauriemccabe 42.6 40.7 42 23
193 paulfroberts 42.5 42.1 37 28.7
194 krestivo 42.4 44.9 46.5 21.3
195 Horses4Sources 42.3 41.8 35.2 33.6
196 802dotchris 42.3 42.5 46.2 21.8
197 jgptec 42.2 38.2 32.4 24.5
198 McGeeSmith 42.2 38.4 38.2 28.9
199 etravelproject 42.1 44.7 35.5 24.1
200 maslett 42.1 41.1 41.5 23.2
201 jeffmann 42.1 45.4 37.3 21.4
202 hkisker 42.1 38.8 29.7 31.6
203 glennodonnell 42.1 43 45.6 23.4
204 jalvear 42.1 39.3 48.4 20.2
205 Mark_Goldberg 42.1 38.8 37.6 25.8
206 EliseOlding 42 38.1 36.8 33.2
207 RayLucchesi 42 42.5 54.5 23
208 btemkin 42 46.9 29.5 30.1
209 gcolony 41.9 56.7 31 33.2
210 johnlovett 41.9 47.8 51.3 22.7
211 GigaOMPro 41.8 45.7 31.9 24.7
212 FreeformCentral 41.8 41.1 38 29.7
213 AjitJaokar 41.8 46.1 48.5 21.6
214 Neovise 41.7 38.6 38.2 25.2
215 adamhleach 41.7 38.6 50.3 20.3
216 IDCInsights 41.7 50 30.6 23.8
217 michaelwolf 41.6 41.1 41.9 22.7
218 SarahBurnett 41.6 45.2 45.2 21.3
219 bfinucane 41.4 46.6 51.7 21.4
220 TonyBaer 41.3 41.2 44.6 22.5
221 sliewehr 41.3 38.2 53 21
222 vtri 41.3 43.8 41.7 20.7
223 douglas_quinby 41.2 44.1 42.8 22.7
224 AlanWebber 41.2 46.8 37.2 21.7
225 NickLippis 41 42.9 29.6 21.1
226 smulpuru 40.8 45.9 28.4 24.7
227 shigginski 40.8 35.4 44.2 24.3
228 Gabeuk 40.7 40 43.4 20.7
229 abonde 40.7 37.6 37.5 29.1
230 iSuppli 40.7 46.1 5.5 26.1
231 EricaDriver 40.6 44.3 43.8 20.8
232 darranclem 40.6 39.7 40.7 19.9
233 KeithHumphreys 40.6 41.5 40.3 24.7
234 Thomas_Husson 40.6 44.8 36.6 24.6
235 jhurwitz 40.5 50 35 21.8
236 s_v_g 40.5 38.6 48.2 19.6
237 gwoodill 40.4 49.6 43.3 22
238 pattyinboothbay 40.1 44.8 35.2 20.3
239 atmanes 40.1 44.2 31.4 20.5
240 BurtonGroupIT 40.1 46.6 31.7 21.6
241 allenweiner 40.1 42.1 32.6 19.5
242 jimholincheck 40 44.4 31.3 21.9
243 sureshvittal 39.9 45.9 43.4 22.8
244 jmcquivey 39.9 45 42.6 22.8
245 Montejam 39.7 40.7 44.4 20.1
246 jamet123 39.7 44.7 31.1 20.5
247 timehhh 39.7 41.3 40.5 25.2
248 LinusGreg 39.7 44.9 34.6 20.8
249 GartnerTedF 39.6 37.6 33.9 32.5
250 philww 39.6 44.1 35.1 26.4
251 davidcard 39.4 44.6 39.2 21
252 joeltweet 39.4 53.7 42.4 21.5
253 tjkeitt 39.4 38.5 36 26.3
254 ventanaresearch 39.3 43.8 30.7 20.3
255 keith_rng 39.2 40.7 43.2 19.4
256 BobWarfield 39.2 42.4 41.1 20.4
257 CRozwell 39.1 42.7 33.2 25.1
258 mark_koenig 39 39.4 44.8 19
259 heidishey 38.9 37 44.8 21.4
260 avigreengart 38.9 36.1 30.8 22.7
261 jpmorgenthal 38.8 42.8 41.2 20.3
262 TomGrantForr 38.8 42.7 31 20.1
263 lauraramos 38.8 51.8 33.3 22.6
264 dschatsky 38.8 41.4 32.7 21
265 gilbanesf 38.7 46.5 38 20.4
266 rogermud 38.7 42.5 9.2 19.1
267 ABI_4G 38.6 38.2 5.9 26.9
268 StefanRied 38.6 43.7 31.9 20.4
269 SeanCor 38.6 48.1 45.9 21.5
270 alexkwiatkowski 38.4 37.1 42.3 22.4
271 joestanhope 38.4 40.2 40.6 21
272 erichknipp 38.4 38.5 41.7 19.6
273 punirajah 38.4 35.6 37.5 19
274 rwhiteley0 38.3 40.6 38.6 23.1
275 jjegher 38.3 40.5 43.2 22.9
276 rschmelzer 38.3 39.8 34.8 19.8
277 ravenzachary 38.3 42.9 32.3 19.6
278 imlazar 38.2 40.9 42.8 20.7
279 stessacohen 38.2 41.2 51.3 19.5
280 cee_m_bee 38.2 39.5 36.4 21
281 adamjura 38.2 36.3 46.2 19.6
282 bradholtz 38.2 40.9 34.3 19.6
283 Bersin 38.1 50.9 28.6 22.7
284 rayval 38.1 46.7 35.8 20.3
285 dmavrakis 38.1 36.6 42.3 20.6
286 pragkirk 38 43 41 19.9
287 MattRosoff 38 43 30.4 22.2
288 thinkovation 38 39.7 47.7 19.3
289 siriusdecisions 37.9 46.5 36.4 20.5
290 TheNakedChief 37.9 34.6 36.4 26.2
291 JeffPR 37.8 43.9 32.8 19.3
292 mbrandenburg 37.7 38.5 50.4 19.3
293 NormTravelTech 37.7 42.9 30.3 22.6
294 Jossgillet 37.6 33.5 43.2 18.1
295 brian_riggs 37.5 40.7 38.6 20.9
296 jesstsai 37.4 39.3 33.9 18.3
297 dxmitche 37.4 42.4 32.9 19.2
298 jeunice 37.3 38.7 36 20.2
299 bmirabito 37.2 47.9 33.6 20.1
300 Heuristocrat 37.2 40.1 27.8 18.2
301 smwat 37.2 34.5 38.6 21.7
302 martinatherton 37.1 37.9 42.5 18.3
303 ripcitylyman 37.1 37.8 28.3 22.8
304 sjschuchartCA 37 35.7 53.9 18.8
305 Celent_Research 36.9 43.2 30.3 22.9
306 ChristianKane 36.9 36.3 40.9 19
307 lauwhitehouse 36.9 39.7 40.2 28.5
308 Lciarlone 36.9 41 38.4 18.5
309 bobblakley 36.8 36.2 49.2 19.2
310 peter_w_ryan 36.8 30.1 41.8 23.2
311 bwalder 36.8 36.3 33.5 18.1
312 mikeferguson1 36.8 39.4 35.1 19
313 joltsik 36.7 40.2 27.9 28.3
314 ajbowles 36.6 38.7 38.2 20.4
315 NewsShark 36.6 43.9 8.4 20.6
316 waband 36.4 43.4 36.7 23.5
317 bsdunlap 36.4 38.2 33.8 18.3
318 BarryRabkin 36.3 41.1 42.7 18.5
319 REdwards 36.2 37.9 26.6 20.2
320 alyswoodward 36.2 37.9 48.2 18.4
321 msbrumfield 36.2 39.2 34.1 18.4
322 GaryatWikibon 36.1 39.3 38.4 18.1
323 ekmurphy 35.9 34.3 43.4 17.2
324 nealhannon 35.9 39.5 35.3 18.1
325 Burgess_Gary 35.8 34.9 38.8 19.4
326 mlees 35.8 38.9 38.8 18
327 Hitwise_AP 35.8 50.1 27.8 20.2
328 Gartnergreg 35.8 40.5 35.4 18.8
329 twehmeier 35.7 31.2 52.6 22.1
330 MobileAberdeen 35.7 40.1 36 18.8
331 Chris_Gaun 35.6 43.5 28.7 21.9
332 TKspeaks 35.6 52.9 32.8 21.7
333 Josh_Bersin 35.6 52.3 29.2 20.9
334 spendmatters 35.6 38.6 28.8 21.7
335 LockTD 35.6 37.9 33.4 18.1
336 DenisPombriant 35.6 43.2 30 19.6
337 aschmitt 35.6 36.6 32.6 17.9
338 pund_it 35.5 36.8 36 17.8
339 fjeronimo 35.4 38.9 27.6 20.1
340 theresaregli 35.3 42.5 37.5 18.9
341 minicooper 35.3 44.5 37.9 19.5
342 katehanaghan 35.3 37.6 47.6 17.8
343 dkusnetzky 35.3 40.6 39.9 18.7
344 scottn7 35.2 37.7 30.8 17.6
345 iangjacobs 35.2 40.8 33.8 18.5
346 Frost_Sullivan 35.2 43.1 5.5 19
347 esganalysttmac 35.1 41.8 44.2 18.7
348 Shawn_McCarthy 35.1 39.5 35.7 18
349 nickpatience 35.1 38.9 34.5 20
350 jaysonsaba 35.1 38.6 31.1 21.1
351 billtancer 35.1 39 42.5 21.6
352 jensbutler 35 35.4 34.7 18
353 ca_bshimmin 34.9 41.2 29.6 17.9
354 jim_techclarity 34.9 39.2 35.8 18.3
355 D_Hong 34.9 40.3 33.3 18.2
356 ABINextGen 34.8 31.2 35.2 20.1
357 MarkRaskino 34.8 40.6 29.8 18.6
358 cdhowe 34.8 34.6 29.7 17.9
359 jonathanbrowne 34.7 41.8 35.5 18.2
360 chinamartens451 34.7 34.8 25.8 16.9
361 srepps 34.7 40.4 36 22.7
362 jblin 34.7 36.8 26.2 17
363 JimSinur 34.7 37.5 24.6 31.1
364 mlevitt 34.7 40.1 25.6 17.5
365 weckerson 34.6 42.5 32.6 19
366 PHassey 34.4 34.5 32.7 17.2
367 nengelbert 34.4 40.2 30.8 17.7
368 dfrankland 34.4 43.6 36.8 18.9
369 JulieAsk 34.3 40.3 21.3 19.7
370 nora_freedman 34.3 39.9 46 17.8
371 DortchOnIT 34.2 39 32.3 18.3
372 VLI 34.2 33.6 39.3 17
373 Rick345 34.1 38.1 31.2 17.9
374 kreidy 34.1 40.3 43.1 20.2
375 PikeResearch 34.1 40.3 8.4 24.2
376 toppundit 34.1 40.3 28 18.1
377 Nemertes 33.9 39.4 8.4 18.7
378 ferrusi 33.8 36.9 35.1 17.3
379 vvittore 33.8 34.3 39 17.1
380 rob_bamforth 33.8 35.6 35 17.1
381 edwardsjonat 33.7 35.5 39.8 18.8
382 logisticsviewpt 33.7 40.9 32.6 20.3
383 AgingTech 33.7 44 25.6 20.6
384 mbkmbk 33.6 38.7 26.9 19.1
385 katiesmillie 33.6 37.6 32.4 16.9
386 benwoony 33.6 36.3 25.6 27.3
387 analystnick 33.5 40.3 32.7 17.8
388 infonetics 33.5 44.9 25.4 22.2
389 securityjeff 33.5 35.7 37.2 17.3
390 heyshiv 33.5 33 50.5 17.1
391 CXPOeilExpert 33.4 37.2 7 16.8
392 royillsley 33.4 39.2 29.5 17.4
393 ForresterJobs 33.4 49 32.8 19.5
394 bojan_simic 33.4 37.2 34.7 20.1
395 prashanthrai 33.3 33.8 29.2 16.2
396 lauradidio 33.3 36.7 23.3 17.5
397 chris_townsend_ 33.2 40.4 44 18.3
398 stor2 33.2 39 30.5 17.1
399 billnagel 33.2 33.5 34.1 16.6
400 nigelwallis 33.1 33.3 34.3 16.1
401 cloudpundit 33.1 37.8 30.6 19.2
402 demartek 33.1 40.4 31.8 17.6
403 TECtweets 33 37.7 26.5 16.9
404 brucemr 33 33.5 29.6 16.3
405 npdgroup 33 49.4 4.4 20.4
406 jtsd 33 30.3 30.9 17
407 nickster2407 32.9 37.4 34.2 17.1
408 rnantel 32.9 38.4 7 17
409 jboye 32.9 39.7 30.7 19.9
410 Eval_Source 32.8 35.9 32.5 17.1
411 EquaTerra 32.8 40.9 6.6 20.7
412 passingnotes 32.8 37 36.7 16.5
413 KSterneckert 32.8 39.8 32.9 17
414 ema_research 32.7 43.5 7.3 17.9
415 suds 32.7 36.8 33 16.2
416 azornes 32.6 38.5 4.8 17.3
417 carldoty 32.6 38.1 30.3 17.1
418 jcapachin 32.6 38.3 30.4 17.2
419 howett 32.6 31.6 45.5 16.1
420 darrenbibby 32.6 38.6 25.2 17
421 AMR_Research 32.5 51.2 26 19.5
422 TGView 32.4 36.7 27.3 16.9
423 epopova 32.4 35.9 29.5 16.4
424 e2theb 32.4 29.4 36 16.6
425 Senformation 32.4 37.4 36.2 16.8
426 jarrodgingras 32.3 41.8 35.6 17.5
427 mtauschek 32.3 33.4 36.3 16.4
428 wif 32.3 35.6 29.3 24.2
429 fgilbane 32.3 39.9 35.7 17.4
430 matteastwood 32.2 37.4 26.3 17.4
431 euroLAN 32.1 37.2 31 16.3
432 stavvmc 32.1 31.9 37.4 16
433 Telesperience 32.1 36 27.6 17.1
434 ePubDr 32.1 33.7 27.5 16.4
435 Payment_Expert 32.1 46.4 27.6 18.2
436 mizkonary 32 35.6 31.4 18
437 EveGr 31.9 35.1 26.9 16.2
438 infotrends_mps 31.8 37.3 33 16.5
439 FillMurphy 31.8 34.2 24 19.4
440 IDCBrasil 31.6 41.3 2.9 19.6
441 Craw 31.6 40.4 30.1 19.4
442 gregbuzek 31.5 33.4 27.4 15.6
443 zkerravala 31.5 38.6 23.1 16.9
444 PaulBrown_SA 31.4 34.4 31.4 15.7
445 SA_Update 31.3 40.5 3.3 17.6
446 chenxiwang 31.3 31.1 28.9 21
447 pmcginnis 31.3 38.2 8.4 15.6
448 reastman 31.2 35.6 29.2 15.7
449 PJHines 31.2 39.6 27.4 16.8
450 diteb 31.2 38.6 37.6 16.4
451 tim_walters 31.2 39.1 30.6 18.5
452 mHingley 31.1 36.7 6.6 17.7
453 NPDFrazier 31 42 34.9 18.1
454 CompassIntel 31 38.2 25.2 16.4
455 jfrey80 31 38.8 26.4 18.7
456 Andrew_Boyd 30.9 42.2 34.1 16.9
457 RachelDines 30.9 39.4 34.6 18.7
458 EverestGroup 30.9 39.3 23.9 16.6
459 AndyBrownSA 30.8 30.5 38.2 15.1
460 tamarabarber 30.8 38.6 36.5 17.4
461 100Gigabit 30.8 41.6 26.7 16.7
462 InterpretLLC 30.8 30.1 29.3 19.6
463 mobilesimmo 30.8 35.5 26.8 16.1
464 markhrobinson 30.7 38.5 24.5 16.1
465 acfrank 30.6 37.9 26.3 15.8
466 Aberdeen_CMTG 30.6 46.6 27.6 17.8
467 mgrey 30.5 36.5 21.5 16.2
468 jctec 30.5 32.1 30.4 16.6
469 DaveMario 30.4 37.5 34.6 16.7
470 kevinnolanuk 30.4 39.4 27.5 17.8
471 carriejohnson 30.3 37.4 35.2 16.8
472 idccanada 30.3 43.4 8.4 16.9
473 rstormonth 30.1 32.7 25.3 17
474 leedoyleidc 30 37.6 19.5 19.5
475 jmp_katz 30 38.2 35.5 16.7
476 dlevitas 29.9 36.7 28.7 15.9
477 benwood 29.9 42.4 25.2 17.3
478 dconnor 29.8 38.6 33.4 16.4
479 hokun 29.8 36.1 37 16
480 drjimmys 29.7 33 7.7 14.3
481 Nathan_Safran 29.6 33.2 36.1 15.3
482 instantBP 29.6 35.1 27 15.3
483 markpmcdonald 29.6 38.1 4.8 16.3
484 daniel_krauss 29.5 30.9 25.4 15.2
485 paulzagaeski 29.4 23.8 33.9 20
486 mbarbagallo 29.4 36.5 28.3 18.8
487 TechMarketView 29.4 34.4 5.9 15.1
488 andreasantonop 29.3 37.5 40 15.9
489 melanieturek 29.3 36.4 33.1 16.1
490 bseitz 29.3 28.7 39 14.4
491 IDC_EMEA 29.2 31.3 54.4 17
492 stephatkins 29.2 32.1 27.2 16.1
493 markbowker 29.1 39.1 24.7 16.3
494 PeteCunningham 29.1 36.7 37.6 16.3
495 juniperresearch 29 38.6 24.2 16.4
496 dougwashburn 29 38.5 32 18.2
497 thickernell 29 34.9 24.3 15.5
498 MattyHatton 29 37.2 35.5 15.9
499 paulbudde 29 34.7 20.8 15.6
500 Kindervag 28.9 33.6 41.5 15.9
501 fgens 28.9 41.6 26.6 16.9
502 dreeves1 28.8 31.6 30.2 15.4
503 zmcgeary 28.8 38.7 46.7 15.7
504 jamystewart 28.7 40 27.2 16.4
505 Madtarquin 28.7 37.6 37.2 15.6
506 strothkamp 28.7 36.8 26.7 16.4
507 wjmalik 28.6 32.9 36.4 15.3
508 AnalysysMason 28.6 33.7 21.9 21.8
509 mgerush 28.6 37.6 28.3 17.4
510 jaranderson 28.6 29.3 35.6 16.6
511 poneillforr 28.5 30.8 24 16.5
512 mgilpin 28.5 38.1 31.1 16.4
513 G_ant 28.5 33.8 35.7 15.4
514 red_gillen 28.5 30.7 24.3 19.6
515 michaelgreene 28.5 37.9 28.9 16.3
516 lisabradner 28.5 41.3 27.2 16.4
517 NinaLytton 28.4 30.3 30.9 15.6
518 nsturgill 28.3 33.1 22.7 16.2
519 Lluis_Altes 28.3 32.3 5.9 14.3
520 dpotterton 28.2 34.1 5.1 16.4
521 KeithKTsang 28.2 34.5 34.6 14.9
522 ChrisOber 28.2 34.4 27.6 15.1
523 nikkibaird 28.1 36.1 23.4 15.6
524 JoshSMartin 28 27 28.7 13.4
525 brightfly 28 36.5 5.5 14.9
526 Canalys 28 38.2 5.1 15.5
527 annenielsen 28 35.8 26.4 14.6
528 srog 27.9 37.6 36.4 15.7
529 adriandrury 27.9 31.7 26.4 14.4
530 DarylPlummer 27.9 41.4 32 17.3
531 RogerKay 27.9 38.3 26.1 16
532 elizabethstark 27.9 35.1 30.6 15.3
533 CurlyGuyBry 27.9 30.7 36.1 15.5
534 richwatson 27.9 38.7 29.7 16
535 dtwing 27.9 34.5 30.3 14.9
536 lightplay 27.8 31.4 33.3 14.7
537 debswee 27.8 32.3 31.4 14.7
538 MKRasmussen 27.8 40.9 5.1 16.4
539 chrischute 27.8 32.3 26.6 14.6
540 msmvnj 27.8 36.4 26.8 15.4
541 algillen 27.8 36.1 28.9 15.7
542 ghalimi 27.8 36.3 0 15.9
543 Frost_Events 27.7 36.4 24.3 14.7
544 anshublog 27.7 32.7 33.2 14.6
545 naveenhegde1 27.7 30.4 23.1 13.9
546 jamiemlewis 27.6 37.6 33.4 15.7
547 galvar60 27.6 36 4.8 15.1
548 rkoplowitz 27.6 39.6 27.4 16.4
549 gcreese 27.6 37.7 19.3 16
550 rsilvalondon 27.5 30.7 2.9 15.8
551 TheTowerGroup 27.5 36.3 22.9 15.8
552 LFrankKenney 27.5 34.1 34.5 15
553 susankevorkian 27.4 35.1 22.7 14.4
554 instat 27.4 40.5 5.1 16.2
555 CushingAnderson 27.3 37.7 32.5 15.4
556 geoffblaber 27.3 37.8 34.2 15.8
557 MWDAdvisors 27.3 34.7 25.5 16.4
558 rwildeman 27.2 36.9 21.8 15.4
559 smcleish 27.2 37.5 27.4 15.7
560 kimknickle 27.2 32.7 26.6 14.4
561 DougWilliamsMHD 27.2 31.8 31.9 14.7
562 jgownder 27.2 34.3 27.6 15
563 jonathansteel 27.2 37.2 28.7 15.3
564 zapthink 27.2 32.2 17.7 15.1
565 ChristineChang 27.2 37.2 19.9 18.4
566 diane_clarkson 27.1 40.2 23.6 16.1
567 BenBajarin 27.1 26.9 27.5 13.2
568 P_Wannemacher 27.1 30.3 29.4 15.5
569 treerao 27 31.3 41.5 14.7
570 wfz 26.9 32 6.2 13.7
571 JonCrotty 26.9 32.7 8.4 13.5
572 Richard_Fouts 26.8 35.9 24 14.9
573 itstorage 26.8 37.5 32.2 15.4
574 pyramidresearch 26.8 39.6 5.9 15.7
575 TedSchadler 26.7 42.6 21.9 17.1
576 sebastiancoss 26.7 33.7 22.3 17.6
577 jimlmurph 26.7 40 23.1 15.7
578 IDCPortugal 26.7 27.8 21.6 13.7
579 davidmsmith 26.7 38.6 27 15.7
580 RichBohn 26.6 40.7 9.2 14.6
581 IDCLatin 26.6 36.9 5.5 15
582 HW_Support 26.5 33.1 25.8 14.7
583 bgassman 26.5 39.8 27.8 16.1
584 ITAnalysis 26.5 28.9 23.8 13.3
585 jbozman 26.5 34.4 5.5 14.5
586 domdupuis 26.5 28.1 26.8 13.4
587 emilynaglegreen 26.4 37.1 25.7 17.3
588 jonarber 26.4 27.2 38.5 13.5
589 CCSInsight 26.3 38.7 23.3 15.5
590 SaaSpro 26.2 37.8 22.3 15.4
591 IDEASCP 26.2 26.3 17.1 15
592 barryparr 26.2 38.7 27.1 15.5
593 DortchAtFocus 26.2 28.4 31.1 13.3
594 tombitt 26.1 40.6 33.5 16.4
595 ABIresearch 26.1 39.4 2.9 16
596 davecapp 26.1 34.1 24.3 14.5
597 wmcneill 26.1 36.5 22.9 14.6
598 JoeGalvin 26 36.7 24.1 14.9
599 jenbelissent 26 37.5 26.4 15.3
600 versace57 26 28.9 30.2 13.3
601 wkernochan 26 28.6 50.1 13.9
602 tcorbo 26 35.7 24.7 14.6
603 creativestrat 26 29.9 16.5 15.5
604 scottsantucci 26 36.4 22.5 14.9
605 tarzey 26 34.9 41.7 14.5
606 jeffheynen 25.9 35.1 26.9 14.6
607 cborovick 25.9 36.6 23.4 14.7
608 adelesage 25.8 35.8 26.6 15.1
609 Informatm 25.8 35.7 19.2 15.1
610 MWardley 25.7 33.3 24.1 14.4
611 ericdomage 25.7 30.2 23.7 13.8
612 angie_p 25.7 33.2 31.8 14.1
613 paula_rosenblum 25.7 33.4 40.9 14.5
614 whita 25.7 34.6 33.9 14.6
615 ABI_MobileNW 25.7 33 21.4 14.6
616 bpmfocus 25.7 38.4 23.8 15.6
617 vernonxt 25.5 35.9 18.8 14.8
618 mdecastro 25.4 34.7 25.2 14.2
619 jeffkagan 25.4 41.2 26.6 14.7
620 LizBoehm 25.4 32.3 25.8 14.3
621 aaronmcpherson 25.4 34.4 26.9 14.3
622 danbarlev 25.3 29.1 27.5 12.7
623 TheEbizWizard 25.3 33.9 28.5 14.1
624 gphifer 25.3 38.7 4.8 14.9
625 tracresearch 25.3 33.1 28.2 13.7
626 gcoimbra 25.2 29.7 27.3 13.1
627 lcannell 25.2 32.7 27.9 13.8
628 christinaylee 25.2 31 35.5 13.6
629 SW_Support 25.2 32.3 25.6 13.8
630 duncanwjones 25.2 28.5 27.6 15.1
631 pete_lacey 25.2 29 25.9 13
632 AiteGroup 25.2 35.9 27.2 14.7
633 acschmidt 25.2 32 24.1 13.7
634 SaaSEurope 25.1 34.3 24.6 14.5
635 marylaplante 25.1 31.6 4.4 14.1
636 jamesbrehm 25.1 34.6 20.9 14.1
637 tobybell 25.1 36.6 45.5 14.7
638 dianemyers 25.1 34.4 24.1 14.1
639 NancyJami 25 32.8 23.9 13.5
640 clayryder 25 25.5 18.4 12.4
641 miravperry 25 34.5 28.1 14
642 Aberdeen_HCM 24.9 40.1 21 15.2
643 WiseGreyOwl 24.9 34.2 28.1 14.3
644 shauncollins 24.9 35.7 22.3 14
645 tjennings 24.8 36.2 33.5 14.6
646 karenmassey 24.8 35 28.3 14.2
647 DouglasHayward 24.8 31.4 21.3 13.2
648 bswtelecom 24.8 35.8 21.1 14.3
649 RJWitty4Gartner 24.8 34 22.3 14.2
650 DavidJWest 24.7 37.3 5.1 14.6
651 Bajarin 24.7 34.9 3.7 14.3
652 pallega 24.7 30.5 28.5 13.8
653 coverby 24.6 34.4 32.6 14.3
654 sbalaouras 24.6 40.2 21.5 15.4
655 prussom 24.5 35.6 21.4 14.9
656 Tiffani_Bova 24.5 36.5 21 14.6
657 alexcullen 24.5 38.4 19.5 15.3
658 ShivBakhshi 24.5 36.3 2.6 14.5
659 josiesephton 24.4 32.4 25.9 13.4
660 skingstone 24.4 35.1 29.1 14.6
661 DaveBoulanger 24.4 40.5 28 14.2
662 cchristiansen 24.3 35.6 5.9 13.8
663 rdkugelvr 24.3 31.4 22.6 13.1
664 tonyiams 24.3 32.7 22.7 13.5
665 ltabb 24.3 37 15.9 14.9
666 marksdriver 24.3 35.3 3.7 14
667 emmaking_escp 24.3 34.4 31.9 13.8
668 melindaballou 24.3 31.1 23.1 13.4
669 DanVesset 24.2 33.5 22.7 14
670 simonrob451 24.2 31.5 27.2 13.6
671 MaryJTurner 24.2 33.8 23.9 13.8
672 rambadri 24.1 29 32.7 13
673 tim_shepherd 24.1 37.2 16.3 14.4
674 fjhr 24.1 34.1 3.7 13.8
675 bobbymuhlhausen 24.1 32.3 29 13.3
676 EinatShimoni 24.1 32.8 26.5 13.3
677 julie_craig 24 31.6 18.5 13.8
678 cjones1405 24 35.1 18 14
679 VicGart 24 32.7 21.7 13.6
680 bolarotibi 23.9 30.8 27.4 12.9
681 komarah 23.9 38.5 19 14.7
682 danolds 23.9 30.3 18.5 12.9
683 LaurenEcks 23.9 29.8 24.9 12.5
684 ChrisFletcher 23.9 36.5 21.2 14.1
685 BLheureux 23.9 30.4 27.6 14.8
686 wzhou 23.8 31.2 23.5 12.9
687 DellOroGroup 23.8 42 19.4 15.8
688 iTGuru 23.8 36.7 2.9 16.2
689 dlogiudice 23.8 30.7 22.2 12.9
690 TPI_News 23.8 36.2 22.6 14.3
691 StephenB_TG 23.7 30.2 22.6 13.1
692 SimonYates 23.7 36.4 25.3 14.6
693 PierManenti 23.7 29.8 23.5 12.6
694 pdebeasi 23.7 36.2 19 14.1
695 drchrisholmes 23.6 25.1 18.8 13.6
696 Bloor_Research 23.6 34.1 0 14.3
697 atwalls 23.6 26.6 25.3 12
698 DavidMercer_SA 23.5 31.4 19 13.1
699 MiriamKutcher 23.5 34.6 26.2 13.7
700 JackieFenn 23.4 37.9 2.9 14.5
701 Stuart_Robinson 23.4 28.8 21.6 13.9
702 hwdewing 23.4 30.5 22.1 13
703 DaveEckert 23.4 34.6 24.5 13.8
704 IDCconferences 23.4 29.4 18.9 12.7
705 Quocirca 23.3 33.3 20.7 13.8
706 lesliehand 23.3 32 22.7 13.2
707 Experton 23.3 33.8 6.6 13.1
708 lizherbert 23.3 39.9 17.4 15.1
709 jackzimmerman 23.2 32.7 19.1 13
710 Whiterope 23.2 28.9 18.1 12.4
711 monkchipsconf 23.2 29.1 24.9 12.5
712 ramonkrikken 23.2 25.9 38.2 12.4
713 dfloyer 23.1 31.5 4 12.9
714 KimballBrown 23.1 32.6 31 12.9
715 s2_williams 23 27.2 19.1 11.8
716 chrismines 23 34.6 39.5 14.1
717 zStorageAnalyst 23 30.2 31.2 13.3
718 illuminata_inc 23 33.7 23.3 14.2
719 Display_Market 23 29.6 21.3 12.6
720 tpohlmann 22.9 33.6 27.3 13.6
721 Staggmacey 22.9 34.2 20.4 13.6
722 dsholler 22.9 21.2 19.1 10.8
723 chrisandrews50 22.9 29.6 28.2 13.2
724 SeanPODowd 22.9 32.3 21.4 13
725 Joshkrischer 22.9 29.6 28.2 12.6
726 m2mcguire 22.7 36 16.6 13.7
727 gerrybrown 22.7 35 15.1 13.5
728 RadicatiGroup 22.7 29.3 25 13
729 140letters1idea 22.6 28.4 23.6 11.9
730 gdschreck 22.5 37.5 42.4 14.8
731 Candefero 22.5 31.9 16.4 12.2
732 OvumButlerBI 22.5 36 2.2 14
733 wstofega 22.4 33.3 4 13
734 tomaustin 22.4 34.1 24.4 13.6
735 jneeson 22.4 33.9 7 12.4
736 IDCevents 22.3 35.3 30.4 13.7
737 allymotz 22.3 30.3 5.5 12.1
738 Nimblepm 22.3 27.2 4 11.9
739 nariv 22.3 28.5 18.7 12
740 fab_biscotti 22.2 39.2 26.5 14.9
741 BradleyAnthonyJ 22.1 36.3 2.6 13.9
742 tolvet 22.1 29.3 18.8 12.1
743 informatm_pr 22 27.6 23.4 11.6
744 dkerrsa 22 28.8 20.6 12.3
745 ElainebColeman 22 27.1 20.6 11.3
746 408wij 21.9 26.1 19.9 11.1
747 RobertEParker 21.9 30.3 18.9 12.2
748 DHSchoolar 21.9 22.7 27.3 10.7
749 robhelm 21.9 34.1 18.1 13
750 BI_Hatch 21.9 32.8 20.2 12.6
751 habeel 21.9 26.6 28.9 11.2
752 mark_diodati 21.8 31.5 4.4 12.9
753 SeanRyanAnalyst 21.8 29.9 5.5 11.9
754 danagould 21.8 33.5 26.9 13
755 ynatis 21.7 34.8 21.6 13.7
756 vbaker 21.7 35.4 4 13.3
757 meredithwhalen 21.7 32.7 5.5 17.3
758 PNARICH 21.7 30.4 20.9 12.3
759 jones_rd 21.7 25.9 19 11.9
760 Jezzagreen 21.6 30 4 12.1
761 SEB4IDC 21.6 31 20.9 12.7
762 c_egge 21.6 28.5 29.4 12
763 pinicohen 21.6 29.1 17.6 12.1
764 ChrisLRichmond 21.5 23.5 27.9 12.2
765 fpignatti 21.4 27.1 20.7 11.3
766 jscaramella 21.3 32.1 19.8 12.9
767 smbresearch 21.3 25.2 20.2 10.7
768 the_big_pic 21.3 33.6 20.1 12.9
769 amywohl 21.3 35.7 15.1 13.4
770 peterostrow 21.3 39.4 19.8 14.2
771 iriches 21.3 27.4 21.9 11.4
772 benpiper_sa 21.2 25 20.6 10.8
773 dharringto 21.1 30.4 4.4 11.9
774 rodnelsestuen 21 28.2 20.3 11.7
775 richardwinter 21 34.3 8.4 12.1
776 ABI_Devices 20.9 33.3 4 13
777 ABI_MobConsumer 20.9 29.3 20.2 12
778 Steve_Cramoysan 20.9 31.1 33 12.6
779 richvancil 20.8 29.9 17.7 12
780 logicalleap 20.8 28.1 28.2 12.2
781 jarekknapik 20.8 27 19.1 11.1
782 ABI_MobileMoney 20.8 27.7 18.7 11.7
783 vokeinc 20.7 28.1 5.5 11.3
784 orrtechnology 20.7 26 0 11.4
785 georgetubin 20.7 26.2 19.8 10.9
786 AlexandraKim 20.7 37.2 5.5 13
787 richardawebb 20.6 29.5 16.2 13.4
788 DennisGaughan 20.6 35.1 19.6 13
789 plburris 20.5 38.5 11.5 14.2
790 TekStrategist 20.5 30.3 15.1 11.8
791 chrisvoce 20.5 34.5 22.9 13.2
792 sgrant1974 20.4 29.6 18 11.6
793 mcnabb_kyle 20.4 35.1 29.7 13.6
794 alaasaayed 20.3 27.9 18.1 10.6
795 peterschay 20.3 27.1 20.1 11
796 maureencfleming 20.2 31.2 54.3 13
797 DaveReinsel 20.2 34.5 18.5 12.7
798 KenPresti 20.2 31.5 21.9 12
799 CXP 20.2 32.2 6.6 11.7
800 galitfein 20.1 28.6 2.9 11.3
801 SamDriver 19.9 31.4 19.9 12.3
802 RCMcDowall 19.9 23.1 12 10.3
803 andrew_dun 19.9 29.8 18.1 11.6
804 AlexPForrester 19.9 28.1 21.8 11.3
805 steve_pr 19.8 34.2 3.7 12.5
806 scottpezza 19.8 30.4 23.5 11.8
807 ian_wesley 19.7 24.4 59.6 11.4
808 Chris451mobile 19.7 30.9 23.5 12
809 AnalyzeIT_ 19.6 27.7 21.6 11.1
810 mbcxp 19.6 29.6 19.5 12
811 LSileo 19.6 29.9 23.3 11.5
812 richpartridge 19.5 28.6 19.3 11.4
813 ABI_LBS 19.5 25 17.3 10.4
814 fhalper 19.5 34.2 5.5 12.2
815 susanealdrich 19.5 26.3 31.2 11
816 IDCAP 19.4 34.6 16.7 13
817 CSLeClair 19.2 29.3 3.7 11.4
818 Cliff_Condon 19.2 25.5 57.6 11.9
819 InventoryTrack 19.2 29.2 15.1 11.3
820 ForresterTel 19.1 25.1 25.4 10.4
821 KHarrisFerrante 19.1 28.1 15.7 11.2
822 ekirchheimer 19.1 34 62.7 13.4
823 bholmes3 18.9 33.6 18.1 12.7
824 Bala_Ganesh 18.9 34.3 21.1 12.5
825 ddaoud 18.8 31.6 4.8 11.5
826 jonathangaw 18.8 30.7 20.8 11.6
827 dangeiger 18.8 27.7 17.5 10.6
828 Dansommer 18.8 31.3 40.3 12.3
829 abicarlaw 18.7 37 2.9 12.9
830 jnoelatpna 18.6 29 14.9 11.5
831 robertmcneill 18.6 28.5 16 10.6
832 delotto4gartner 18.6 30.7 14.2 12
833 brian__burke 18.5 32.8 19.7 12.2
834 hchaight 18.4 37.4 13.7 13.7
835 timcoulling 18.4 34.6 12.6 12.3
836 rwa_ca 18.4 34.7 4 12
837 jw_harris 18.4 24 18.7 10
838 ABI_DigitalHome 18.3 30.4 19.8 11.8
839 btulsiani 18.3 33.4 14.3 12
840 Schoolcw 18.3 27.7 3.3 10.7
841 ABI_M2M 18.3 29.3 14.9 11.4
842 nbelanger 18.3 32.9 22.3 11.7
843 AlastairE 18.2 34 16.5 11.9
844 dmolony 18.1 22.7 16.7 9.8
845 PhoneResearchMK 18.1 24.3 20.6 9.8
846 richardmahony 18.1 27.3 20.7 10.8
847 PamelaCDInforma 18 27 18.8 10.6
848 itinsurancegeek 18 26.6 17.6 10.9
849 bburke25 17.9 28.3 21.1 10.7
850 jonpaisner 17.9 29.2 19.1 10.9
851 susanfeldman 17.9 35.3 13.7 12.6
852 kathywilhide 17.9 34.7 16.3 12
853 rstrohmenger 17.8 24.2 26.4 10.4
854 dcearley 17.8 33.9 4 11.8
855 NERSKINE 17.8 33.4 21.6 11.9
856 paolopescatore 17.7 35.8 17.5 12.6
857 susananalyst 17.7 26.1 6.6 9.8
858 BeanBoston 17.7 37.1 5.5 12
859 mjball 17.6 34.3 4.4 11.6
860 tfoydel 17.6 23.9 15.8 10
861 HenryCorp 17.6 14.2 40.7 7.7
862 wrishel 17.6 35.1 18.3 12.3
863 ForresterEvents 17.6 24.5 25.8 9.9
864 frankgillett 17.5 24.8 27.6 9.9
865 ehigdon 17.5 33.3 23.9 12.2
866 judytsweeney 17.5 24 12.2 9.5
867 emilyvanmetre 17.5 32.5 17.6 11.4
868 janetwaxman 17.5 32.2 44.1 12.1
869 Jim_Burton 17.4 27.9 24 10.8
870 cschreinerNY 17.4 23.2 17.4 9.5
871 rh_forrester 17.4 29.2 19.2 11.5
872 Jeff_Orr 17.3 24.4 3.7 9.5
873 Brazingo 17.3 33.8 5.1 11.6
874 jcstrategyanaly 17.2 22.3 4.4 9
875 keithdawson 17.2 26.3 21.5 10.1
876 Roopamjain 17.1 31.1 17 11
877 zthomas 17.1 34.7 5.5 11.4
878 BobOffutt 17.1 26.2 29.2 10.8
879 gilescottle 17 22.1 29 9.6
880 tdegennaro 16.9 27.7 3.3 10
881 venecialiu 16.8 32.7 4.4 11.2
882 ToleHart 16.6 35.6 1.1 12.2
883 ABI_CleanTel 16.5 24.1 15.9 9.9
884 MesabiGroup 16.5 27.4 13 10.5
885 SGalvino 16.4 28.7 27.8 10.5
886 NicoleDufft 16.4 33.5 12.2 11.4
887 lafleche 16.3 31 14.7 11
888 NadineManjaro 16.2 34.8 3.7 11.5
889 hmorrisidc 16.2 32.3 12.5 11.8
890 joshuaholbrook 16.1 24 3.7 9.3
891 ajglawrie 16.1 31.5 10 11.7
892 emilyriley62 16.1 26 23.5 10.1
893 rcontu 16 32.5 3.7 11.2
894 cnxcnx 15.9 30.4 15.3 10.6
895 Monikino 15.8 21.5 2.9 8.5
896 ivanoortis 15.7 24.9 15.4 9.8
897 AndyGLawrence 15.7 27.5 2.9 9.8
898 b_worthington 15.6 26.7 2.9 9.4
899 kquadri 15.5 23.2 5.1 8.5
900 s_hendrick 15.4 26.4 3.3 9.7
901 hellojackson 15.3 22.2 17.6 8.3
902 MobileAnn 15.1 32.1 2.6 10.9
903 c_green_ 15.1 21.3 20 8.5
904 LiamMcGlynn 15.1 31.1 2.2 10
905 SWdeG 15.1 25 3.7 9.2
906 k1fwe 15 29.7 2.2 10.2
907 peteroconnor 15 23.9 61.6 9.9
908 billmcnee 15 31.1 16.2 11.1
909 wintergreen40 15 20 3.3 7.9
910 maryknox 14.9 34.2 3.7 11.1
911 vbough 14.8 24.6 3.7 9
912 ellenmcarney 14.8 35.7 3.3 11.6
913 twerner1952 14.8 37.3 17.3 11.9
914 neilstrother 14.7 24.7 21 9.5
915 CXPcmdv 14.7 19.9 3.3 8
916 hmanning 14.6 34.7 0 11.8
917 dariotalmesio 14.6 22.2 5.1 8
918 jpops123 14.5 30.2 12.3 9.9
919 SteveHodgkinson 14.4 27.2 12.9 9.8
920 ndrakos 14.3 33.4 0 11.5
921 bill_doyle 14.3 34.3 3.7 11
922 altimetergroup 14.2 32.9 21 11.7
923 IDC_Cloud 14.1 34.3 12.1 11.8
924 dwaldt 14.1 28.7 2.9 9.7
925 bguptill 13.9 23.1 19.6 8.9
926 mbailey316 13.9 30.8 3.7 10.1
927 FranNL 13.6 24.3 15.8 8.5
928 ianbirks 13.6 20.4 2.9 9
929 sunsuvradeep 13.5 15.2 60.4 7.8
930 sradicati 13.5 24.8 18 9.4
931 sfeinberg132 13.4 23.2 17.4 8.5
932 CarrollRheem 13.4 25.1 27.7 9.4
933 ABI_BUSMOBILITY 13.3 26.4 15.9 9.4
934 angelabeckers 13.1 24.5 2.2 8.9
935 CarlClaunch 13.1 23.5 18 9.4
936 drthomasmendel 13 29.5 11.6 9.8
937 varunsedov 12.9 16.2 21.6 6.7
938 ClabbyAnalytics 12.9 22.3 11.7 7.7
939 ellendaley 12.8 30.7 16.6 10.1
940 philkendall 12.8 10.7 16.7 5.2
941 cynick 12.7 21.4 1.1 8.2
942 anogee 12.6 29 20.1 10.2
943 securitynigel 12.6 19 19 7.3
944 JustinSearles 12.6 27.8 15.7 8.8
945 clausbmortensen 11.8 22 14.1 7.9
946 ericbrown_forr 11.7 24.2 16.6 8.6
947 Marc6Sargent 11.5 33.9 2.9 10.1
948 gartner_aadi 11.4 23.7 0.4 8
949 LCD_Market 11.4 30.5 2.2 9.4
950 jmorency1952 11.4 29.7 0.7 9.6
951 sudin_apte 11.3 23.3 10.3 8.1
952 martingarner 11.2 31.8 5.1 8.8
953 martinreynolds 11.1 31.2 1.5 9.6
954 GartnerBI_CRO 10.9 29.2 2.9 9
955 kfbrant 10.8 20.7 21.1 7.7
956 steve_brazier 10.7 32.9 2.9 9.5
957 lnurzynski 10.6 21.6 19.3 6.7
958 dszubert 10.6 31.5 3.3 8.8
959 smingay 10.5 31.4 2.2 9.5
960 susanmcneice 10.3 23.1 2.2 7.7
961 gdeb40 10.3 30.2 0.4 9
962 davidwang 10.2 17.1 10.4 6.3
963 Lussanet 10.1 30.8 2.2 9.2
964 cmilanesi 10 31.3 0 9.8
965 ChrisGood 9.9 31.1 2.9 8.4
966 rglaz 9.8 23.1 3.7 7.4
967 rsallam 9.6 30 2.2 8.7
968 Pfirstbrook 9.6 29.5 2.6 8.5
969 kilucas 9.6 30.8 0.7 9.4
970 jake1306 9.5 22.3 4.8 6.7
971 ovum 9.5 33.1 0 9.8
972 evaausalo 9.4 19.3 20.7 7
973 JohnKatsaros 9.3 28.1 2.9 8.1
974 cdgerm86 9.3 28.5 0.7 8.7
975 EricSiegel 9.1 33 0 9.5
976 baldydubois 9.1 22.9 1.5 7.4
977 IDC_Compliance 9 27.6 0.4 8.5
978 lauramclellan 9 29.7 0.7 8.9
979 cbyrnes 9 30.4 0.4 9
980 MadihaAshour 8.9 20.7 4.8 6.1
981 ritaeknox 8.7 13.8 0.7 5.4
982 rebeccawetteman 8.6 25.9 0.4 7.8
983 longhaus 8.4 19.1 19.5 6.6
984 CuSe93 8.2 13.5 10.8 4.5
985 SimEllis 8.2 19.9 3.7 6.2
986 selinnachin 8.1 16.9 2.9 5.3
987 wpurvis 8.1 20.1 4.8 5.7
988 ABIBurden 7.9 22.1 2.2 6.8
989 marknemec 7.7 27.3 0.4 7.9
990 mcantara 7.7 20.3 4 5.8
991 Eddie_Radcliffe 7.7 18.7 4 5.3
992 IMEXresearch 7.6 24.1 2.2 6.7
993 DrBrianLambert 7.6 13.1 15.2 4.7
994 Texas54 7.4 17.4 1.5 5.4
995 bergeay 7.1 23.6 2.2 6.4
996 janeclabby 6.9 17.2 2.9 5.3
997 ErrolRasit 6.6 22.2 0 6.7
998 KenVollmer 6.4 21.1 0 6.2
999 mktleader 6.3 16.4 3.7 4.5
1000 MelanieAPosey 6.1 19.1 3 5.6

Algorithm and Methodology tmp9CD

Following – Twitter lists the number of people each user follows. The tendency for most celebrities is to only follow a few individuals. The more people that someone follows, there is an increased likelihood of them actively participating in conversations with the community instead of simply broadcasting to it. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.

Followers – Twitter lists the number of people that follow each user. Like subscribing to a feed, this is a clear indication of ‘popularity’ as it requires someone to actively request participation. Even though TweetLevel has a ranking of people based upon popularity, it is influence, engagement and trust that is more important. Due to the nature of logarithmic ranges, a change in the number of people that follow someone, such as from 500 – 1000, will give a far higher change in score than a move from 180K – 200K. Following ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Note: Twitter opened its API to TweetLevel so that data could be sourced easily and quickly to benefit the user.

Since the initial creation of TweetLevel, we have now been able to incorporate Twitter Lists into this part of the algorithm. Someone’s follower score will increase depending upon the number of times a user is included in a list, the number of people who follow that list and the authority of those people.

Updates – How often does someone update what they are doing. This number is purely objective as it scores someone highly no matter what the content of their post (i.e. how relevant is it). Nevertheless it is assumed that if someone posts frequently but has poor content then their ‘followers’ will decrease. Update ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 30) that was used as part of the algorithm. Name Pointing – e.g. @name – How many people engage in conversation with a celebrity or point to their name. The clearest way to establish this is to run a search on the number of people who reference @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 30) – again this was then used as part of the algorithm.

Retweets – Has a tweet caused sufficient interest that it is worth re-submitting by others? Despite a great deal of ‘noise’ (i.e. posts that are not relevant or interesting), when someone sees something that is of high interest, their post can be re-tweeted. The clearest way to establish this is to run a search on the number of people who reference RT @username in a message. This calculation is based upon a one month period combined with a 24 hour period. The number of times this happens is calculated with each range was assigned a number (0 to 50) – again this was then used as part of the algorithm.

Twitalyzer – “This is a unique (and online) tool to evaluate the activity of any Twitter user and report on relative influence, signal-to-noise ratio, generosity, velocity, clout, and other useful measures of success in social media.” This 3rd party tool is a useful method to combine automated metrics dependent upon criteria within posts and publicly available numbers. Where tools such as this are available, we incorporate them into the algorithm to achieve a more confident score. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twitalyzer noise to signal ratioSignal-to-noise ratio is a measure of the tendency for people to pass information, as opposed to anecdote. Signal can be references to other people (defined by the use of “@” followed by text), links to URLs you can visit (defined by the use of “http://” followed by text), hashtags you can explore and participate with (defined by the use of “#” followed by text), retweets of other people, passing along information (defined by the use of “rt”, “r/t/”, “retweet” or “via”). If you take the sum of these four elements and divide that by the number of updates published, you get the “signal to noise” ratio. Twitalyzer gives users scores from 0 to 100. Ranges were determined (i.e. more than 20, more than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twinfluence RankTwinfluence is an automated 3rd party tool that uses APIs to measure influence. For example: “Imagine Twitterer1, who has 10,000 followers – most of which are bots and inactives with no followers of their own. Now imagine Twitterer2, who only has 10 followers – but each of them has 5,000 followers. Who has the most real “influence?” Twitterer2, of course.” As with Twitalyzer, this index uses 3rd party tools to add greater confidence in the overall Twitter score. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Twitter GraderTwitter Grader is the final automated tool to add greater confidence to the final index. This site creates a score by evaluating a twitter profile. Similar to the other criteria, ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

 Involvement Index – The Involvement Index is unique Edelman IP that calculates a score based upon how an individual engages with their community. It is calculated by analysing the content of an individual posts. People who score highest in this category have frequent, relevant, high-quality content that actively involved the twitter community (asking questions, posting links or commenting on discussions) and did not purely consist of broadcasting. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Velocity Index – As more people engage on Twitter, it may become harder to keep activity going. The velocity index measures changes on a regular basis and assigns a score based on increased or decreased participation. Ranges were determined (i.e. less than 20, less than 30, etc.) and each range was assigned a number (0 to 20) that was used as part of the algorithm.

Weighting - Each specific variable listed above was given a standard score out of 10. Using a weighting scale I varied the importance of the each metric to establish an individual’s total score.

Weighted for Popularity – the key variable is the number of people someone has following them. There are many online tools that show this such as Twitterholic.

Weighted for Engagement – the key variables are an individual’s participation with the Twitter community (as measured by the Involvement Index), with additional emphasis on the frequency of people name pointing an individual (via @username), the numbers of followers and the signal to noise ratio. Other attributes were included in the final score but were given a lower weighting.

Weighted for Influence – the key variables in this instance is a combination of the number and authority of someone’s followers together with the frequency of people name pointing an individual (via @username) and the how many times and individuals posts are re-tweeted. Other attributes were included in the final score but were given a lower weighting.

Weighted for trust – the best measure of trust is whether an in individual is will to ‘trust’ what someone else has said sufficiently that they are also prepared to have what they tweeted associated with them. The key metric in this instance are a combination of retweets and number of followers. Other attributes were included in the final score but were given a lower weighting. In the true spirit of ‘open sourcing’ this work, I welcome your comments, views and criticisms in how this approach can be as accurate as possible. Whereas I don’t believe for one moment that TweetLevel has found the holy grail of social media measurement, I think it is a good step forward and look forward to discussing this with you.

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23 Responses to “Top Analyst Tweeters”

  1. I’m not a top anything, but I think my rank is about right when I look at all the people that I follow here. My one concern is that I think the Engagement ranking needs a bit of tweaking. I see a few twitter accounts with very few posts, but with very high engagement rankings, which makes it look like there’s some sort of rate-based ranking that supersedes volume.

    Otherwise, it’s fascinating stuff and actually helps show me where I need to improve to be a better Twit. ;) Thanks!

    Hyoun

  2. Interesting methodology – I’m curious how I rank if you add me (I’m new to the analyst role as of June, but active on the social media – @stu on Twitter). Note that @abnerg is now working for a vendor, no longer as an analyst. Have you considered using a list or directory where people could add/remove themselves? Options such as We Follow or Listorious are possibilities.
    Cheers,
    Stu
    Wikibon

  3. 3 Stephen Loudermilk

    Congrats to all the analysts who made this list!

    I would love to see an analyst relations and media relations TweetLevel list.

    Is anyone developing this at Edelman?

  4. Awesome post! there are quite a few people I wasn’t following on the list and whom I’m glad to discover.

    Please add me, TweetLevel says I’m at 48.0.

    I updated my bio and registered to Sage’s directory to reflect that I also analyze the industry.

    Thanks,

    Josh

  5. Interesting post, interesting methodology. @itworks is an IT industry analyst here in Belgium but we are not in this worldwide list.

    I have checked out where @itworks would be placed, and I am happy to see that you put me in the top-250, close to my good friend Michael @DorchonIT and the honorable @TonyByrne

    Patrick @itworks Van Renterghem

  6. Great post. Fun to see many of my friends so well represented. Would enjoy seeing how I would fair. Please add @shawnrog

    Shawn Rogers
    VP Research – Business Intelligence
    Enterprise Management Associates

  7. Hi Jonny – very cool list, and as an x-Yankee guy from mid-90′s it’s interesting to see how the ‘new-age’ firms (Altimeter, Econsultancy etc) compare to the old-school firms.

    Can you add me to your updated list as well – I’m a 41.0 on TweetLevel, and still do advisory work for a number of vendors and corp clients, blog at http://abonde.typepad.com/blog, and turn out a few white papers now and then, while also helping to start-up Offerpop.

    thanks!
    Allen
    twitter.com/abonde
    http://www.EvokeCRM.com

    PS: I also had a ZX81…and an Atari 800 back in the day :-)

  8. Thanks for the work involved in this exercise. I know it takes a lot of time to do this.

    Your formula is pretty complicated. If I used something like that in a report clients and my editors would be complaining.

    The key, I think, is to balance how much you talk and converse with actually having something to say. (That comes from research.)

  9. Thanks everyone for your comments – really appreciate it. A few responses:

    @dahowlett @avigreengart @stu @itworks @shawnrog @abonde @JoshNursing – am updating the list with your names – thanks for letting me know.

    Hyoun – you are right, the engagement score is worked out with a multitude of factors beyond volume.

    Stephen – I will publish an AR version of this next month. Should be interesting :)

    Josh – as it happens the formula is all about being transparent. I can’t stand measurement tools that purely focus on popularity so have tried to be as open as possible about the inner works of how tweetlevel works. There is some real science and hard-core maths behind this if you want to dig deeper.

  10. Thanks for the work on this list and for including me. Also a good resource to easily explore new folks to follow!

  11. Jonny, I’m sure it’s a complicated equation for engagement, but when the result says that ekirchheimer, maureencfleming, Cliff_Condon, ian_wesley, peteroconnor, and sunsuvradeep are all more “engaged” than Jeremiah Owyang when Jeremiah has 10x the twitter engagement and posts of all of the rest combined, it sticks out. Cliff is a great analyst in many ways, but I don’t think his Twitter account is what he’s best known for.

    It’s still the best tool of measurement that we have for this, but there is something in the engagement scoring that doesn’t ring true the same way that the other areas do.

  12. Hyoun

    You raise an interesting point and one that is crucial to understanding TweetLevel.

    What is key is how someone engages recently within micro-communities. it is more important to grasp how someone has conversations within their niche rather than just broadcasting.

    In this instance, though Jeremiah is indeed a superstar, the way he engages twitter recently within his community is far less then the people you referenced. If you have a look at previous scores, you will see he has a far higher engagement level. Maybe he was just busy and didn’t have time the past two weeks – its unlucky but Tweetlevel aims to reward those people who currently engages well as oppose to who used to.

  13. A lot of work went behind this post and many thanks to Jonny for this. I am on this list as are many people who I would expect to be as key influencers but more importantly there are many more people here who I did not know in advance and that’s the real value of this list. In my case, the primary vehicle of contribution to the Web is not twitter but rather the open gardens blog. Nevertheless, I think this list shows people who are influential, who contribute original content and engage – so its very useful kind rgds Ajit

  14. Thanks for adding me, Jonny.

    Come to think of it, the ranking should be an app to update it in realtime for analysts. I’m already up to about the 90th rank and a score of 49.4 so it can change very fast.

    Actually, I am sure that it would benefit a lot of people for other domains. e.g. let’s say I want to know the top ranking Twitterers for Startups, or the best Twitterers for Novel Writing, or the best Twitterers about Travels.

    This would be an awesome new tool.

  15. Great post. Why dont you have a Share this icon for us to share with others?

  16. Your analysis is ignoring an important consideration. People are looking for insight which can come from other than official analysts. Us end-customers are equally worth listening to…

  17. Hi there,

    I see you are still tracking cms watch (we were 7th last time round). However we changed the company name at the start of this year to The Real Story Group and that is no longer used.

    Now it is http://www.realstorygroup.com – @realstorygroup with the analysts also individually tweeting for example @alanpelzsharpe etc

    Best!

    Alan

  18. 18 ddines

    I feel like a killjoy in this discussion. It looks like this is a popularity contest and quantity over quality. And does having higher twitter rank make me a better analyst or mean that I have more influence? Am I better off influencing 5000 mid level managers or 50 CEO’s? Are the CEO’s following me on Twitter, or do they prefer a phone call?

    As far as I can see, it just means that higher ranked analysts are better at using the tool. Don’t get me wrong, I think Twitter is great, but it is just tool for communicating and not end in itself.

    Am I missing something?


  1. 1 So what is an analyst anyway? | Strategic Messaging
  2. 2 Technobabble 2.0’s Top Analyst Tweeters provides useful insights into visibility, but does not show who is influential » SageCircle Blog
  3. 3 The 7 Tenets Of Building A “Star Analyst” Firm
  4. 4 Top Analyst Tweeters « The IIAR Blog
  5. 5 Open Gardens » I am ranked 213 / 1000 globally by influence among the top analysts using twitter

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