The influence of customer value on word of mouth: a study of the financial services company in Brazil

Costa, Sandro Bonfim da; Claro, Danny Pimentel; Bortoluzzo, Adriana Bruscato

doi:10.7819/rbgn.v20i2.3798

Sandro Bonfim da Costa

Insper, Marketing Department, São Paulo, Brazil

http://orcid.org/0000-0002-2163-3427

Danny Pimentel Claro

Insper, Marketing Department, São Paulo, Brazil

http://orcid.org/0000-0002-8387-0938

Adriana Bruscato Bortoluzzo

Insper, Quantitative Methods Department, São Paulo, Brazil

http://orcid.org/0000-0003-2872-031X

Responsible editor: Prof. Dr. Susana Costa e Silva

1
. Sandro Bonfim da Costa, Professional Masters in Business Administration, Insper, Brazil. E-mail: Sandro_bonfim@hotmail.com

2
. Danny Pimentel Claro, PhD in Business, Wageningen University, Netherlands. E-mail: dannypc@insper.edu.br

3. Adriana Bruscato Bortoluzzo, Doctor of Statistics, Universidade de São Paulo, Brazil. E-mail: adrianab@insper.edu.br

Contribution of each author:

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Figure 1:
Scatter plot and trend curve of CRV as a function of CRV, both in logarithms.

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Table 1 Reference Empirical Evidence WOM CLV CRV Main findings and limitations Berger, Jonah and Schwartz, Eric M. (2011 ) Journal of Marketing Research Three studies: About 2,000 volunteers, who received product and gift information, reporting recommendations.1,687 volunteers, marketing campaigns sent by e-mail.Study with 120 volunteers, through short conversation with stimuli. Measures the level of recommendation, considering: Product interest level;Accessibility / visibility, tips, promotional gifts. N/A N/A Accessibility forms WOM. Public visibility and tips influence what people talk about. Not always the most interesting products are discussed. It lacks the investigation of the actual gain of WOM in sales and result, as well as the quality and duration of WOM. Hidalgo, Pedro, Manzur, Enrique, Olavarrieta, Sergio and Farías, Pablo (2007 ) Journal of Business Research Chilean firms with CLV calculation, based on public data of large corporations. N/A Measures CLV considering: Fees paid by the customer, less operating expenses.Retention rate based on the % of clients who remain in the company after 1 year.Employs discount rate of 12%. N/A For industry with low level of brand differentiation and low level of customer involvement, seeking cheaper competitor prices reduces CLV and, consequently, stimulates marketing investment. Suggests that future studies should take into account (i) consumer behavior in the after sales, (ii) design of services that are important to the customer, and (iii) investment in sales force, gifts, marketing efforts, etc. Chang, Chun-Wei and Ijose,Olumide (2016 ) Journal of Business Research 4,675 Taiwan’s large bank customers, with 224,112 transactions (January 2011 to January 2013). demographic data (age, income, occupation, ZIP code, family size and marital status); and Transaction data (purchase value, location and store name and purchase date). N/A CLV Calculation considering 4 components: Expenses expectation; Marketing expenses; Retention rate; and Discount rate. N/A Creates 4 customer profiles, not only considering CLV but also Current Value (Most Valuable Customers, Potentialities, Loyalty Crisis and Less Valuable Customers). It seeks to guide paths for the treatment of each identified profiles. As an evolution in future studies, individualized retention rates can be sought, instead of a constant retention rate. One can aggregate additional information about marketing actions, interactions and etc., seeking the impact of these actions in CLV. Persson, Andreas (2013 ) European Journal of Marketing Qualitative method, with analysis of 3 large banks. Interviews with 4 to 6 employees. Information of action costs and behavior change results captured, evaluating effects on CLV and ROI. N/A Seeks to expand CLV measured result through cost reduction, based on strategies to adapt the customer’s behavior N/A Companies that identify sources of high costs related to their customers can derive substantial benefits in reducing these costs regardless of the customer’s profitability. Case studies show that changes in customer behavior reduce costs, maintaining or even increasing retention and margin measured by CLV. As a future evolution, it should expand the number of evaluated cases, expand to other industries and with a longer term to analyze the results. Suggests future research to carry out longitudinal study to measure the long-term effects on CLV. Kumar, V. and Reinartz, Werner (2016 ) Journal of Marketing Extensive literature review related to relationship marketing and CLV, using empirical studies of several authors. N/A Extensive literature review related to CLV, considering use and introduction form. N/A Enjoys vision of Value for the Customer and Customer Value. When analyzing Value for the Customer, it defines the concept of Perceived Value by the client, which can be measured by objective attributes or perceived attributes. When it addresses Customer Value, it uses CLV as an index that measures the present value of a customer, according to future purchases, considering revenues, expenses and behavior. It adds the idea of strategy based on CLV, also used for acquisition, retention and recovery. It brings the view that the Customer Value comes not only from the financial value of their purchases, but also from their influence on other consumers. V. Kumar, J. Andrew Petersen, & Robert P. Leone (2010 ) Journal of Marketing Four studies: Financial companies, including a direct marketing campaign for a sample of 300 clients, out of a total of 14,160 clients.Sample of 600 clients, from the same company, considering total residual of 13,860 customers.Sample (6,700) and control group (6,560) of the residual sample, discounting the two previous groups (13,260).Retail company and sample of 40,000 customers, collected from 2005 to 2007. N/A CLV calculation considering, in a certain period: Client’s expenses expectation;Marketing expenses; andDiscount rate. CRV calculation, considering: Recommendation time;Number of recommendations in the period and margin contribution (excluding margin already existing);Cost acquisition saving in case of customer coming from recommendation. The article shows how to quantify the incremental results in the marketing strategies guided according to CLV and CRV; It empirically illustrates how to determine a set of CRV behavioral drivers, using data from a retail company to drive marketing campaigns more efficiently, as well as opportunities to leverage CRV. As limitations, CRV may not apply to all industries. Not all companies will have the capability and systems to maintain the CRV. CRV works well in a more stable environment. Valenzuela, Leslier, Torres, Eduardo, Hidalgo, Pedro e Farías, Pablo (2013 ) Journal of Business Research Sales force of a large Chilean retail bank, sending 150 questionnaires (measuring 207 items). Response was 132 questionnaires (88% rate of return). N/A It does not calculate CLV directly, but the effect of a CLV-oriented sales force on sales force result. N/A Study shows that there is a positive relationship between sales force oriented CLV and its performance. CLV-oriented sales force behavior is important in building the value of customers and the company. As main limitation, self-reported CLV by a single respondent, when the ideal would be to collect information from varied sources. This study A random sample of 768 clients of a Brazilian financial institution, followed by three steps: Capture of satisfaction and recommendation indexes;Mapping the recommendation behavior; andEffective acquisitions on those who claim to recommend. Captured in the survey, through the recommendation question. A question was created that sought to identify effective recommendation, by respondents indicating names who received recommendations and cross-referencing with firms records to identify effective purchase. Adds to the existing CLV, by seeking to simplify the calculation and making it applicable to most firms, considering as main variables: Potential future revenue, according to product ownership and accumulated balance;Survival rate, measuring the likelihood of customer retention. Adds to the existing CRV measure. The CRV is composed of the value coming from the recommendations of the clients, being the sum of the CLVs of all the nominee individuals. Through the CLV and CRV, the study generates inputs and recommendations for firms seeking to expand sales through WOM, tracking performance not only for the value-added individually by the customer (CLV) but also the value of the clients indicated by him (CRV). In developing criteria for measuring the recommendation (measurement index is little explored academically) a study generates practical index, which can be created and administered by many corporations. There are opportunities for future studies, such as expansion of the study for companies in other industries, looking for possible specific adaptations.

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Table 2:
Description of Variables

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Table 3:
Descriptive Measures and Correlations between Numerical Variables

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Table 4:
Results for Hypothesis 1

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Table 5:
Results for Hypothesis 2 and 3

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Table 1
Reference	Empirical Evidence	WOM	CLV	CRV	Main findings and limitations
*Berger, Jonah and Schwartz, Eric M. (2011* Berger, J., & Schwartz, E. M. (2011). What drives immediate and ongoing word of mouth. Journal of Marketing Research, 48(5), 869-880. ) Journal of Marketing Research	Three studies: About 2,000 volunteers, who received product and gift information, reporting recommendations. 1,687 volunteers, marketing campaigns sent by e-mail. Study with 120 volunteers, through short conversation with stimuli.	Measures the level of recommendation, considering: Product interest level; Accessibility / visibility, tips, promotional gifts.	N/A	N/A	Accessibility forms WOM. Public visibility and tips influence what people talk about. Not always the most interesting products are discussed. It lacks the investigation of the actual gain of WOM in sales and result, as well as the quality and duration of WOM.
*Hidalgo, Pedro, Manzur, Enrique, Olavarrieta, Sergio and Farías, Pablo (2007* Hidalgo, P., Manzur, E., Olavarrieta, S., & Farías, P. (2008). Customer retention and price matching: The AFPs case. Journal of Business Research, 61(6), 691-696. ) Journal of Business Research	Chilean firms with CLV calculation, based on public data of large corporations.	N/A	Measures CLV considering: Fees paid by the customer, less operating expenses. Retention rate based on the % of clients who remain in the company after 1 year. Employs discount rate of 12%.	N/A	For industry with low level of brand differentiation and low level of customer involvement, seeking cheaper competitor prices reduces CLV and, consequently, stimulates marketing investment. Suggests that future studies should take into account (i) consumer behavior in the after sales, (ii) design of services that are important to the customer, and (iii) investment in sales force, gifts, marketing efforts, etc.
*Chang, Chun-Wei and Ijose,Olumide (2016* Chang, C.-W., & Ijose, O. (2016). Measuring customer lifetime value: An application in credit card industry. Journal of Business Research, 1, 7-24 ) Journal of Business Research	4,675 Taiwan’s large bank customers, with 224,112 transactions (January 2011 to January 2013). demographic data (age, income, occupation, ZIP code, family size and marital status); and Transaction data (purchase value, location and store name and purchase date).	N/A	CLV Calculation considering 4 components: Expenses expectation; Marketing expenses; Retention rate; and Discount rate.	N/A	Creates 4 customer profiles, not only considering CLV but also Current Value (Most Valuable Customers, Potentialities, Loyalty Crisis and Less Valuable Customers). It seeks to guide paths for the treatment of each identified profiles. As an evolution in future studies, individualized retention rates can be sought, instead of a constant retention rate. One can aggregate additional information about marketing actions, interactions and etc., seeking the impact of these actions in CLV.
*Persson, Andreas (2013* Persson, A. (2013). Profitable customer management: Reducing costs by influencing customer behaviour. European Journal of Marketing, 47(5-6), 857-876. ) European Journal of Marketing	Qualitative method, with analysis of 3 large banks. Interviews with 4 to 6 employees. Information of action costs and behavior change results captured, evaluating effects on CLV and ROI.	N/A	Seeks to expand CLV measured result through cost reduction, based on strategies to adapt the customer’s behavior	N/A	Companies that identify sources of high costs related to their customers can derive substantial benefits in reducing these costs regardless of the customer’s profitability. Case studies show that changes in customer behavior reduce costs, maintaining or even increasing retention and margin measured by CLV. As a future evolution, it should expand the number of evaluated cases, expand to other industries and with a longer term to analyze the results. Suggests future research to carry out longitudinal study to measure the long-term effects on CLV.
*Kumar, V. and Reinartz, Werner (2016* Kumar, V., & Reinartz, W. (2016). Creating enduring customer value. Journal of Marketing, 80(6), 36-68. ) Journal of Marketing	Extensive literature review related to relationship marketing and CLV, using empirical studies of several authors.	N/A	Extensive literature review related to CLV, considering use and introduction form.	N/A	Enjoys vision of Value for the Customer and Customer Value. When analyzing Value for the Customer, it defines the concept of Perceived Value by the client, which can be measured by objective attributes or perceived attributes. When it addresses Customer Value, it uses CLV as an index that measures the present value of a customer, according to future purchases, considering revenues, expenses and behavior. It adds the idea of strategy based on CLV, also used for acquisition, retention and recovery. It brings the view that the Customer Value comes not only from the financial value of their purchases, but also from their influence on other consumers.
V. *Kumar, J. Andrew Petersen, & Robert P. Leone (2010* Kumar, V., Petersen, J. A., & Leone, R. P. (2010). Driving profitability by encouraging customer referrals: Who, when, and how. Journal of Marketing, 74(5), 1-17. ) Journal of Marketing	Four studies: Financial companies, including a direct marketing campaign for a sample of 300 clients, out of a total of 14,160 clients. Sample of 600 clients, from the same company, considering total residual of 13,860 customers. Sample (6,700) and control group (6,560) of the residual sample, discounting the two previous groups (13,260). Retail company and sample of 40,000 customers, collected from 2005 to 2007.	N/A	CLV calculation considering, in a certain period: Client’s expenses expectation; Marketing expenses; and Discount rate.	CRV calculation, considering: Recommendation time; Number of recommendations in the period and margin contribution (excluding margin already existing); Cost acquisition saving in case of customer coming from recommendation.	The article shows how to quantify the incremental results in the marketing strategies guided according to CLV and CRV; It empirically illustrates how to determine a set of CRV behavioral drivers, using data from a retail company to drive marketing campaigns more efficiently, as well as opportunities to leverage CRV. As limitations, CRV may not apply to all industries. Not all companies will have the capability and systems to maintain the CRV. CRV works well in a more stable environment.
*Valenzuela, Leslier, Torres, Eduardo, Hidalgo, Pedro e Farías, Pablo (2013* Valenzuela, L., Torres, E., Hidalgo, P., & Farías, P. (2014). Salesperson CLV orientation’s effect on performance. Journal of Business Research, 67(4), 550-557. ) Journal of Business Research	Sales force of a large Chilean retail bank, sending 150 questionnaires (measuring 207 items). Response was 132 questionnaires (88% rate of return).	N/A	It does not calculate CLV directly, but the effect of a CLV-oriented sales force on sales force result.	N/A	Study shows that there is a positive relationship between sales force oriented CLV and its performance. CLV-oriented sales force behavior is important in building the value of customers and the company. As main limitation, self-reported CLV by a single respondent, when the ideal would be to collect information from varied sources.
This study	A random sample of 768 clients of a Brazilian financial institution, followed by three steps: Capture of satisfaction and recommendation indexes; Mapping the recommendation behavior; and Effective acquisitions on those who claim to recommend.	Captured in the survey, through the recommendation question. A question was created that sought to identify effective recommendation, by respondents indicating names who received recommendations and cross-referencing with firms records to identify effective purchase.	Adds to the existing CLV, by seeking to simplify the calculation and making it applicable to most firms, considering as main variables: Potential future revenue, according to product ownership and accumulated balance; Survival rate, measuring the likelihood of customer retention.	Adds to the existing CRV measure. The CRV is composed of the value coming from the recommendations of the clients, being the sum of the CLVs of all the nominee individuals.	Through the CLV and CRV, the study generates inputs and recommendations for firms seeking to expand sales through WOM, tracking performance not only for the value-added individually by the customer (CLV) but also the value of the clients indicated by him (CRV). In developing criteria for measuring the recommendation (measurement index is little explored academically) a study generates practical index, which can be created and administered by many corporations. There are opportunities for future studies, such as expansion of the study for companies in other industries, looking for possible specific adaptations.

Variable	Description
CRV	Customer Referral Value (CRV), calculated for each respondent customer with valid referral names (Logarithm)
Recommendation	Score given for the recommendation question (0-10) (Standardized)
CLV	Customer Lifetime Value (CLV), calculated for each customer (Logarithm)
Plan balance	Value of the accumulated reserve balance in the plan (in $) (Logarithm)
Satisfaction	Score given for the satisfaction question (0-10) (Standardized)
Age	Customer age (in years) (Standardized)
Gender	Gender of the customer (Female 0 and Male 1)
Potential	Customer potential based on the segmentation strategy. Three classes: (3) AB, (2) C, and (1) DE
Marital status	Marital status of the customer (Married 1 and Single 0)
Region	GDP per capita of national regions
Graduate	Customer education (Graduate 1 and Others 0)
Plan type	Type of customer plan (VGBL 1 and PGBL or Traditional 0)
Tax option	Tax option chosen by the customer, (Regressive 1 and Progressive or Traditional 0)
Underage	Pension plan ownership for those underage (No 0 and 1 Yes)
Tenure	Since first product purchase (in months) (Standardized)
Recency	Time since the last contribution to the plan (in months) (Standardized)

Variable	(1)	(2)	(3)	(4)	(5)	(6)	(7)	(8)
CRV (1)	1
Recomendations (2)	0,051	1
CLV (3)	0,016	-0,036	1
Balance (4)	0,008	-0,040	0,811	1
Satisfaction (5)	0,051	0,696	-0,054	-0,038	1
Age (6)	-0,008	-0,042	0,296	0,368	-0,010	1
Time (7)	0,065	-0,081	0,050	0,061	-0,072	0,059	1
Recency (8)	0,032	-0,035	0,024	0,045	-0,009	0,089	-0,016	1
Mean	151,21	8,20	2139,46	54812,84	7,94	47,64	82,83	10,69
Standarddeviation	1690,18	2,47	4787,09	133653,94	2,00	13,49	59,17	53,66

Variables	Hipothesis	CRV (Customer Referral Value)
Variables	Hipothesis	Model 1	Model 2	Model 3
Independet Variables
Customer Lifetime Value (CLV)	H₁	-,37 (-2,6)**	-,39 (-2,95)***	,35 (-2,68)***
CLV²	H₁	,05 (2,50)**	,05 (3,04)***	,04 (2,76)***
Control Variables
Recomendation		-66 (-2,39)**	-,69 (-2,61)**	-,73(2,77)***
Satisfaction		-,57 (-3,73)***	-,55 (-3,73)***	-,54 (-3,65)***
Age		-,21 (-1,76)*	-1,7 (-1,57)
Gender		1,06 (6,07)***	1,08 (6,29)***	1,12 (6,58)***
Potential		,31 (2,61)**	,30 (2,66)***	,23 (2,20 )**
Marital Status		-38 (-1,91)*	-,36 (-1,87)*	-,47 (-2,54)**
Region		-,12 (-2,47)**	-,12 (2,60)**	-,12 (-2,71)***
Graduate		-,05 (-,25)
Plan Type		,49 (2,28)**	,49 (2,33)**	,46 (2,22)**
Tax Option		-,14 (-,76)
Underage		-,87 (-3,33)***	-,95 (-4,86)***	-,96(-4,86)***
Tenure		,23 (2,02)**	,25 (2,50)**	,25 (2,53)**
Recency		,57 (2,31)**	,55 (2,29)**	,46 (1,96)*
Plan Balance		,22 (,62)
Constant		5,75 (12,42)***	5,66 (13,70)***	5,88 (15,04)***
R²		0,69	0,69	0,68
Adjusted R²		0,64	0,65	0,64
F-statistic		12,06**	16,16**	17,05**
Observations		109	109	109

Variables	Hipotheses	Recommendation
Variables	Hipotheses	Model 1	Model 2	Model 3	Model 4
Independentes Variables
Plan Balance	H₂	-,00 (-,03)	-,00 (-,02)	-0,1 (-,15)	-,03 (-,65)
Customer Lifetime Value (CLV)	H₃	-,01 (-,26)	-,01 (-,28)	-0,1 (-2,21)**	-,03 (-1,72)*
CLV²		-,00 (-,25)	-,00 (-,23)
Control Variables
Satisfaction		,29(13,09)***	,29(13,12)***	,29 (13,21)***	,29 (13,63)***
Age		,01 (,54)	,01 (,55)
Gender		-,07 (-2,07)**	-,07 (-2,10)**	-,07 (-2,18)**	-,07 (-2,37)**
Potential		-,04 (1,79)*	-,04 (-1,80)*	-,04 (-1,97)**	-,04 (-2,13)**
Marital Status		,00 (,02)
Graduate		-,07 (-1,65)*	-,06 (-1,64)	-,06 (-1,67)
Plan Type		,08 (2,05)**	,08 (2,07)**	,08 (2,00)**	,06 (1,83)*
Tax Option		-,03 (-,90)	-,03 (-,90)
Underage		-,01 (-,02)	-,00 (,13)
Tenure		-,02 (-,1,17)	,00 (,13)
Recency		-,03 (-1,80)*	-,03 (-1,80)*	-,03 (-1,86)*	-,02 (-1,76)*
Constant		,50 (8,04)***	,50 (8,11)***	,50 (8,51)***	,40 (8,64)***
R²		0,29	0,29	0,29	0,28
Adjusted R²		0,27	0,27	0,27	0,27
F-statistic		14,23***	16,48***	21,41***	29,92***
Observações		553	553	553	553

[1] Responsible editor: Prof. Dr. Susana Costa e Silva

Brasil

Brasil

The influence of customer value on word of mouth: a study of the financial services company in Brazil

Abstract

Purpose:

Design/methodology/approach:

Findings:

Originality/value: