Fusing multiple data sources to enhance the efficiency for retail targeting Harshvardhan Sarda and Hendrik Van Blerk
With the growth of informal trade in South Africa, manufacturers are increasing looking at developing distribution models that enable them to reach the informal trader in the most efficient manner, to ensure availability of their products in key retail hotspots. The current distribution model in the country is a wholesale led model, with most manufacturers having limited control over the last mile of distribution in the country. This results in skewed distribution structure, impacting consistency of brand availability in the in-formal markets. Our belief is that the wholesale approach is driven by both resourcing around reaching these outlets as well accurate knowledge of the location of the informal retail hotspots in the country. The focus of our paper would be to put forward an approach around enumerating retail outlets in the country which helps to identify high concentration of retail outlets, without having to undergo a full retail enumeration exercise.
Through an expanding array of data collection methods, most research companies have a large inventory of unused data. This presentation will detail one method used to gain different insights from previously collected syndicated data – specifically, viewing data from a spatial context.
As humans, we ‘think fast’ a lot more than we think slow. Due to technology, we are doing even more fast thinking and even less slow thinking than ever before. In ‘Blink’, Malcolm Gladwell discusses the power and pitfalls of fast, intuitive thinking “how, in many cases, our initial gut feelings can bring us closer to the truth than when are using slow, deliberative thinking and inundated with information. Daniel Kahnemans’ book introduced many marketers to Behavioural Economics: thinking, fast and slow. System 1 (representing fast, almost automatic thinking) and System 2 (representing slow deliberative thinking). Finally, Nicolas Carr’s ‘The Shallows’ investigates the impact that modern technology like the internet is having on our brains. In short, what he found is that the incidence of rapid or System 1 thinking is skyrocketing and we are, as a species, engaging in less and less deep, deliberative thinking, and this is literally and physically reshaping our brains. But are we reflecting this fact in market research? What kind of thinking do we typically encourage in market research in general? Thinking of the screening tools, most early stage screening tools force people into a slow, rational thinking mindset. For example, we show the test stimulus to respondents, ask them to look at it carefully, then rate it on key measures such as liking, relevance, uniqueness, purchase intent, etc. While these questions can be useful as providing a diagnostics, in the real world, people don’t generally think this way. And they certainly don’t purchase consumer packaged goods using this type of thinking. In reality, consumers typically make their decisions in just a few seconds. The approach illustrated in this case study takes consumers away from scaled responses, directly pitting items against each other in a series of contests that are fast and intuitive. In this case study, 20 claims were tested. consumers were shown a pair of claims and asked to indicate their preference, and the winners moved on until a final was chosen with new randomization in each round. From this exercise, we collected two variables. First we looked at the % time that a claim had won across all of their contests, which provided the preference of each claim. Second, in the background and unknown to respondents, we also collected their reaction time at the millisecond level. This data was collected at both the individual respondent level as well as the individual item level for every single contest. Then the preference data and reaction time were combined to calibrate a single metric to show the overall appeal of each claim and the claims were ranked accordingly.
A social segmentation model of the diverse and complex South African society with broader implications for the research industry Petrus de Kock, Jan Wegelin and Elsa Thirion-Venter
As a diverse nation, there are many attributes that shape and inform our behaviour daily, in very different ways. In a fast paced and dynamic society, South African citizens are exposed to continuous change. How are we influenced by these dynamics, and how does it shape our thoughts and actions? To develop deeper insight into the impact dynamics of change have on our society, Brand South Africa, African Response and MarkData embarked on a process of developing a tailored segmentation model of the South African society. As researchers, we are used to the broad segmentation profiles, or a combination thereof, such as race, age, gender and province which provide broad insights into different profiles of our society. But, essentially, these are tangible or genetic discriminatory principles. Added to this, we’ve seen the slow but definitive demise of the LSM segmentation model which has become less and less reliable and effective. To illustrate, LSM has no historical discriminatory component so whether one acquired a TV, for instance, fifteen years ago, it still counts as an indicator of living standards today. Furthermore, 80.8% of the South African society is classified as Black (StatsSA, 2017), is it acceptable or even reliable to consider or articulate that four out of five South Africans are in some or other way similar? The argument is not that race is void of any value as an identifier or indicator, but it should be used in the appropriate context and not stretched to reach specific behavioural or consumer conclusions. These types of segmentation strategies in a diverse and complex society with high unemployment, multi-linguistic and multi-cultural heritage, social grants and as one of the most urbanised countries in Africa (Edmunds, 2013) are simply not reliable enough to assume consistent behaviour across the basic tangible or genetic segmentation attributes. Added to the above are more complex notions such as racial integration, the need for economic growth and a more pronounced impact of education on society. With these influencers or challenges shaping the thoughts of South Africans daily, the segmentation debate has become more complex and intricate. For many years, different segmentation techniques have been developed and refined with the aim to define sub-parts of some total market (Claycamp and Massy, 1968). Some segmentation models are used globally, based on assumed universal truths of opinion or sentiment such as favourite or trusted, which in some cultures could be contradictory expressions when one is asked if a product or an entity can hold the same qualities as a person. From a different angle, quota samples are often used to research an identified group, which is essentially a predefined segment, and finding deeper engagement with that pocket of the population. The question remains, would it have been useful, in one of the most diverse and multi-cultural societies in the world, to first understand the population from a range of angles based on theoretical principles and then zoom in on each of the segments to identify behaviour, sentiment, intervention or communication strategies? Brand South Africa requires insights that transcend mere consumer behaviour based on broad segmentation practices. Thus, the segmentation model developed aims to encompass insight into attitudes, behaviours, and opinions regarding the South African Nation Brand as it manifests in the realms of politics and governance, business and economics as well as civil-society. In this paper, Brand South Africa, together with African Response and MarkData developed such a social segmentation model of the South African nation based on four constructs, National Identity, National Pride, Active Citizenship and Social Cohesion. These four constructs were explored theoretically and then used as a basis for segmenting society to evaluate a point-in-time assessment of the levels of integration, and how South Africans consider their role in society through anchor points. This paper is not so much about the findings of the research, but more about how it was developed and the implications of current and traditional research segmentation practices against a transition towards a more strategic research approach that continuously form the basis of future research to build a body of knowledge that informs and directs an understanding of the dynamics at play in any population or market.
Drastic times call for drastic measures: Uncovering market research buyers’ perspectives on the impact of privacy regulations on their operating environments Kudzai Guvi
As the pace of change continues to accelerate, market research has been saved by embracing new technologies and developing methodologies in line with the digital revolution. These new technologies and subsequent methodological shifts, brought about by various aspects, including automation, artificial intelligence and big data, has resulted in both suppliers and clients harnessing, or at least attempting to harness them in our environments. At a granular level, these technological developments have benefited us immensely, albeit with a number of well publicised obstacles that we continuously face and navigate, ranging from integrating existing in-house data into our research reports and the need for speed in conducting research at the moment of truth, to the demand for better visualisation and reporting. Subsequently, attempts have been made to overcome these challenges, with limited focus on other potentially more pressing concerns. While research suppliers (partners) typically engage with us clients seeking to obtain a clear understanding of our business and marketing objectives for the year, not enough is done in understanding the evolving nature of our operational environments, particularly regarding the increasingly complex privacy regulatory environment. The reality in our business environment is that these new digital methodologies are faced with a plethora of compliance (evidently evolving into organisational) regulations aimed at minimising risks and protecting customers and organisations from a variety of concerns, including but not limited to, cyber-crimes (money or personal information stolen online), cyber-attacks (online theft of classified information or disrupting services), companies collecting and sharing personal data online with other organizations, all of which are constantly present and evolving. Clear demonstration of these risks is the fact that according to the latest Allianz Risk Global Barometer 2018, South Africa is reported to have the third highest number of cyber crime victims worldwide, losing billions of rands a year to cyber-attacks predominantly through hyperlinks and the sharing of personal information numbers. Subsequently, the way we as organisations use data is affecting not only our risk profiles, but our brand reputation and relationships with customers. These operational risks have resulted, and justifiably so, in the placement of security measures, moreso within banking institutions in order to reduce the numbers of cyber-crime victims. What is emerging is the increasing complexity in the sourcing and handling of any forms of information relating to individuals, with the growing need for privacy impact assessments on research projects in our organisations aimed at identifying, assessing and managing the potential privacy risks that may arise from implementing programmes and projects. At present, implementation of research solutions by suppliers in our environment is predominantly reactionary to the changes that are occurring in our business operations. This is evidenced for example by addressing our need for more immediate research results aimed at resolving customer concerns quickly through provision of live dashboards that pull through customer detail to the relevant contacts in the business. However, this often requires the supplier to conduct an information technology audit that enables system integration to fit into our existing client information technology infrastructure, often times a very cumbersome and lengthy process. In undergoing this process, there are instances whereby the process and integration of technologies is only approved at a time when the objectives of the research have become outdated, missing the opportunity to make a valuable contribution towards the client’s organisation. The challenge lies in the definite need for more a proactive solutions approach in seeking to ensure that the intended research objectives are not only addressed, but also in a manner which easily fuses with our evolving operational environments so as to avoid any unnecessary delays that may compromise the usefulness of the results. Shiny new research technologies that continue to use hyperlinks risk becoming irrelevant, as they are increasingly restricted from operating in our environments. For the market research industry to remain relevant in a sustainable way we need to make sure that we, both clients and suppliers, are able to satisfy the changing compliance regulations, with the Protection of Personal Information (POPI) act being a key driver. Important to note that these regulations are not only being implemented locally but also at a global level, with the European Union’s General Data Protection Regulation (GDPR) coming into effect shortly (May 2018) and earmarked to harmonise existing data protection laws, in addition to fundamentally strengthening the rights of people in the EU to control their personal data. There is no question that the potential impact of these privacy regulations is massive, and much is still a work in progress. What is clear is that it is beginning to trigger profound changes within organisations of all kinds that collect data from people, with banking institutions being one of the most affected. This in turn will require alterations in process, technology, delivery, and design of surveys. But while these regulations represent a significant disruption to business operations from a market research perspective in the short term, it also represents a strategic opportunity in the longer term for research to be fully embedded in organisations.
The hype of understanding and mapping the shopper path to purchase and realities of collecting data at the moments of consumption and purchase: using technology enabled research to get closer to the moments of consumption and purchase without being intrusive in the life of the research participant Jack Hlongwane
Manufacturers of brands or products and retailers need to know what their customers look like, what they do before purchasing their products, what channels they choose and more importantly how the product fits into their broader life. Getting closer to the moments where customers use and shop for products provides a full context of the shoppper’s daily life, hence uncovering instants-of-intent where the purchase decision can be influenced. The shopper journey is complex and non-linear, also people do not always accurately recall the steps they took to make their final purchase or the factors that influenced their purchase behaviour. To get a comprehensive view of the shopper journey, one needs a layered approach that combines observational, behavioural and transactional data. Technology enabled research allows one to use mix methodologies to get closer to the moments that matter without being intrusive on the life of the research participant. Through quantitative research one is able to identify the channel repertoire of the shopper, their missions, spend and shopping styles. Qualitative research is then used to deep dive selected segments to get closer to their moments of consumption and purchase, without making it awkward for the research participant.
Journey to the center of the mind – decoding consumer’s decision making! Ejaz Mirza and Giulia Iorio-Ndlovu
Africa is a land of opportunities, with a potential for unprecedented growth. While the extraordinarily levels of ethnic, cultural and behavioural diversity are an asset, they are also an obstacle for businesses to overcome. Add to this, the new age culture, influenced by the ever-connected digital world. It’s clearly not easy for any business trying to make inroads into upcoming and established African economies. While the solution is obvious enough, understanding the thought processes of the diverse consumers across African nations is easier said than done – but not impossible! We present a novel way for marketers and researchers to get closer to decision makers and consumers of products and services by employing key factors driving the digital madness – the INTERNET, SMARTPHONES, COMMUNICATION PLATFORMS, and the consumers’ natural urge to share and communicate with others.
For decades companies have been trying to understand how customers feel about their products and services. Traditionally most research conducted in the field of customer service, satisfaction and customer experience focused on cognitive aspects of the engagement between the customer and the organisation. This research paper aims to explore the methodology and value of measuring customers’ emotions instead of cognitive aspects of their experience. Shortcomings of traditional measurement of customers’ experience. One of the most noted shortcomings of traditional customer experience research is that it usually only focusses on measuring cognitive constructs. Legrenzi & Troilo (2005), indicate that consumer satisfaction has been measured as a cognitive-state using principally quantitative techniques, resting on an assumption of the consumer as a “rational elaborator” of information. If customer satisfaction can be defined as the feeling a person experiences when a service or product offering meets his or her expectations, the question then arises why the majority of research studies only focus on measuring cognitive aspects of the interaction? Not only does the majority of studies related to customer satisfaction and customer experience focus solely on a cognitive evaluation of a customer’s experience, there are also an increasing number of studies that suggest that a respondent’s reported level of satisfaction is a poor predictor of their future repeat purchase or referral behaviour (Brady & Cronin Jr, 2001). A recent study conducted by Palmer & Koenig-Lewis (2010) indicate that while some of this poor predictability could be related to situational factors – that dissatisfied customers might not have other choices or that satisfied customers end their relationship with a company because they no longer need the services – some of this poor predictability might be caused by the lack of affective measures included in these studies. They further state that while some studies have included affective components, that “emotions have remained relatively unexplored as a link between measures of satisfaction, future behaviour and referral”. Organisations therefore face a difficult challenge since (a) most of them only collect cognitive feedback and (b) the accuracy to predict future behaviour when using these measures are questionable. How should organisations then measure and use customer feedback to improve their customer experience? Why are emotional measures not included in satisfaction research? There are various reasons why only a selected number of previous research papers and companies attempting to measure and improve their customer experience, include emotions in their measurements:
- Scepticism – Although there is mounting evidence that emotions are an important aspect to include in customer experience measurement, this has not filtered through to all organisations. Deep-seated scepticism about the trustworthiness and usefulness of affective metrics still dominates many organisations who believe that having a great product at the right price is sufficient. This prevailing paradigm, seeing emotions as subjective and unpredictable, makes it difficult for organisations to justify investing time, money and energy in the measurement of emotions to design better experiences.
- Merging of two realities – Another reason why companies struggle to effectively measure and use customer emotions is because it requires the merging of two realities that seems incompatible. The one reality is the data imperative. Most organisations understand the importance of data and that to truly differentiate yourself you need to collect better data and use it more effectively than your competitors. The second reality is that customers are human beings that experience emotions that are esoteric, fleeting and sometimes even contradictory. The merging of these two realities, collecting meaningful data about customers’ emotions is extremely challenging.
- Business application – One of the aspects that should also be noted is the lack of practical application within the business environment of these findings. It is the transfer of these theoretical findings into the business environment that is still lacking. Many organisations that do include emotional aspects in their customer satisfaction research, still don’t fully understand how to use this information to significantly improve their customer experience.
- Employing new methodologies – Most organisations uses surveys with questions and scales to collect customer feedback. Asking customers to rate their experience and subsequent emotions on a quantitative scale is not the ideal methodology. Ideally you want to ask customers explicitly which emotions they experienced and use text analysis to analyse this unstructured feedback. New methodologies and analysis systems are therefore required to effectively collect and extract insights from customers’ emotional feedback.
The advantages of measuring customer emotions Customer experience implies a customer being involved at different levels in their engagement with a company; rational, emotional, sensorial and physical. Customers are inherently emotional beings, and every interaction with an organisation will elicit a specific emotion, whether the company intended it or not. Understanding customers’ emotions during an interaction is essential to understanding whether an interaction helps drive greater engagement and satisfaction or if it is having the opposite effect. The challenge for companies is that not only are customers becoming more demanding, but there is now a growing volume of engagements with companies that happens using a variety of digital channels. These less personal forms of engagement may make customers feel detached and can cause a breakdown in the customer-company relationship. Because of this, customers may start to feel that their emotions are not valued and their needs not understood. Companies therefore need to constantly evolve and innovate to meet the changing and progressively more elusive needs of customers. The use of linguistic systems that enables companies to better understand the content and tone of customers during digital interactions are seen by many experts as the next generation of customer experience solutions. Linguistics refers to the scientific study of language, its structure, grammar, syntax and sentiment. This type of analysis enables companies to better understand customers’ emotional state and analysing patterns over time provides a deep level of insight into the Voice of the Customer. The use of linguistics will allow companies to identify specific interactions and areas of improvements, delivering better experiences, engaging deeply with customers, strengthening relationship and building long term loyalty.
Identifying international top line trends, and bringing it home Amone Redelinghuys and Anneri Venter
Now more than ever, change and innovation is occurring at a rapid rate across the entire marketing research spectrum, with no indication of slowing down. As research suppliers and users we are continuously made aware that what we did in the past (even what we are doing now) might not be sufficient in the future. Keeping up with the latest research trends, and remaining relevant in our approaches and offerings, is therefore paramount to our continued success. While overall industry reports, like the GRIT report, provide insightful indications of international trends, little is known about how it will play out in the South African context. In addition, we as South African market researchers know that international hypes and realities play out differently in our unique context, and requires further exploration. Therefore, a gap exists to test and unpack international trends among South African clients and consumers to get a more nuanced, realistic, and accurate view of what the future of market research looks like.
Brands and influencers: rules of engagement for authentic relationships with online communities Stacy Saggers and Andrea Morris
The origins of tribal or community-centred living stem back to prehistoric times and have been covered extensively in evolutionary psychology (Bartle, 2011). From the time of cavemen who would hunt, gather and build shelter in tribes to the present day, where in Africa there are around 3000 traditional tribes still in existence, people who find themselves in similar circumstances have operated as a collective. In fact, tribes are so powerful that, despite vast environmental, industrial and digital changes over time, tribe members often remain true to the underlying philosophies that brought them together. An example is the Zulu tribe, which is still the largest ethnic group in South Africa with around 10 million members and is now spread across both metropolitan and rural areas. The word ‘tribe’ need not only describe purely ethnic or pre-colonial communities. Tribes exist in a macro reality such as across nationalities, religious affiliations or shared language, as well as the more micro or manifestations of these nationalities, religions and languages that emerge over generations, over geographies and dynamically as new experiences shape them (Bartle, 2011). Indeed, tribes are a constant, permanent feature of human existence, which co-exist through an intangible shared history or experience, satisfying basic human needs for authentic collective living (Rustrum, 2011). If communities have always and will always continue to exist, then their perpetuation must surely meet a deep universal human need. It only takes a few seconds to personally resonate with the relevance and expression of tribal or communal engagement and interaction; key needs include the experience of safety in numbers (i.e. support and protection), validation (i.e. social identification and approval), and a reliance on trustworthy information upon which humans make decisions (i.e. education and learning) (Spinks, 2015). Given the universal needs that communities fulfil, it is clear that whether we consider communities with a traditional lens and label them ‘tribes’ or with a more modern lens and label them ‘networks, friends, groups or festivals’, the human requirements for support, protection, validation, identity and shared learnings will always exist. So what does community look like in our present environment? In an automated world, where extensive information and artificial intelligence offer the option of becoming increasingly inwardly-focussed, introspective and self-sufficient (Wright, 2015), a contrasting phenomenon appears to be unfolding; one where humans are in fact connecting across wider circles for support, protection, validation, identity and shared learnings to make informed, validated decisions, authentically. In our personal lives, we connect via digital platforms such as Instagram, Facebook, Pinterest and Snapchat, as well as across physical platforms such as book clubs, coffee dates, church services, kids play groups, hobby meetings etc, affording equal importance to both platforms. Similarly in the workplace, businesses connect across corporate ecosystems, using both digital and physical interaction to efficiently and effectively connect their brands with their clients, customers and consumers. Across all these communicative systems, the physical and digital realms have equal power and ability to connect people and enable authentic connection. It is our opinion that we should not treat ‘digital’ ‘modern’ or ‘technological’ communities as new or different from the communities of the past. Indeed, digital communities are an integral part of how we interact and will become more indistinguishable from the physical world as they continue to be used as a means of valuable and authentic connection (Wright, 2015). The point here is that communities which have their origin in the digital space should be viewed with as much appreciation and relevance by brands as those which have their origin in the physical space. This means that they should uphold the rules which govern social interactions and which lead to authentic relationships. We propose that while there is much discussion around the vast possibilities now available to brands making use of digital platforms and specifically the power of influencer marketing (Barker, 2018), the reality is that not all brands appear to act in a way which best leverages the great power that these platforms offer. By way of example, building awareness and affinity for a brand is not as simple as uploading a competition onto multiple somewhat similar Facebook interest groups. Drawing parallels with the physical world, a brand manager would not simply arrive at a book club meeting or a church service and announce that the community members stand a chance of winning in a competition. This is because the same underlying ‘rules’ that govern physical communities underlie and govern digital ones too. The vast pace at which digital platforms have expanded as well as the potential unlimited number of connection opportunities they offer (Zheng, 2018) have meant that the way in which brands should (or could or must) build authentic true-community relationships with their consumers are fuzzy, hazy territory. Every brand and every community is unique so there will never be a ‘one-size fits all’ strategy for brands to establish their place within these digital communities. However, we believe there are some underlying human truths which have their origin in the very reasons that communities exist and which may enable brands to legitimately and authentically engage with consumers (Zheng, 2018). Much of this centres on understanding the reasons for the existence of the group and then ensuring that interaction with its members occur during the moments that matter to them and indeed, are informed by the moments which matter to them. This research aims to uncover how brands could interact in a way that is authentic and relevant and in which their participation and interaction is welcomed. The premise for this research is that the needs of members in digital communities are the same as the needs of members in physical communities and that brands could develop meaningful connections through a deeper understanding of why these communities exist and how authenticity is realised in the digital environment. How do brands legitimately connect within communities? Our proposed idea is to connect with Influencers and thought leaders (Sussman, 2015), to uncover what really makes for community-building and relationship/ network generation.
The world is no longer exclusively defined by gender, race, age and socio economic components. People are much more multifaceted and can be segmented accordingly. We refer to these segments as tribes, a social group of distinct people. Even though society has moved in this direction, we as marketers continue to impose rigid demographic criteria on the people we want to get to know as consumers. They are questioned on what they drank in the last 6 months, why they made the brand choice they did or what on tv they remember seeing. People don’t consciously retain that information. The way to engage with tribes is through conversations. Through this start-small-to-scale-big approach, a focus on a smaller group of people can be powerful in garnering brand advocates. Cultural movements can take much less time to activate against and thus allow for quicker’go to market’ strategies.
The insights landscape is evolving drastically, and it is being challenged by an influx of competing firms in the insights space. With the digital age booming, companies that would never have been a threat a decade ago to market researchers are now competing for clients’ attention. For survey data to continue to play a role in guiding strategic decision making, the need to become data agnostic is essential and it needs to remain relevant, without compromising quality. The research industry has made progress towards becoming more data agnostic, as the GreenBook Research Industry Trends (GRIT) report for Q3-Q4 2017 reported that online communities and mobile first surveys are the top two methods being used by suppliers and buyers across the world. However, in South Africa this view is slightly different. Poorly designed, long winded surveys are still a common practice across different data collection tools in South Africa, despite the world of communication changing to instant, shorter and sharper bites of communication. Previous findings from behavioural economics’ studies highlights how irrational consumers are with their thinking and decision making. However, the majority of surveys are still being designed poorly, triggering System 2 type thinking allowing for rational answers which are not a true reflection of consumer behaviour and decision-making in the real world. Poor and clumsy survey design is not a new topic and has been researched extensively, but the research industry is taking far too long to move towards shorter and smarter survey design. Along with the boom in the digital landscape and the need for in-the-moment insights, comes the responsibility to also design appropriately for small screen devices such as smartphones and feature phones. Past mobile research-into-research has shown the negative impact poor survey design has on data quality. Market researchers are not challenging themselves and their clients enough when it comes to survey design. If the research industry continues to produce clumsy survey designs, surveys will eventually become obsolete as new sources of insights, powered by technology, continue to enter the market. In order to ensure surveys remain relevant in guiding strategic decision-making, market researchers need to ensure they design questions in a shorter and smarter way, to ensure good quality data – tapping into System 1 type thinking, as well as to keep users engaged. With the research industry gravitating towards a more device agnostic data collection approach, surveys need to be more mobile friendly to cater for all the different screen devices. Admittedly, it takes more than ‘the perfect survey design’ for a project to be successful. A research project has many elements that contribute to its success, from survey design, correct sampling frame, correct data collection method, efficient project planning all the way to insight generation. For the purposes of this paper the focus will be only on survey design and how to ensure the survival of surveys. In order to keep surveys relevant for the future and to ensure good data quality, what are the top best survey design practices that should be implemented right now across all data collection methods in South Africa, with an emphasis on design for digital devices? The research paper will evaluate a survey design that was used for CAPI and mobile data collection. With the use of case studies, the presentation will compare the two data collection methods, highlighting good and bad examples of questions, the impact of long brand lists without rotation, top boxing effect, respondent fatigue and honest responses when engaging on a mobile phone. The purpose of this research paper will be to showcase best practice techniques for survey design to ensure that researchers and clients continue to win by design.
The intent of the study is based on the continual rise of Influencer Marketing, which is fully realised by only a limited number of South African companies. Influencers fall part of a sub-category within Influence Marketing as one of the four key elements, where Influencer Marketing is not only executed as an activity but rather used to support and drive the overall long-term customer framework. Influencers have the power to affect change in behaviour through a change in consumer perception, which presents a distinctive opportunity in using neural analysis solutions to bridge the gap between data science and strategy execution. The process of sifting through and analyzing big data to optimise the planning, decision making and outcomes of influencer marketing will provide the significant link between the thoughts and insights consumer truly have and how companies tap into that ‘gold mine’ of data. The value of initiating such a strategy and revealing what does not work will be explored in the social and environmental context. The issue of consumer behavior falls in the field of marketing. Behavior consists of recognition, perception, emotions – understanding how consumers feel, how they evaluate different experiences and alternatives. The use of information and communication technology has transformed into something unique and has the ability to stir up business’s normal thinking and strategy approach. According to Fortune, the influencer market is going to grow up to $10 billion globally by 2021. This stretches the relevant need for companies to get every player involved in this business and take on the challenges ahead. The rise of ad blockers, outdoor and digital clutter and the decline of TV viewership is boosting the growth of influencers, confirming that word of mouth is the most effective type of marketing even in the social media era. It has only become digital, just like many other aspects of our life. The process of using influencers has gradually become more automated; from content analysis to influencer search and brand affinity. The growing transformation of companies’ interaction with its customers is based on advanced information technologies (wearable devices, wireless internet communications, smartphones, and computers) and social analysis (such as Twitter, QQ, Facebook, blogs, Instagram and Skype). Customers are accustomed to seeking and following information from influential individuals, someone with a high online status and presence. Thus companies are faced with a growing challenge where consumers’ perceptions depend on factors out of their control and not merely on their efforts alone. How can marketers control the perception of their brand in an environment which is increasingly out of their control? Trust plays a critical role in accessing customers social behaviour to change the perception of a brand. Artificial intelligence technology and big data analytics tools can cut through the fluff and fake followers to provide precise information about thousands of brand ambassadors and followers across a spectrum of social media platforms. Maintaining a powerful personalised marketing and social intelligence platform looks past the over utilised realm of micro-influencers or newsflashes by using proprietary artificial intelligence (AI) algorithms to analyse brands’ social media communities. This leads us to explore three basic principles of influencer marketing. First is the discovery space, the reach of the audience size. Second is the relevance of the topic being expressed and lastly, resonance is the outcome of reach combined with relevance. Resonance determines how much activity an influencer initiates by posting content. These three principles will be explored in conjunction with neural analysis.
Decades of research have concluded that human behaviour is largely driven by nonconscious process – and yet, the market research industry predominantly focuses on insights gathered through surveys, focus groups, and other such self-report (and conscious) measures. At a global scale, nonconscious measurement is no longer just a “special occasion” consideration, with over 50% of research suppliers already using and engaging with methodologies in this space (GRIT report, 2017 Q3 – Q4). Neuro and biometric measures certainly present valuable data, however, various restrictions – most notably around cost, scalability and expertise – limit the application of these tools (specifically in the South African market). Subsequently, valuable nonconscious insights are not integrated with conscious data – and we rarely get the ‘full view’ or ‘complete picture’ of consumer behaviour. Nonconscious measurement does not only face challenges of practicality in application – a general lack of awareness / knowledge / understanding around nonconscious insight is also prevalent amongst the industry (applicable to both buyers and suppliers).