Perspectives
In an era dominated by technological advancements, AI-driven insights and synthetic data are gaining importance toward helping understand consumer behaviour.
Much has been written recently in the media about this topic with articles suggesting that the rise of synthetic data is poised to disrupt the market research industry, threatening to make traditional methods obsolete. As Mark Ritson highlights in Marketing Week, research firms are expected to resist this shift, but the reality is that marketers are likely to gravitate towards technology-driven solutions, signalling a far-reaching transformation in the industry.
However, while the technology and tools offer unprecedented capabilities, the human touch remains irreplaceable, calling for a balanced market research approach that relies less on AI power and synthetic data, and more on human expertise, to extract meaningful consumer insights and authentic brand relationships.
The role of AI in generating market insights and vital analytics
Research and analytics have been in a state of constant evolution, powered by tech innovation. Some AI tools are proving particularly useful for ingesting, analysing and synthesising large datasets, performing an initial set of analyses, and identifying patterns that would otherwise take data analysts and market researchers significantly more time and resources to uncover.
For example, at Hall & Partners, and broadly at the Escalent enterprise, our AI-teams are piloting a range of AI tools designed to analyse and synthesise verbatim feedback from quantitative surveys and/or audio-video files from in-depth interviews/focus groups. These tools will identify key themes and provide an initial layer of analysis, streamlining the process of extracting meaningful insights for brands.
AI tools strengthen market research as they have the ability to handle vast amounts of data, perform complex calculations, and generate initial syntheses, thereby helping identify the "what" by revealing trends, patterns, and correlations.
Despite the power of AI tools, the "why" behind consumer behaviours and the "so what" for brand strategies remain the domain of human expertise. Understanding the motivations, emotions, and contextual factors that drive consumer actions requires qualitative insights that AI alone cannot provide. This is where researchers and marketers play a crucial role in harnessing insights from AI.
The role of the researcher or insights professional has evolved far beyond mere data collection. They now serve as invaluable advisors, offering crucial context that bridges the gap between understanding the "why" and "so what" to strategically answering the "now what."
Effectively bridging AI technology and human insights for strategic decisions
Smart human researchers are essential for interpreting data, asking the right questions, and ensuring that AI models are appropriately guided. Further, the skill of a researcher in framing the correct prompts and questions is critical to leveraging AI effectively. Without human input to steer AI, the technology may provide accurate data but miss the nuanced understanding necessary for strategic decisions.
The integration of AI and human expertise creates a balanced approach that maximises the strengths of each. We incorporate AI in market research to handle the heavy lifting of data processing, leaving our research and insights team free to delve deeper into the more nuanced and tenuous aspects. This synergy allows for a comprehensive understanding of consumer behaviour, combining the broad patterns identified by AI with the rich, contextual insights provided by human analysis.
For example, while AI may identify a trend in declining brand loyalty, human researchers can explore the underlying reasons through in-depth interviews, ethnographic research and focus groups. They can uncover emotional and psychological factors, such as changing values or dissatisfaction with a particular aspect of the brand experience, while AI can still help them ingest multiple interview and focus group recordings at scale and transforming them into analysis-ready formats and summaries. Such utilization of human-AI collaboration to synthesize actionable insights are crucial for developing brand strategies that resonate with consumers on a deeper level.
Synthetic data: A step too far in market research to mimic real human behaviour?
The same set of possibilities and limitations hold true for synthetic data too. Synthetic data is artificially generated information that mimics real-world data. It is created through algorithms and simulations, designed to have the same statistical properties as actual data without including any identifiable information from real-world entities. This kind of data is often used in fields such as machine learning, data analysis, and software testing, and has gained popularity due to its scalability, cost efficiency, and privacy compliance.
We recognise that research and analytics is constantly evolving but the use of synthetic data may arguably be a step too far. Synthetic data cannot capture the individuality and emotional depth of human beings and their day-to-day lives. It fails to grasp human emotions and the context of nuanced individual experiences, which are crucial in shaping behaviour. We believe there is still a crucial role for real human research to uncover unique insights which are not possible from synthetic data alone.
For example, Hall & Partners’ research teams provided a global bank with valuable insights into the influence of language on campaign engagement across different markets. In the UAE, qualitative research revealed that the use of English significantly impacted campaign effectiveness. This insight, gained through direct interaction with the target audience, enabled the client to develop a multi-lingual, multi-ethnicity campaign that enhanced inclusivity, engagement, and impact.
The complexity of the real world, with its nuanced human interactions, cannot be fully replicated to understand consumer behaviour by synthetic datasets. Consequently, synthetic data often lacks the richness of real-world data, potentially leading to inaccuracies in model training and insights that fall flat.
Inaccurate or unbalanced synthetic datasets in market research can lead to biased insights and decisions, adversely affecting marketing strategies, product development, and customer engagement.
Unlike synthetic data use cases, human insights capture the subtle emotional triggers, irrational behaviours, and personal preferences that drive consumer decisions. This rich understanding enables marketers to craft more personalised and impactful campaigns. By tapping into the authentic voices and experiences of real people, businesses can uncover deeper motivations and trends that algorithms and synthetic data might overlook, leading to more successful and resonant marketing initiatives.
For example, through an immersive online community spanning three markets, C Space assisted an alcoholic liqueur brand in identifying new 'occasions' for their product, uncovering consumer-generated ideas that inspired innovative marketing strategies. Similarly, through in-depth video interviews across multiple countries, Escalent helped a prominent ad platform unearth granularities associated with advertisers’ and ad agencies’ experience with competing ad platforms, and the technical, functional and relational aspects driving those sentiments. These insights, coupled with exploratory testing of new features and concepts, helped the ad platform determine product and marketing levers to consolidate market share and customer stickiness.
Addressing bias and inclusivity: Can synthetic datasets navigate DEI challenges?
In today's AIverse, the need for brand authenticity and trust in customer-brand relationships is more crucial than ever. The open data economy allows for personalised customer experiences, but the human touch ensures these experiences are truly meaningful. As consumers grow wary of data privacy and manipulation, brands must build trust through authentic communication. While AI and synthetic data can enhance research, they should never replace the insights gained from real, diverse human experiences.
Using synthetic data in market research raises several DEI-related issues too. It can inherit or amplify biases from original data, resulting in discriminatory outcomes, and may fail to represent minority groups, leading to a lack of inclusivity and overlooking systemic issues. Validating synthetic data to reflect real-world diversity is challenging, impacting accuracy and relevance.
Additionally, ethical concerns include questions about the authenticity and integrity of research if synthetic data misrepresents marginalised communities within society. Compliance with DEI standards add complexity, especially with sensitive information. Developing and validating synthetic data for DEI market research is resource- and time-intensive and, if not managed well, can reinforce stereotypes, complicate quality control and potentially undermine trust.
Embracing a balanced approach that respects the complexities of human emotions and individuality is essential for producing consumer research and insight that can facilitate meaningful consumer experiences and building authentic, enduring brands.
Brands must seek to balance innovation with empathy, ensuring that their interactions remain genuine and relatable, fostering deeper connections with their customers. Successful brands are those that encourage Human-AI collaboration and leverage technology to enhance human connections rather than replace them.
Looking ahead
The future of brand building relies on a balanced integration of AI and human insight. While technology equips businesses with powerful tools for extensive data analysis and synthesis, human expertise remains crucial for interpreting these findings and crafting business strategies that truly resonate with consumers.
By leveraging AI tools and the depth of qualitative insights, brands can achieve a comprehensive understanding of their audience. This holistic approach fosters trust and loyalty in an increasingly digital world, ensuring that brands are not only data-informed but also deeply connected to the nuanced realities of their target markets.
The advisory role of human researchers offers a deeper understanding of human behaviour, brand dynamics, and industry trends. This unique perspective enables them to deliver actionable insights that drive informed decision-making and fuel brand growth. Their expertise ensures that data isn't just informative, but transformative.
The synergy between technology and human insight is essential for creating meaningful consumer experiences and building authentic, enduring brands.
5 key takeaways on brand building while leveraging synthetic datasets in market research
- Balancing technology with human insight: While AI offers powerful tools for large-scale data analysis and initial pattern recognition, it lacks the ability to capture the emotional depth and nuanced behaviours that human expertise provides.
- The limitations of synthetic data: Synthetic data in market research can introduce biases, miss emotional context, and lead to inaccuracies in model training, highlighting the necessity for real-world data to ensure authenticity and reliability in research findings.
- The role of human expertise: Human researchers are essential for interpreting data and analyses outcomes, asking pertinent questions, and providing qualitative insights that AI alone cannot offer. This human touch is crucial for understanding the "why" behind consumer behaviours to gather insights and develop brand strategies that resonate at a deeper level.
- Ethical and trust considerations: In an age where data privacy is a significant concern, maintaining brand authenticity and building trust through genuine human interactions and insights is more important than ever. Brands must balance technological advancements with empathy and authenticity to foster meaningful consumer relationships.
- Integrating AI and human insights: The future of effective brand strategy lies in the harmonious and successful integration of AI and human expertise. Human-AI collaboration ensures a comprehensive understanding of consumer behaviour, combining broad data patterns with rich, contextual insights to create impactful, personalised marketing strategies.
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