Volume 8 (2022-23)

Each volume of Applied Marketing Analytics consists of FOUR 100-page issues, published in print and online.

The Articles published in Volume 8 include:

Volume 8 Number 4

Editorial
Barry Keating, University of Notre Dame
Practice papers
What’s the story with marketers and data storytelling? An educator’s perspective
Jonathan Copulsky, Senior Lecturer of Marketing and Academic Director, Business Marketing Strategy, Northwestern University

Fuelled by digital technologies, marketers now have more access to data than they ever thought possible. At the same time, tools for analysing this data have become easier to use and more powerful. But more data and better tools have not always led to greater value. This paper discusses why better storytelling skills may help marketers ‘crack the code’ in delivering more value from data and analytical tools, argues that data storytelling is a teachable skill that all marketers need to learn and master and discusses what lessons were learned in training graduate marketing students in data storytelling skills.
Keywords: data storytelling; data visualisation; marketing analytics; marketing training; marketing skills; presentation skills; data narratives
Upper funnel ad effectiveness and seasonality in consumer durable goods
Vivian Qin, Senior Data Scientist and Koen Pauwels, Principal Research Scientist, Amazon Ads

Brands usually invest in a portfolio of ad products for brand consideration and conversion. To gauge performance, brands often use ad-attributed metrics to compare return on advertising spend (ROAS) across different ad channels. There are two shortcomings with this approach. First, it relies on a predetermined attribution window (eg 1 day, 14 days, 30 days).1 The resulting ROAS does not only favour lower funnel ads, such as paid search, but could change with different attribution models. Secondly, attributed performance metrics usually do not consider seasonality, and organic consumer demand changes over the course of the year, which could bias the estimates of the effectiveness of ads. This could result in mistakenly attributing high organic demand to campaign performance. These issues are addressed with a seasonal autoregressive integrated moving average with x/exogenous variables (SARIMAX) model, accounting for seasonality and brands' past performance. This analysis compares ad efficacy on total retail metrics, regardless of attribution methods. This method is applied to Amazon Ads for 15 brands in US consumer durables. While the lower-funnel ad product (Sponsored Products) sees a lot more current usage, higher-funnel ad products such as Sponsored Brands, demand side platform (DSP) display, and Streaming TV Video are all found to have higher efficacy. Brands should evaluate their ad-product performance at regular intervals to avoid under-utilising high-performing ad products. Future research is also encouraged to replicate this methodology in different verticals and locales for generalisability.
Keywords: digital advertising; marketing analytics; time series model; Amazon Ads; consumer durables; brands; ROAS
How brand mentions in television advertising affect consumer attention, recall and evaluation
Mark Vroegrijk, Specialist Data, Science and Analytics, DVJ Insights

One of the critical success factors of any television commercial lies in the extent to which consumers can correctly link it to the advertising brand. While several studies have underlined the importance of (frequently) mentioning the brand's name to foster such brand linkage, they generally have not accounted for consumers' intrinsic tendency to avoid advertising. Because many consumers divert their attention from a commercial before its end is reached, not every brand mention is going to be observed by everyone, which may severely hamper their impact. In fact, prior academic work has shown that these brand mentions themselves may form an (additional) trigger to skip a commercial prematurely. The current paper brings both literature streams together and models the impact of different types of within-ad brand mentions on 1) consumers' second-by-second decision to skip a commercial or keep watching, and 2) their subsequent ability to recall the brand — conditional on what elements of the commercial they could and could not observe. In addition, as determining the optimal number of brand mentions implies that the right balance needs to be struck between their positive (recall) and negative (loss-of-audience) effects, further input for this decision is provided by also analysing how consumers' opinions and attitudes towards a commercial are affected by in-ad branding. The findings demonstrate that even with just a few second-long brand mentions within a commercial, a better performance in terms of viewer attention and brand recall is achieved compared to having a brand watermark for the commercial's entire duration. It was also concluded that a high number of (aural) brand mentions is better suited to more rational, ‘sales activation’ commercials, while a low number of (visual) brand mentions is preferred for more emotional, ‘brand-building’ commercials.
Keywords: television advertising; brand cues; brand watermarks; advertising avoidance; consumer memory; attitude-towards-the-ad
Research papers
A regional comparison of the skills sought by employers for entry-level data scientists, data analytics, business analytics, marketing analytics and digital analytics professionals
Angela D’Auria Stanton, Professor of Marketing and Wilbur W. Stanton, Professor of Marketing, Radford University

Fact-based decision making is changing job functions within organisations more than any other technology. Analytics, once the purview of the data scientist, is now spread throughout organisations. No longer is there a single job title, job function or set of required skills and credentials for an analytics career. Companies now recruit analytics talent based on required skill sets. Part 1 of this research1 focused on a cross-region comparison of the demand and employer requirements in job ads posted on LinkedIn for entry-level marketing analytics professionals. In Part 1, the authors reviewed the skills employers seek when hiring entry-level marketing analytics professionals in three geographic regions. The authors presented evidence of the growth in marketing analytics worldwide and how it has become a global phenomenon. Using job postings scraped from LinkedIn, Part 1 of the study extended previous research by focusing only on entry-level marketing analytics professionals' skills, knowledge and abilities in the United States, the United Kingdom and the European Union. The authors presented findings across the three regions, clearly noting where distinct differences were identified in job postings by employers seeking entry-level marketing analytics professionals. Finally, the authors provided emerging and creative methods for recruiting analytics talent in a very complex and dynamically changing environment. This paper, Part 2 of the research project, focuses on a cross-region comparison of demand and employer requirements in job ads posted on LinkedIn for entry-level data scientist, data analytics, business analytics, marketing analytics and digital analytics professionals. The authors examined the similarities and differences in employer expectations by region across requirements for hard skills, soft skills, software skills and credentials.
Keywords: analytics professionals; job requirements; United States; European Union; United Kingdom
Modelling the influence of teenagers’ shopping motivation on their intention to purchase sports merchandise: A perspective from an emerging economy
Sahil Gupta, Associate Professor, Jaipuria School of Business, et al.

This study has focused on analysing the factors influencing the shopping motivation of teenagers in relation to their intention to purchase licensed sports merchandise. It has particularly focused on understanding the impact of shopping motivation, brand image, sports celebrity, personal values and team identification on the purchasing intentions of teenagers. After building upon the theoretical framework of the various constructs, the relationship has been analysed through structured equation modelling that has helped to reveal the influence of these factors on buying intention. The results show a positive relationship between the variables and purchase intentions for sports merchandise. The results would provide meaningful and relevant input for developing marketing and branding strategies to attract teenage consumers to buy sports merchandise associated with various teams in a sporting event. As the variables are interconnected, a better marketing strategy with effective communication would help in delivering the right outcomes for young consumers.
Keywords: teenagers; shopping motivations; sports merchandise; purchase intentions
Customer loyalty in the insurance industry: From traditional to analytical marketing — a bibliometric analysis
Manuel Leiria, Nelson deMatos and Efi génio Rebelo, School of Economics, University of Algarve

This study describes the conceptual structure of customer loyalty in insurance through a bibliometric analysis and identifies the emerging industry and research trends. A total of 98 scientific documents published about customer loyalty in insurance are examined using two bibliometric software programs, VOSviewer and SciMAT, that allow the spatial representation of the research concept. Both descriptive and network analysis are produced in this research. The paper highlights the importance of customer loyalty to successfully compete in the insurance industry and identifies good practices that insurance companies should adopt. The analysis of research trends highlights the importance of statistical models and algorithms to anticipate customer decisions. This is the first comprehensive article offering a bibliometric analysis to research the main trends on customer loyalty in insurance.
Keywords: loyalty; insurance industry; customer loyalty; bibliometric analysis; thematic analysis; research propositions; VOSviewer; SciMAT
Exploring the factors of social media communication and their impact on online corporate brand image
Talvinder Kaur, Research Scholar and PhD Candidate and Sarbjit Singh Bedi, Associate Professor, Dr B. R. Ambedkar National Institute of Technology

In the past two decades, social media has transformed the way marketers communicate with their customers. Customers have moved from traditional media to new media to gather information. The purpose of this paper is to explore the factors of social media communication and its impact on online corporate brand image. The descriptive study uses exploratory factor analysis (EFA) and stepwise regression on data collected from 651 social media users. The study extracted three factors in firm-created content and two factors in user-generated content. Further, the study showed that social media interactivity and user comments have the strongest impact on the online brand image of any company.
Keywords: social media communication; firm-created social media; user-generated social media; online corporate brand image; branding

Volume 8 Number 3

Special Issue: Innovative Methods to Measure Digital Marketing Analytics: Part 2

Guest Editors: Ana Reyes-Menendez and Nuria Ruiz-Lacaci, Rey Juan Carlos University, and Pedro Palos-Sanchez, University of Seville

Editorial: Innovative methods to measure digital marketing analytics: Part 2
Ana Reyes-Menendez and Nuria Ruiz-Lacaci, Rey Juan Carlos University, and Pedro Palos-Sanchez, University of Seville
Research papers
Marketing performance measurement: A model of organisational and behavioural factors
António Pimenta da Gama, Universidade Europeia, IADE, Faculdade de Design, Tecnologia e Comunicação, UNIDCOM/IADE, Unidade de Investigação em Design e Comunicação

Performance measurement and analysis has been a major concern in marketing and remains a vital issue in many companies. However, specialised literature has devoted much more attention to the choice of metrics to be used than to the identification and description of mechanisms through which the effectiveness of the process can be improved. These mechanisms are more managerial than technical in nature and include the set of rules, policies and structures allowing management to ensure that strategies are in place and objectives are monitored and achieved. When deployed, they assist in coordinating activities and aligning interests to maximise the value of measurement. Addressing the preceding topic, this work proposes a theory-based model aimed at helping professionals to overcome some of the internal barriers that hamper the design and proper functioning of a marketing performance evaluation system. The model is composed of six organisational and behavioural factors: marketing strategy, marketing capabilities, organisational context, measurement focus, measurement integration and interactivity, and organisational structure.
Keywords: marketing performance; marketing strategy; marketing capabilities; organisational context; measurement focus; measurement integration and interactivity; organisational structure
How eye tracking can predict consumer behaviour preferences on mobile devices
Ana Reyes-Menéndez, Assistant Professor, Rey Juan Carlos University, Pavel Žiaran, Faculty of Business Economics, Mendel University in Brno, Rebeca Antolín-Prieto, Associate Professor and Nuria Ruiz-Lacaci, Marketing Professor, Rey Juan Carlos University

The use of mobile devices and scope of multimedia tools is growing rapidly, which evokes the need to search for new approaches in the field of human–computer–mobile interactions. The objective of this paper is to test how appropriate eye-tracking technologies are for answering mobile questionnaires in the context of human–mobile interaction and consumer behaviour management. This research studies the possibility of answering screen-based questionnaires simply by looking at the question items using a mobile device in comparison to the classical online questionnaire in which the user needs to click the answers. We compared the data from the eye-tracking (implicit questionnaire — question items are simply placed on the screen without scale) and the classical screen-based questionnaire with continuous scale (explicit questionnaire). Data were processed on a biometric software platform. This research could have a broad range of implications in the multimedia and mobile industry, with both scientific and commercial applications. This research opens new avenues for further research into every interaction between mobile users and mobile websites and apps that substitute traditional online interactions with biometrics.
Keywords: eye tracking; mobile questionnaire; questionnaire; HCI; mobile interaction; mobile devices
The voice era: Future acceptance of digital voice assistants and how they will transform consumers' online purchasing behaviour
Niko Muñoz and Bianca A. Kremer, ESCP Business School, Madrid Campus

Digital voice assistants (DVAs), such as Amazon Alexa, are causing upheaval in the marketplace due to their enormous potential in e-commerce. Despite this potential, because this technology is cutting edge, there remains a lack of insight into the main drivers of DVA use in e-commerce and voice-commerce (v-commerce). Drawing on theoretical foundations, such as the technology acceptance model (TAM) and the ‘unified theory of acceptance and use of technology’ (UTAUT), this study aims to explore the key determinants behind the use of DVAs. Specifically, it proposes ten hypotheses that are tested with quantitative data obtained through an online survey from a diverse sample of 315 participants in several countries. Regression analysis was employed to identify eight factors that will have an influence on the future acceptance of v-commerce, in which trust, social influence and hedonic motivation have the greatest effect. Since v-commerce is still relatively unknown to consumers, the focus of any strategy should include confidence-building, enjoyable and motivating activities and social programmes. Companies should be transparent about the data they plan to collect and process and give consumers options as to how they can get informed and address perceived privacy concerns. This would enable DVA manufacturers to speed up consumer adoption of a new technology that has been around for some years but has still not become mainstream. Brands should keep up to date with these technologies and start experimenting and partnering with DVA vendors, such as Amazon, Google or Apple, by selling utilitarian and low-involvement products and services.
Keywords: digital voice assistants; voice commerce; TAM; UTAUT; technology acceptance; SPSS; quantitative survey; multiple regression analysis; correlation
Knowing the levers to pull to measure and optimise digital marketing performance
Emma Lo Russo, Chief Executive Officer, Digivizer Pty Ltd

Digital marketing is now pre-eminent across brand building, business development, marketing and selling. Today's digital natives are researching, engaging and buying online, in business to business (B2B) and business to consumer (B2C), across every vertical market. This creates new opportunities for marketers. But to maximise the returns on their efforts and investment, they need to understand and optimise the performance of their digital marketing programmes in the face of fierce competition for the eyes and attention of customers and prospects, and for the best possible position in search returns. This effort starts with knowing where customers and prospects are to be found, in the sense of understanding whether a cohort of names are real prospects or simply people being targeted by marketing programmes. This may seem a statement of the obvious, but work with clients and research indicate that it is less common than might at first be expected. There are also new challenges in being accountable for the results. Chief executive officers (CEOs), chief marketing officers (CMOs) and boards now understand that the data are there to be analysed at each level of investment across content, campaigns and targeting. They expect more from the budgets they spend on their marketing, and they expect everyone involved, not just a favoured few, to know what is going on. Marketers and business owners know they need to make sense of millions of pieces of data and do so without undue expense or delay. This can maximise the value of the data they have to hand. And to achieve this means they need to know which levers to pull in time to make a difference. This paper discusses techniques and approaches to measuring the performance of digital marketing programmes across multiple channels, addresses the dilemma of ever-increasing complexity and ever-increasing expectations, and presents possible solutions to the challenges around the accountability increasingly placed on marketers to prove their worth. It addresses the challenge of data biases and distinguishes between data — the raw material of digital marketing — and insights — what make the data useful. Case studies show how organisations use real-time data to test and experiment and to understand which levers to pull.
Keywords: marketing; digital; attribution; social media; search; data-driven; content marketing
A regional comparison of the skills sought by employers for entry-level marketing analytics professionals
Angela D'Auria Stanton, Professor of Marketing and Wilbur W. Stanton, Professor of Marketing, Department of Marketing, Radford University

This paper is Part 1 of a two-part project. This paper focuses on a cross-region comparison of the demand and employer requirements in job ads posted on LinkedIn for entry-level marketing analytics professionals. This paper comprehensively reviews the skills employers seek when hiring entry-level marketing analytics professionals in three geographic regions. The authors begin by providing a brief history and evolution of the growth in demand for analytics professionals. The authors then discuss the growth in demand for marketing analytics professionals. Next, the authors present the general skills and abilities desired by employers, followed by the evolution and challenges of hiring analytics professionals. The authors present evidence of the growth in marketing analytics worldwide and how it has become a global phenomenon. Using job postings scraped from LinkedIn, this study extends previous research by focusing only on entry-level marketing analytics professionals' skills, knowledge and abilities in the US, the UK and the EU. Content analysis of position descriptions and job requirements was used to determine the similarities and differences within the four broad skillset categories (hard skills, soft skills, software and credentials) in the three geographic areas. The authors present findings across the three regions, clearly identifying where distinct differences were identified in job postings by employers seeking entry-level marketing analytics professionals. The authors then offer an assessment of the challenges to organisations in recruiting employees with the skills desired. Finally, the authors provide emerging and creative methods for recruiting analytics talent in a very complex and dynamically changing environment. Part 2 of this research project will focus on a cross-region comparison of demand and employer requirements in job ads posted on LinkedIn for entry-level analytics professionals, specifically the phrases data scientist, data analytics, business analytics, marketing analytics and digital analytics. The authors will examine the similarities and differences in employer expectations by region.
Keywords: marketing analytics; digital analytics; job requirements; United States; European Union; United Kingdom
Integrating datasets: Segmenting the fashion market using risk aversion
Martin Paul Block, Professor Emeritus, Medill School of Journalism, Media, Integrated Marketing Communications, Northwestern University

A marketing segmentation can often be improved with the addition of variables which are often found on different datasets. Using a classification regression tree (CRT) methodology with predictor variables shared across datasets, the terminal node identification equations can be used to estimate the variables on a different dataset. The use of CRT allows the inclusion of categorical variables, such as marital status and ethnicity, as well as continuous variables, such as age and education. Three datasets were integrated and a chi-square automatic interaction detector (CHAID) tree is then used to segment the women's clothing fashion market by demographic and reward and aversion variables. The analysis suggests possible marketing strategies targeting high-spending segments as well as media strategies.
Keywords: data integration; fashion; segmentation; decision tree
Data-driven influencer marketing strategy analysis and prediction based on social media and Google Analytics data
Kristo Radion Purba, Assistant Professor, Department of Computer Science, University of Southampton Malaysia and Yee Jia Tan, Data Analyst, Department of Ambassador Development, MeCan App Sdn. Bhd

Due to various uncertainties on social media, data-driven strategy has become a necessity for influencer marketing. Typically, a promotional post by an influencer aims to direct the viewers to buy a product from a brand's website. The objective of this paper is to analyse the factors that contribute to the popularity of promotional posts in terms of likes and website visits count. This research utilised Facebook (FB), Instagram (IG) and Google Analytics (GA) data collected from the ambassadors (or influencers) of MeCan App, a Malaysian e-commerce company. The factors that contribute to popularity have been successfully identified, such as the optimal posting time, hashtags, image type, interval and ratio of posts. For example, they should post based on the ratio of one regular post for 5.4 promotional posts for the best exposure. Additionally, regression methods were implemented to predict website visit count, with an accuracy of 69.9 per cent using Random Forest Regressor.
Keywords: data analytics; machine learning; social media; e-commerce; marketing strategy
Book review
Marketing Metrics
Reviewed by Stewart Robbins,Senior Industry Consultant, Teradata

Volume 8 Number 2

Special Issue: Innovative methods to measure digital marketing analytics: Part 1

Guest Editors: Ana Reyes-Menendez and Nuria Ruiz-Lacaci, Rey Juan Carlos University, and Pedro Palos-Sanchez, University of Seville

Editorial: Innovative methods to measure digital marketing analytics: Part 1
Ana Reyes-Menendez and Nuria Ruiz-Lacaci, Rey Juan Carlos University, and Pedro Palos-Sanchez, University of Seville
Practice papers
How marketers can use the power of an AI/ML model to identify and predict customers
Shashi Bellamkonda, Adjunct Professor, Georgetown University

Marketers are increasingly faced with a lot of data and need to identify the best prospects. Sales teams are often sceptical of the data provided by marketing and possibly blame the quality of the prospect data provided by marketing. Enter a neutral party, a neural network, an AI/ML model that can analyse the current customers and provide a mechanism for identifying co-relations and similarities in larger prospect data and increase the efficiency of sales teams.
Keywords: marketing analytics, artificial intelligence, machine learning, data, modelling
How businesses of any size can use AI in a digital marketing strategy
Martin Broadhurst, Director, Broadhurst Digital Limited

In recent years it has been said that data is the new oil and marketing departments have never had much data to work with. At the same time, big tech companies are investing huge sums into artificial intelligence and machine learning (AI/ML) while making access to these tools easily available through cloud-computing services. This convergence of data abundance and easy access to AI/ML technology has created a huge opportunity for marketers to become more efficient and more effective through the use of AI. However, marketers are still struggling to take advantage of the opportunities presented by marketing AI technology due to a lack of knowledge within the profession. Organisations are educating marketing professionals through frameworks such as the 5Ps of Marketing AI to help identify use cases. The AI/ML marketing deployment matrix helps marketing professionals self-assess their organisation to better identify ways to utilise AI for their situation.
Keywords: artificial intelligence, AI/ML, marketing AI, AI framework
Web3 and the future of marketing
Kelly Cutler, Program Director and Faculty, Medill School, Northwestern University

The rise of Web3 and related regulations have brought data privacy concerns to the forefront for brands and marketers. With the rise in legislation, the deprecation of third-party cookies and an eye towards transparency, Web3 promises a more open, permissionless online environment. This has implications, from ad targeting to the storage and collection of user data. New concepts including zero-party data, micro-experiences and non-fungible tokens (NFTs) represent trends that are emerging with Web3, but the future is still to be defined. Marketers must understand the implications of the changing data privacy landscape and discover new and creative ways of sourcing and collecting data that follow the new guidelines that are being established by legislators, as well as by walled gardens such as Apple, Meta and Google. To do so, they will have to experiment and innovate. Here, we will explore the evolution of the web from its earliest version into the future. We will also review the different ways marketers currently collect and use customer data. Finally, we will explore new ways for brands and marketers to stay relevant in this evolving digital ecosystem with zero-party data, integrated marketing technology, customer-centric governance and NFTs.
Keywords: Web3, NFTs, blockchain, zero-party data, data privacy, walled gardens, digital marketing
C-3DP: A cross-cluster analysis model to identify latent categorical customer attributes
Roger Kamena, Lead Data Scientist and Head of Innovation and R&D, Adviso Conseil Inc.

Using two-dimensional clustering methods to segment a customer database is a popular practice. The advantage of two-dimensional clustering is the ability to map customers according to a well-defined business logic. For example, how many segments can be identified based on the customers’ age group and RFM score? Such an approach also has the advantage of reducing the dimensionality of datasets and a model’s training time. Conversely, the trade-off of clustering on two dimensions is to ignore all the other dimensions potentially available in a CRM or web analytics platform. As such, the qualitative traits analysis of each segment from available customer dimensions can be challenging, especially for categorical dimensions with higher cardinality. In order to maximise the customer insights derived from cluster analysis, the paper proposes a qualitative trait prevalence scoring system: the C-3DP index (categorical density, dominance and diversity prevalence index). This technique maps a subset of dominant qualitative segment traits using a simple algorithm, as opposed to relying solely on traditional descriptive analytics approaches.
Keywords: marketing segmentation, cluster analysis, machine learning, consumer insights
Attribution done right: How to prove the real value of marketing
Moni Oloyede, Director of Marketing Infrastructure, Fidelis Cybersecurity

Marketing attribution models are used by businesses to keep the marketing department accountable for the expenditure and the resources they use, as marketing is often seen as a cost centre within many organisations. Marketers implement marketing attribution models for two purposes. Firstly, to justify the money spent on marketing campaigns and activities, and secondly, to identify which marketing channels and tactics produce the desired results or outcomes. However, marketing departments continually struggle to use marketing attribution models to justify expenditure or show results. The most common reasons many marketers struggle to implement attribution models are issues with data integrity, lack of knowledge around how to effectively use marketing attribution tools and the sheer complexity of the buyer’s journey. In this paper, it is argued that the actual problem lies in how marketers perceive the use of attribution reporting. Furthermore, it is posited that those reasons are just symptoms of a larger problem with marketers’ approach to marketing attribution. If marketers want to use attribution successfully then they need to change the purpose of their attribution models to focus on customer metrics and not business outcomes. Nearly all marketing attribution focuses on return on investment as a desired outcome; however ROI is a business outcome, not a customer metric. Focusing on customer metrics such as brand awareness, brand engagement and churn rate will provide marketers with the informed outcomes they desire. The ability to gain insight from an attribution model comes from establishing the goal of the attribution model and then aligning the proper marketing metrics to the desired outcome.
Keywords: marketing technology, marketing automation, business analytics, marketing attribution, dashboards and reporting, omni channel marketing, digital marketing
Net searcher sentiment: A web-search based replacement for net promoter score
Isaac Gerber, Director, Commercial Insights and Analytics, Captify®

In 2003, Bain consultant Frederick Reichheld published an article in Harvard Business Review arguing that the best predictor of top-line growth can be captured in a single survey question: ‘Would you recommend this company to a friend?’ In the almost 20 years since, Reichheld’s question, referred to as net promoter score (NPS), has become a standard metric for many organisations, complementing and even replacing more comprehensive customer satisfaction surveys. Yet, just as Reichheld argued in 2003 that companies were measuring the wrong thing, NPS itself may be the wrong measure. As documented in recent literature, NPS captures self-reported attitudes versus behaviour, is prone to sampling bias and runs the risk of non-participation bias. This paper explores the creation of a new metric, net searcher sentiment (NSS), that replaces NPS’s reliance on survey data with aggregated search data. This paper lays out the benefits of NPS, its shortcomings as documented in the relevant literature, the methodology behind NSS, how it addresses the shortcomings of NPS, and provides two examples of NSS in action.
Keywords: net promoter score, brand measurement, growth, brand loyalty, search data, SEO, marketing
Empirical measurement of marketing analytics orientation: Quantifying the factors that create highly analytical marketing practices
Anthony F. Branda, Chief Data and Analytics Officer, ASB Bank Limited, Mark Weber, Research and Analytics Consultant, WellSpring Consulting, and Eduardo Lucio, Chapter Lead for Data Science, ASB Bank Limited

Marketing analytics involves use of data tools to quantify and monitor marketing performance (MP) to both optimise investments in marketing programmes and maximise customer interaction. Built on market orientation (MO) theories, this study establishes a construct and measure of marketing analytics orientation (MAO) to assess factors that predict MAO. A novel measure that provides empirical evidence of MAO and its relationship to MP is presented using data collected from a survey of company leadership and marketing analytics professionals in real-world businesses. The results demonstrate that people effectiveness and analytic skill sets mediate the relationship between MAO and MP. These findings describe a new tool that may help data scientists and business owners better understand the drivers of marketing analytics maturity, including the importance of professional analytics skills, top management support, data governance, the credibility of the analytics organisation, and the adoption of analytics within corporate culture.
Keywords: Marketing analytics orientation, marketing performance, marketing analytics, market orientation, data analytics governance, analytics adoption
Research paper
The impact of digital marketing on the performance of firms in Tunisia
Bechir Fridhi, Assistant Professor, College of Business Administration, Majmaah University

The objective of this study is to examine digital marketing in Tunisia and its benefits as a business model used by Tunisian businesses and to determine the influence of digital transformation on the performance of firms in Tunisia. In addition, the objective of our empirical survey is to define the capacities and skills essential to the success of a digital transformation. The study focused on: (1) establishing the extent to which digital marketing has been adopted by firms in Tunisia and (2) determining the influence of digital transformation on the open innovation performance of Tunisian firms. The result of the integration of technological power into the management of enterprises gives rise to a digitalisation that disrupts marketing strategies, significantly contributing to the creation of new business models. The results revealed that the use of digital marketing is significantly linked to three open innovation performance metrics: increased revenue, acquisition of new customers and retention of existing customers. This open innovation performance also has a positive and significant relationship with the use of digital channels by customers, showing that customers using digital channels in their purchasing process will tend to buy, consume and be more loyal than customers using the classic channels.
Keywords: digital marketing, digital transformation, partial least square (PLS) approach, open innovation performance
An explorative study of salient usability attributes affecting m-commerce consumer behaviour in a Nordic context
Lasse Baungård Løber, Assistant Professor, UCL University College, Denmark and Simon Svendsen, Analytics Translator, Danfoss A/S

M-commerce, or mobile commerce, refers to smartphone shopping and plays an increasingly large role within e-commerce. Past research in the field of information systems (IS) success has primarily consisted of quantitative studies. Little research has been conducted in an m-commerce context. Furthermore, few qualitative works on the intersection of success factors from firms’ perspective and m-commerce exist. In fact, there is a knowledge gap regarding how business practitioners can increase their website usability in an m-commerce setting. Based on the mapping of usability attributes by Kuan et al., which elaborates on DeLone and McLean’s IS Success Model, this paper aims to identify the most important website usability attributes by generating new insights about mobile consumers’ behaviour. This is obtained via a qualitative approach, using data about consumer behaviour on four Nordic m-commerce webshops within the baby products industry. Eight respondents completed a smartphone task while verbalising their thoughts. This data was supplemented with eye-tracking information. The theoretical model was operationalised via creating 19 codes corresponding to 19 usability attributes. As such, this paper took a deductive approach, coding the data in NVivo by tagging labels to categorical labels. Based on the number of references for each categorical label, three salient attributes were identified to increase m-commerce website usability: ‘ease of navigation’, ‘relevance’ and ‘effectiveness of product search and comparison’. The managerial implications include recommendations for these three attributes, including the use of categorisation and filtering systems, avoiding uncertainty and minimising the potential negative consequences related to the purchase intention and enabling on-page product and consumer product experience comparisons. While this study is based on a small data sample, and represents a minor exploration into a niche market, it nonetheless provides a starting point for business practitioners who have the goal of increasing usability in an m-commerce context.
Keywords: m-commerce, usability, information systems success, e-commerce, online shopping, user experience

Volume 8 Number 1

Editorial: Towards a theory of analytics and guidelines for practitioners
Marco Vriens, CEO, Kwantum Analytics
Practice papers
Unlocking the full potential of social listening platforms through prescriptive-based intelligence
Mike McGuirk, Lecturer, Babson College

Today’s business leaders are demanding access to information that will help them make more informed decisions. The widespread shift to customer-centric business practices, which require a much deeper understanding of consumer needs, emotions, and behaviours, is a primary driver of this heightened thirst for more data. This data obsession has triggered an unprecedented level of innovation in marketing technology. Particularly, innovation in platforms that can ingest and analyse new sources of consumer data. Social listening platforms are an important contributor to this new data collection and analytics ecosystem. This paper explores the adoption of social listening platforms and social analytics practices and details the distinct and highly valuable benefits these solutions can provide marketers and customer experience management executives.
Keywords: social listening, social analytics, customer analytics, marketing analytics, market research, marketing, customer experience
Customer lifetime value: How to find the right calculation and prediction approach
Shirley Coleman, Technical Director at NU Solve, Newcastle University, et al.

In this age of abundant data, there are special opportunities for companies to measure the value of their customers. Such analytical action can help inform business and marketing decisions. This article gives an overview of what is meant by customer lifetime value and describes four approaches to calculating its value. We compare the pros and cons of each approach and show how engaging with the measurement activity can be beneficial for your business. Finally, the article gives guidelines so that managers can decide which approach best fits their current situation.
Keywords: data science, statistical models, marketing decisions, data scientist, predictive modelling, machine learning, small business, SME
The three stages of workforce optimisation: Moving beyond the industry standard
Dakota Crisp, Data Scientist, RXA, et al.

Erlang-C has long been the industry standard for call centre staffing. As call centres evolve and staffing concerns move to other industries, the standard methods don’t always work as expected. While traditional scheduling methods focused on translating historic demand into staffing needs, the estimation of demand and the logistics of scheduling employees have not always been equally considered. Through the analysis of multiple use cases from distinct industries, this approach evaluates all three stages of workforce optimisation and explores the gap between theory and reality.
Keywords: optimisation, staffing, call centres, ensemble learning, Erlang-C, automotive, forecasting
The intuition behind machine learning in marketing: Linear TV attribution
Mario Vinasco, Director BI and Analytics, Credit Sesame

Linear or broadcast TV continues to be an important channel for lead generation and user acquisition but precise attribution to an ad is not possible; attribution methodologies include time-based windows, keyword search within those windows, pixels that fire within the same Wi-Fi, panels, etc. This paper describes a forecasting methodology that uses machine learning to analyse recent and historical time series of new user registrations as well as additional factors and variables that affect new user acquisition. We then use this forecast to construct a baseline of expected new user volumes and how we attribute new users above that baseline to TV.
Keywords: Marketing analytics, forecasting, linear TV
Should you change your ad messaging or execution? It depends on brand age
Koen Pauwels, Distinguished Professor of Marketing, Northeastern University, Adjunct Professor, BI Norwegian Business School, et al.

Should advertisers change their message (what is said), just as they do the execution (how it is said) to reflect changing consumer preferences? This paper is the first to quantify how these ad components and their interplay affect brand sales. The authors define the concepts of market consistency and changes in ad executions and show how they interact with each other and with the brand’s age in their sales outcome. The empirical analysis confirms the hypotheses in the US minivan market. As a brand matures, executional variations become increasingly beneficial, but changing advertising messaging to remain consistent with customer preferences becomes less effective. For older brands with little executional variation, changing the ad message even reduces sales. The authors thus uncover important boundary conditions for the opposing theories that brands should ‘stick with their message’ versus ‘change with the times’ and advise how to manage advertising as the brand matures.
Keywords: advertising, advertising messages and execution, brand management, brand maturity, Hausman-Taylor regression
The culture and leadership style combination that cultivates a best-in-class marketing organisation
Laura Patterson, President, VisionEdge Marketing, Rita Egeland, Adjunct Marketing Professor and Kathleen Wong, Graduate Student, University of Texas at Dallas

The 2021-2022 Marketing Organisation Value and Performance Management (MPM) Benchmark Study is the continuation of a longitudinal study that began in 2001. The purpose of the study is to gain insights into which high performing best-in-class (BIC) marketing organisations do better and differently from their peers to earn high marks from a randomly selected group of C-Suite executives. These executives assessed Marketing on its ability to measure and communicate its value, impact and contribution to the business. The 2021-2022 study focused on gaining insight into whether organisational culture and/or leadership style are factors that contribute to the emergence and success of BIC marketing organisations. The study addressed three C-Level questions: 1) Is there any relationship between organisational culture and/or leadership style and marketing organisations who excel at performance management? 2) If so, is there an optimum culture or leadership style combination? 3) What do marketing organisations, classified as Value Creators, do differently in terms of turning data into insights, performance measurement and reporting, and processes? Based on the findings, the report identifies what business and marketing leaders can do to cultivate a Value Creator marketing organisation.
Keywords: Marketing performance management, performance management, marketing effectiveness, marketing accountability, marketing measurement, marketing metrics, MPM, marketing analytics, organisational culture, leadership styles
Why multi-disciplinary, cross-silo teams are best at analysing and actioning data collected along the customer journey
Victoria Jenner, Head of Customer Insights & Analytics, Harrods, et al.

Enter 2021, 90 years since the famous McElroy ‘Brand Men’ memo also marked the start of the shift of ‘brand activities’ from advertising to full ownership of everything needed to produce business results: ‘Where brand development is heavy and where it is progressing, examine carefully the combination of effort that seems to be clicking and try to apply this same treatment to other territories that are comparable.’ The explosion of sales and marketing channels since has spawned a plethora of marketing specialisms and seen businesses come almost full circle, with marketing departments focusing solely on incremental growth and campaign ROI, sometimes at risk of losing control of core activities. The pandemic of the last two years has accelerated the growth and importance of digital media and sales channels – another typically siloed team – in how customers research, consider and buy. Change is not only taking place in more obvious consumer markets, but also in B2B, where both customers and suppliers have been forced to move more of sales and service processes online. This is delivering surprisingly positive outcomes in many cases, with McKinsey’s research showing that buyers and sellers alike prefer the new digital reality. As the need to connect ‘base nurturing’ activities (which tend to be owned by sales departments) and ‘growth activities’ (usually led by marketers) becomes clearer and as the digitalisation of both sale and marketing becomes more mainstream, we are seeing the re-birth of the ownership of ‘line of sight to results’ across functional silos. This is happening with the creation of roles such as Chief Growth Officer, Chief Customer Officer and new-style CMOs or CSOs who take a data-first approach and tend to look further than their own discipline along the entire value chain for the customer. This hybrid position bridges traditional departmental silos such as business development, sales, marketing, operations, customer support and information technology. While those organisations are striving to understand their customers’ omni-channel journeys and add value all the way across this complex ecosystem of interactions, some historical models of analysis may no longer be able to cope with today’s cross-silo, omni-channel reality that requires end-to-end insights for many teams across the business. In this article we examine various useful, relevant, data science based approaches on which modern executives can rely to understand this new interconnected reality, allowing them to understand, nurture and grow their customer relationships, even in times of uncertainty and rapid change. We use examples of how traditionally marketing department-led activities such as customer segmentation and marketing investment analysis can evolve into a more cross-functional approach delivering better insights and, importantly, more value to the business.
Keywords: data-science approaches, customer relationships, customer segmentation, marketing
Research paper
How to choose the right influencer for a marketing strategy
Aslı Diyadin Lenger, Assistant Professor of Business Administration, Istanbul Gelisim University

This paper attempts to build a new model for deciding which social media influencers (SMIs) are suitable for the marketing strategies of businesses. How to choose social media influencers is an unanswered question in the literature, and this study attempts to fill this gap. The study employs a Multiple-Criteria Decision-Making (MCDM) method, the fuzzy decision-making trial and evaluation laboratory model (DEMATEL), to determine the relevance of criteria constructed. It observed SMIs on Instagram and reviewed insights from the literature. Five criteria are proposed for selecting the correct influencers: 1) positioning; 2) target; 3) budget; 4) past campaigns; and 5) the number of followers. Businesses were asked to evaluate these criteria according to their experience with using SMIs. The results suggest that the most important criterion is ‘target’, whereas ‘past campaigns’ is the least influential.
Keywords: Influencer, marketing, social media influencers (SMIs), fuzzy DEMATEL, fuzzy logic