gssi, june 22-24, 2011 global sales barometer nick panagopoulos, phd athens university of economics...

GSSI, June 22-24, 2011 Global Sales Barometer

Nick Panagopoulos, PhDAthens University of Economics & Business

Paolo Guenzi, PhDSDA School of Management – Bocconi University

Global Sales Barometer (GSB)Results from the 2010 survey


• Avlonitis, George

• Bolman Pullins, Ellen

• Borgmeier, Arndt

• Brassier, Pascal

• Görne, Jobst

• Guesalaga, Rodrigo

• Humenberger, Anna

• Kairisto-Mertanen, Liisa

Acknowledgments to country coordinators

2

• Korpela, Pentti

• Kwiatek, Piotr

• Lee, Nick

• Leszczynski, Grzegorz

• Rogers, Beth

• Singh, Ramendra

• Weilbaker, Dan

• Wilkinson, John


● Artur Baldauf

● Bill Cron

● Ken Evans

● Greg Marshall

● Bill Moncrief

● Tom Leigh

● Rosann Spiro

Additional acknowledgments

3


ABOUT THE GSB

4


Mission and objectives

Mission The GSB is an annual GSSI-sponsored research initiative that aims

at providing sales academics and practitioners with the latest global insights on what constitutes sales best practice.

Objectives Identify the trends in the world of selling on a global scale. Provide sales practitioners a basis for benchmarking sales best

practice. Publish sales research priorities and a research agenda on topics of

importance to organizations worldwide.

5


Benchmarking salesbest practice across

• Countries• Sectors• High vs. low performing

companies• Time*

Benchmarking salesbest practice across

• Countries• Sectors• High vs. low performing

companies• Time*

Sales goalsSales goals

Sales expenses budget


Sales competenciesSales competencies

Sales management practices


Improving sales practice

6

Sales management expenses


Sales compensationSales compensation

Customer strategyCustomer strategy

Sales channelsSales channels

Customer portfolio mix


GSB Research Model


RESEARCH METHODS

7


Key informants: Sales executives.

Population: Any organization employing salespeople in both B2B and B2C

settings across countries.

Sampling frames: Compiled by country coordinators at the local level.

Data collection method: Online data collection was the dominant method of collecting

responses.

Research design

8


Initial size of sampling frame: 33,872.

- Nonexistent contacts: 436.

= Effective size of sampling frame: 33,436.

Total number of initial responses:1,526 (4.6% response rate)

- cases with excessive number of incomplete responses: 452

= Total number of effective responses: 1,074

Data collection

9


Distribution of effective responses across countries

10

Australia

India

Austria

UK

Finland

Germany

US

Poland

France

Chile

Greece

Italy

0 0.05 0.1 0.15 0.2 0.25 0.3

0.1%

0.7%

2.0%

2.0%

3.7%

4.7%

5.4%

5.8%

8.0%

19.6%

20.6%

27.6%


Initially designed in the English language

Translation-back-translation method was employed

Pretesting conducted in Greece and Italy

Research instrument

11


PRELIMINARY ANALYSES

12


1. Competence assessment:

• We assessed the competence and knowledge level of respondents by employing a 3-item 7-point scale(see Kumar, Stern & Anderson, 1993, Academy of Management Journal)

• Overall, the mean value of competency was 6.13 indicating a relatively high level of competence among respondents.

• To ensure that only those responses of maximum quality are included in the analysis, however, we retained only those respondents that reported an average competency of at least 4 on the 7-point scale.

• This procedure resulted in a final usable sample of 670 respondents across countries.

Preliminary analyses

13


2. Conversion of monetary values: • To allow meaningful comparisons of monetary values (i.e., compensation, sales

expenses, and sales revenues) among different countries that are characterized by different cost-of-living and GDP levels, variables were converted to international dollars by using the 2010 Purchasing Power Parity index (implied PPP exchange rate) which is published by the International Monetary Fund and the World Bank.

• A PPP exchange rate is the ratio of the local currency prices of a particular basket of goods in two different countries.

3. Company performance groups: • For the purposes of the study, companies were grouped into 2 groups (i.e., high vs.

low performing) on the basis of their responses on four items which assessed company performance relative to major competitors on a 7-point scale ranging from 1=“Much worse than competitors” to 7=“Much better than competitors”(Vorhies and Morgan, 2005, Journal of Marketing).

• Specifically, items referred to performance in terms of (a) market share growth, (b) sales revenue growth, (c) profitability, and (d) customer satisfaction.

• Cronbach’s alpha reliability value for this scale was .80, thereby providing evidence that the scale is a reliable measure of company performance.

Preliminary analyses

14


SAMPLE PROFILE

15


Job titles of respondents

16

Chief Sales Executive/Officer

General/National Sales Manager

Field/District/Regional Sales Manager

Sales Manager

Business-Unit/General Manager

Vice President of Sales/Marketing

Top Management (President/Chairman/CEO/Owner/Managing Director)

Marketing/PR/Product Manager

Salesperson/Sales support employee

Business development manager

Other

Account/National/Key Account Manager

Commercial Director

Marketing & Sales Manager

Operations/Services Managers

HR manager

Export Manager

Finance/Accounting Manager

0 0.05 0.1 0.15 0.2 0.25 0.3

26.4%

19.9%

11.7%

11.0%

10.6%

3.3%

3.2%

2.9%

2.9%

1.7%

1.5%

1.0%

1.0%

0.7%

0.7%

0.6%

0.6%

0.4%


Area of economic activity (sectors)

17The statistical coding schemes employed to group companies around areas of economic activity are in line with the NACE and ISIC schemes, which are representative of world commerce (see and

Mining and quarrying

Real estate activities

Public administration and defense

compulsory social security

Other

Water supply

sewerage, waste management and remediation activities

Arts, entertainment, and recreation

Education

Transportation and storage

Administrative and support service activities

Electricity, gas, steam and air conditioning supply

Accommodation and food service activities

Cosmetics/pharmaceuticals

Human health and social work activities

Food manufacturing

Construction

Professional, scientific, and technical activities

Financial and insurance activities

Agriculture, forestry, and fishing

Information and communication

Wholesale and retail trade

Manufacturing (other than food)

0 0.05 0.1 0.15 0.2 0.25 0.3 0.35

0.55%

0.55%

0.55%

0.55%

0.82%

0.96%

1.51%

1.78%

1.92%

2.19%

2.88%

3.15%

3.42%

3.56%

4.38%

5.75%

6.16%

6.44%

10.14%

12.19%

30.55%


MAIN FINDINGS

18


Sales competencies

Numbers correspond to mean values on a 7-point scale, where -1 = “Much worse than competitors” and +3 = “Much better than competitors”19

Maintaining customer relationships

Building customer relationships

Providing good after-sales service to customers

Closing sales

Providing leadership to salespeople

Targeting customers in the right way

Setting sales goals

Selecting the appropriate selling model for each customer

Organizing the sales force

Cross/up-selling customers

Delivering the right sales message

Segmenting customers

Working effectively with other functions in the organization

Providing good support to salespeople

Getting customer/market information

Avoiding excessive discounting

Selecting the right mix of sales channels to reach customers

Keeping the best salespeople

Controlling sales expenses

Turning sales goals into sales plans

Providing training to salespeople

Generating attractive sales leads

Evaluating sales force performance

Building salespeople’s skills

Accurately forecasting sales

Allocating sales resources

Motivating salespeople

Building sales managers’ skills

Determining the right size of the sales force

Quickly turning new recruits into effective salespersons

Using sales technologies

Decreasing the time needed to close a sale

Designing compensation systems

Attracting the best sales talent

0.00 0.20 0.40 0.60 0.80 1.00 1.20 1.40

1.3012048192771

1.28808446455506

1.14660493827161

0.928571428571429

0.918918918918919

0.914634146341463

0.900943396226416

0.896445131375583

0.894984326018809

0.87237479806139

0.846860643185299

0.842356687898089

0.834920634920635

0.815047021943578

0.800911854103344

0.786729857819909

0.78003120124805

0.758400000000001

0.751227495908347

0.748417721518987

0.733333333333334

0.721259842519691

0.686084142394823

0.685805422647533

0.66824644549763

0.640575079872205

0.606060606060607

0.604651162790698

0.55250403877221

0.533687943262411

0.52534562211982

0.498397435897438

0.35

0.343642611683851


Conclusions

20

• There is much room for improvement in almost any aspect of sales force and sales process management (mean value of competencies is not very high).

• Clearly, India, US, and Austria are outperforming the rest of the countries with regard to the average level of most sales competencies

• The lowest average levels of competencies are found in the following countries:

• Finland• France• Germany• Italy• UK

• There is much room for improvement in almost any aspect of sales force and sales process management (mean value of competencies is not very high).

• Clearly, India, US, and Austria are outperforming the rest of the countries with regard to the average level of most sales competencies

• The lowest average levels of competencies are found in the following countries:

• Finland• France• Germany• Italy• UK


Conclusions

21

• Average levels for most of the competencies do not differ significantly among sectors.

• However, the following statistically significant differences were found:

Competencies Highest-performing sectors Lowest-performing sectors

Organizing the sales force Transportation and storage Accommodation and food service activities

Building salespeople’s skills Other Public administration and defense; compulsory social security

Controlling sales expenses Construction Real estate activities

Working effectively with other functions in the organization

Administrative and support service activities Public administration and defense; compulsory social security


Conclusions

22

• More effective companies outperform lower performing ones across all 34 sales competencies.

• Sales competencies that high performing companies differ most compared to low performing companies are in descending order:

1. Motivating salespeople

1. Attracting the best sales talent

1. Providing good after-sales service to customers

1. Closing sales

1. Accurately forecasting sales

• These are areas that companies around the world should target for improvement

• Academic research and teaching need to focus at these areas in order to help companies improve their performance



23


Sales management expenses across countries in Local Currency Units

24

Mean cost of …

…recruiting, selecting, and hiring an individual

new recruit

...training an individual new recruit

... training an established salesperson

… a sales call

Australia (Dollars) NA NA NA NA

Austria (Euros) 3.804,00 6.583,33 2.300,00 86,25

Chile (Pesos) 1.279.354,65 2.024.588,24 1.095.912,50 112.734,21

Finland (Euros) 8.447,06 5.852,94 4.052,94 372,50

France (Euros) 8.629,63 9.380,00 7.126,09 611,77

Germany (Euros) 17.520,00 15.132,81 3.903,57 672,42

Greece (Euros) 13.002,94 1.444,84 1.029,53 168,49

India (Rupees) 16.500,00 31.625,00 25.600,00 641,00

Italy (Euros) 9.403,03 5.934,85 3.796,67 473,57

Poland (Zloties) 4.935,29 3.650,00 3.692,86 279,29

UK (Pounds) 8.364,08 8.250,00 4.653,64 519,75

US (Dollars) 33.427,78 35.125,00 26.325,26 1.140,16

Mean costs are shown; Costs across countries are not directly comparable since they are measured in local currency units. They should only be interpreted within the realms of a given country.

Executives can use these figures to benchmark their expenses in their respective country


Average cost of recruiting, selecting, and hiring a new recruit across countries

25

US Germany Greece UK Italy France Finland Austria Chile Poland India

0.00

5,000.00

10,000.00

15,000.00

20,000.00

25,000.00

30,000.00

35,000.0033427.7777777778

20515.2224824356

17959.8570551609

12577.5592828225

10685.261707989

9503.997389459898780.72642778525

4449.12280701757

3165.716434304952507.77140124343

951.776649746197

Mean costs are shown; Costs are converted to international dollars using IMF/WB PPP index 2010; Australia is excluded from this analysis due to very low number of cases; Statistically significant differences were found among countries based on Kruskal Wallis test (Chi-square = 79,38; Asymp. Sign. = ,000)

SS


Average cost of training a new recruit across countries

26

US Germany UK France Austria Italy Finland Chile Greece Poland India

0.00

5,000.00

10,000.00

15,000.00

20,000.00

25,000.00

30,000.00

35,000.00

40,000.00

35125

17719.9209601874

12406.015037594

10330.3964757709

7699.805068226126744.14600550967

6084.13843707961

5009.76976426805

1995.638266938061854.674796747961824.23857868021


SS


Average cost of training an established salesperson across countries

27

US France UK Germany Italy Finland Chile Austria Poland India Greece

0.00

5,000.00

10,000.00

15,000.00

20,000.00

25,000.00

30,000.00

26325.2631578947

7848.1133882398

6997.94941900205

4570.926731348284314.393939393954213.03656597774

2711.795520231232690.05847953217

1876.451800232291476.695892939551422.00736648251


SS


Average cost of a sales call across countries

28

US Germany UK France Italy Finland Chile Greece Poland Austria India

0.00

200.00

400.00

600.00

800.00

1,000.00

1,200.001140.15789473684

787.382016890209781.578947368424

673.760125053289

538.152011922503

387.214137214137

278.956693241537

232.715074980267

141.913472706155

100.877192982456

36.9750807568064


SS


Average cost of recruiting, selecting, and hiring a new recruit across sectors

29

Mean values are shown; Expenses are converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were found among countries based on Kruskal Wallis test (Chi-square = 41,934; Asymp. Sign. = ,002)


Other

Food manufacturing

Education



repair of motor vehicles and motorcycles




Water supply






Manufacturing


Construction





0.00 5,000.00 10,000.00 15,000.00 20,000.00 25,000.00 30,000.00

659.586697035555

1516.59892423393

2880.82307885485

3942.1318861688

4181.55931679163

4403.66362144549

4791.16355307866

4875.26987076031

6939.31356792677

7630.65678814577

7781.58164164143

8243.21212781852

8978.17906533274

10409.3198167719

11628.2698380185

12305.1524655126

13837.1387453983

15104.5812038905

16644.8237885463

26905.9671645075SS


Average cost of training a new recruit across sectors

30



Education



Food manufacturing


Water supply



Other




Construction



Manufacturing







Real estate activities

0.00 5,000.00 10,000.00 15,000.00 20,000.00 25,000.00 30,000.00 35,000.00

1483.4620148768

3354.80232214029

3366.51199326848

3728.56958737225

3730.08554310632

3743.07482796686

3995.03668369497

4384.44606233109

5358.05796669945

5395.7209393423

5512.91016837147

7116.03573393008

7164.73397849114

7820.85953432051

10535.1348271969

12242.3101883122

12467.2820432248

16299.4315949627

25697.2550676353

32848.751835536

33039.6475770926

SS


Average cost of training an established salesperson across sectors

31





Other

Food manufacturing

Construction




Water supply




Education




Manufacturing






0.00 5,000.00 10,000.00 15,000.00 20,000.00 25,000.00

831.473955735737

1425.15614352416

1721.04315233529

2035.99967597704

2411.7084338396

2581.26311405504

3003.3893056776

3009.30870365276

3080.86331232141

3246.48851247145

3459.66277169046

3683.49356004882

4181.63019723279

4487.72417862261

4784.83956024316

4954.16195551448

5508.19219453868

8058.26860320292

15877.9624613887

20844.3465491924

SS


Average cost of a sales call across sectors

32







Food manufacturing








Other

Education

Construction

Water supply


Manufacturing





0.00200.00

400.00600.00

800.001,000.00

1,200.001,400.00

1,600.001,800.00

2,000.00

58.2195421595754

132.011426550508

158.282779907651

172.092157396751

173.240331614635

192.146135962637

193.946851162765

202.239673904715

251.328682271514

257.179032388806

323.272883782921

370.52512073895

495.594713656388

533.681517773059

681.207792410013

734.200419894972

764.931482550292

797.164886149694

803.095663593097

1884.74669603524

SS


Average cost of recruiting, selecting, and hiring a new recruit between performance groups

33

Mean values are shown; Expenses are converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were not found between groups of companies based on T-test (T-test = -1,1592; Sig. (2-tailed) = ,247)

Low performing companies High performing companies0.00

2,000.00

4,000.00

6,000.00

8,000.00

10,000.00

12,000.00

14,000.00

8,249.55

12,600.52

NS


Average cost of training a new recruit between performance groups

34

Mean values are shown; Expenses are converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were found between groups of companies based on T-test (T-test = -2,544; Sig. (2-tailed) = ,011)


1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

7,000.00

8,000.00

9,000.00

10,000.00

5,510.03

9,312.89

SS


Average cost of training an established salesperson between performance groups

35

Mean values are shown; Expenses are converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were not found between groups of companies based on T-test (T-test = -1,160; Sig. (2-tailed) = ,247)


1,000.00

2,000.00

3,000.00

4,000.00

5,000.00

6,000.00

3,659.88

5,250.29NS


Average cost of a sales call between performance groups

36

Mean values are shown; Expenses are converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were not found between groups of companies based on T-test (T-test = 0,270; Sig. (2-tailed) = ,787)


435.00

440.00

445.00

450.00

455.00

460.00

465.00

470.00

475.00

480.00

479.90

449.29

NS


Conclusions

Clearly, more effective companies don’t overspend on everything.

• Expenses for…• Recruiting, selecting, and hiring salespeople,• Training established salespeople, and • Making sales calls

• …do not differ significantly between the two groups of companies.

• Higher performing companies, however, spend more money for training new recruits.

• Apparently, this helps companies in ramping up new recruits faster and more efficient.

Clearly, more effective companies don’t overspend on everything.

• Expenses for…• Recruiting, selecting, and hiring salespeople,• Training established salespeople, and • Making sales calls

• …do not differ significantly between the two groups of companies.

• Higher performing companies, however, spend more money for training new recruits.

• Apparently, this helps companies in ramping up new recruits faster and more efficient.

37



38


Number of new salespeople hired

39Mean values are shown; Statistically significant differences were found among countries based on Kruskal Wallis test (Chi-square = 125,92; Asymp. Sign. = ,00); Australia is excluded from this analysis due to very low number of cases

SS


Number of terminated salespeople


SS


Number of salespeople who left voluntarily


SS


Number of salespeople assigned to a field sales supervisor


SS


% of the sales force that is female


SS


Age of the sales force


SS


Number of new salespeople hired

45Mean values are shown; Statistically significant differences were found among countries based on Kruskal Wallis test (Chi-square = 64,45; Asymp. Sign. = ,00)

SS


Number of salespeople who were terminated


SS


Number of salespeople who voluntarily left


SS


Number of salespeople who were assigned to a field sales supervisor


SS




SS


Number of weekly sales calls


SS


Comparison between performance groups

51

number of salespeople employed

number of new salespeople hired

number of salespeople who were terminated

number of salespeople who voluntarily left

number of salespeople who were assigned to a field sales supervisor


% of the sales force that holds a college/university degree or more (e.g. MBA)

age of the sales force

number of customers assigned to a salesperson

number of weekly sales calls

0.0020.00

40.0060.00

80.00100.00

120.00140.00

49.8480392156861

4.08578431372547

5.52912621359224

2.07211538461538

7.05494505494503

21.0841346153846

41.7230392156863

38.980487804878

104.213888888889

28.2861111111111

74.71

8.83291457286437

5.90954773869347

3.0528967254408

8.14344262295082

21.7740740740741

44.9770408163264

37.9950372208437

137.19262295082

42.6915819209041

High performing companies

Low performing companies

Mean values are shown; Statistically significant differences (at least at α = 5%) found between groups are based on T-test and are indicated by a red circle


Sales compensation practices

52


Compensation practices across countries(in local currency units)

53

Average…

Countriesgross

monthly salary

gross monthly bonuses

gross monthly commission

gross monthly fringe

benefits

total gross monthly

compensation

total gross annual

compensation

Australia (Dollars) NA NA NA NA NA NA

Austria (Euros) 3.164,29 842,86 533,75 280,00 3.730,50 44.766,00

Chile (Pesos) 869.941,67 329.537,50 574.512,94 106.691,18 1.675.067,80 20.100.813,56

Finland (Euros) 3.344,74 676,92 872,73 420,67 5.351,25 64.215,00

France (Euros) 2.833,53 739,91 839,75 274,88 4.163,25 49.959,00

Germany (Euros) 4.144,61 1.114,91 1.043,94 495,33 4.950,00 59.400,00

Greece (Euros) 1.551,66 622,44 211,96 220,67 2.323,19 27.878,32

India (Rupees) 89.600,00 29.600,00 20.200,00 7.625,00 106.875,00 1.282.500,00

Italy (Euros) 2.546,24 313,10 1.864,53 370,31 4.366,39 52.396,65

Poland (Zloties) 11.905,26 2.188,89 7.082,35 977,06 17.189,29 206.271,43

UK (Pounds) 3.051,21 498,69 280,27 502,85 4.112,00 49.344,00

US (Dollars) 4.254,64 1.104,37 5.284,83 1.333,69 11.584,83 139.017,92

Mean values are shown; Compensation across countries is not directly comparable since remuneration is measured in local currency units. They should only be interpreted within the realms of a given country.

Executives can use these figures to benchmark their compensation practices in their respective country


Gross monthly salary (PPP-adjusted)

54

Mean values are shown; Compensation is converted to international dollars using IMF/WB PPP index 2010; Australia is excluded from this analysis due to very low number of cases; Statistically significant differences were found among countries based on Kruskal Wallis test

SS


Gross monthly bonuses (PPP-adjusted)

55


SS


Gross monthly commission (PPP-adjusted)

56


SS


Gross monthly fringe benefits (PPP-adjusted)

57


SS


Total gross monthly compensation (PPP-adjusted)

58


SS


Gross monthly salary (PPP-adjusted)

59

Mean values are shown; Compensation is converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were found among sectors based on Kruskal Wallis test

SS


Gross monthly bonuses (PPP-adjusted)

60


SS


Gross monthly commission (PPP-adjusted)

61

Mean values are shown; Compensation is converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were not found among sectors based on Kruskal Wallis test

NS


Gross monthly fringe benefits (PPP-adjusted)

62

Mean values are shown; Compensation is converted to international dollars using IMF/WB PPP index 2010; Statistically significant differences were not found among sectors based on Kruskal Wallis test

NS


Total gross monthly compensation (PPP-adjusted)

63


SS


Compensation practices across performance groups (PPP-adjusted)

64Mean values are shown; Statistically significant differences between company groups are indicated by a red arrow


Sales goals

65


How did the sales goals (in monetary value) assigned to your sales force for 2010 change as compared to 2009?

66


What is the average % change in sales goals (in monetary value) between 2009 and 2010?

67


Sales goals have increased by ... %

68

Mean values are shown; Australia is excluded from this analysis due to very low number of cases; statistically significant differences were found across countries based on Kruskal Wallis test

SS


Sales goals have decreased by ... %

69

Mean values are shown; Australia is excluded from this analysis due to very low number of cases; no statistically significant differences were found among countries based on Kruskal Wallis test

NS


70

Sales goals have increased by ... %

Mean values are shown; differences across sectors were not found to be statistically significant based on Kruskal Wallis test

NS


71

Sales goals have decreased by ... %

Mean values are shown; differences across sectors were not found to be statistically significant based on Kruskal Wallis test

NS


How did the sales goals (in monetary value) assigned to your sales force for 2010 change as compared to 2009?

72

Mean values are shown; Statistically significant differences were found between groups of companies based on Mann Whitney U test

SS


% of companies’ salespeople having attained their sales goals in 2010

On average across countries, 63% of company salespeople have attained their sales goals in 2010. On average across countries, 63% of company salespeople have attained their sales goals in 2010.

73



Mean values are shown; Australia is excluded from this analysis due to low number of cases; Statistically significant differences were found among countries based on Kruskal Wallis test (Chi-square: 40,818; Asymp. Sign.: 0,000) 74

SS



75

Mean values are shown; Statistically significant differences were found among sectors based on Kruskal Wallis test (Chi-square: 49,76; Asymp. Sign.: 0,000)

SS



76

Mean values are shown; Statistically significant differences were found between groups of companies sectors based on Mann Whitney U test (Mann Whitney U : 30.079,00; Asymp. Sign.: 0,00)

SS

12,9% difference

Globalbenchmark!

Globalbenchmark!



77


Total sales expenses as a ratio of total sales revenues in 2010

On average across countries, the ratio is 18%. On average across countries, the ratio is 18%.

78



79

Mean values are shown; Statistically significant differences were found among countries based on Kruskal Wallis test; Australia is excluded from this analysis due to low number of cases

SS



80

Mean values are shown; Statistically significant differences were found among sectors based on Kruskal Wallis test; Data for the real estate sector were not available

SS



81

Globalbenchmark!

Globalbenchmark!

SS


Compared to 2009 sales expenses budget, how has 2010 sales expenses budget changed in your business

unit/company?

82


Average % of change in 2010 sales expenses budget compared to 2009 sales expenses budget

83


2010 sales expenses budget has increased compared to 2009 sales expenses budget by…

84

Statistically significant differences were not found among countries based on Kruskal Wallis test; Australia is excluded from this analysis due to very low number of cases

NS


2010 sales expenses budget has decreased compared to 2009 sales expenses budget by…

85

Statistically significant differences were not found among countries based on Kruskal Wallis test; Australia is excluded from this analysis due to very low number of cases

NS


2010 sales expenses budget has increased compared to 2009 sales expenses budget by…

86

Mean values are shown; No statistically significant differences were found among sectors based on Kruskal Wallis test; Data for the real estate sector were not available

NS


2010 sales expenses budget has decreased compared to 2009 sales expenses budget by…

87

Mean values are shown; No statistically significant differences were found among sectors based on Kruskal Wallis test; Data for the real estate, mining/quarrying, and accommodation/food service activities sectors were not available

SS


2010 sales expenses budget has increased/decreased compared to 2009 sales expenses budget by…

88

Mean values are shown; Statistically significant differences were found between performance groups based on Mann Whitney U test

SS


Customer strategy

89


% of selling effort that is allocated to the following activities for 2010

90


% of selling effort that is allocated to acquiring new customers

91


SS


% of selling effort that is allocated to retaining and growing current customers

92


SS


% of selling effort that is allocated to winning back lost customers

93


SS


% of selling effort that is allocated to acquiring new customers

94Mean values are shown; Statistically significant differences were found among sectors based on Kruskal Wallis test;

SS


% of selling effort that is allocated to retaining and growing current customers

95Mean values are shown; Statistically significant differences were found among sectors based on Kruskal Wallis test;

SS


% of selling effort that is allocated to winning back lost customers

96Mean values are shown; Statistically significant differences were not found among sectors based on Kruskal Wallis test;

NS


% of selling effort that is allocated to the following activities for 2010

97Mean values are shown; No statistically significant differences were found between groups of companies based on Mann Whitney U test

NS


Sales channels

98


Number of sales channels utilized

More effective companies employ more sales channels to go to markets compared to low performing companiesMore effective companies employ more sales channels to go to markets compared to low performing companies

99



100


SS



101

Mean values are shown; No statistically significant differences were found among sectors based on Kruskal Wallis test;

NS


% of 2010 sales contributed by sales channel

102


% of 2010 sales contributed by company-owned field sales force

103


SS


% of 2010 sales contributed by manufacturing reps/dealers/brokers/agents

104


SS


% of 2010 sales contributed by call centers

105


SS


% of 2010 sales contributed by direct marketing

106


SS


% of 2010 sales contributed by e-commerce

107


SS


% of 2010 sales contributed by mobile commerce

108


SS


% of 2010 sales contributed by company-owned field sales force

109

Mean values are shown; Statistically significant differences were found among sectors based on Kruskal Wallis test;

SS


% of 2010 sales contributed by manufacturing reps/dealers/brokers/agents

110


SS


% of 2010 sales contributed by call centers

111


SS


% of 2010 sales contributed by direct marketing

112


SS


% of 2010 sales contributed by e-commerce

113


SS


% of 2010 sales contributed by mobile commerce

114


SS


% of 2010 sales contributed by sales channel

115

Mean values are shown; Statistically significant differences were found between the two performance groups based on Mann Whitney test

SS



116


% of sales attributed to different customer types

117


% of sales attributed to different customer types

118

Mean values are shown; Statistically significant differences were found between performance groups based on Mann Whitney U test

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gssi, june 22-24, 2011 global sales barometer nick panagopoulos, phd athens university of economics...

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