More than ever before, it is critical that Consumer Insights Managers and Marketers carefully consider their needs before commissioning and designing a tracking study.
Are they after a streamlined, automated tracker that measures a few basic metrics without advice or support? Or are they looking for a comprehensive tracker with deeper insights backed by expert guidance from consultants? Perhaps it’s somewhere in between: a nimble tracker that allows for flexibility, such as occasional deep dives into hot topics.
Tracking studies that involve a wide range of metric types tend to require more human involvement than other types. There is more to work through, more to understand and interpret, and more nuance to translate from ‘what’ to ‘so what’ and ‘now what’.
In that translation and value-derivation journey, strategic trackers rely massively on the quality of the people who are on the tools, but that isn’t to say there’s not scope for automation, streamlined delivery, democratised access for stakeholders, and efficiency gains. In fact, we are operating at a time when clients should expect to continue to receive the same or better quality work and client service, in a more efficient and cost-effective way. It’s the very combination of human consulting nous and the various applications of AI in tracking that make this possible.
One of the names of the game in tracking is to negate the need for client-side insights and research team members to have to re-work and re-hash agency deliverables into stakeholder-ready assets. It’s about working in a way that releases the client to conduct higher, not lower value tasks – which usually comes in the form of more time with stakeholders, and having impact.
Agencies can deliver better on this basic yet important client need not by looking immediately to AI, but instead by servicing the account with high quality consultants, not over-delegating, and ensuring all members of the agency account team have 100% visibility and appreciation of the objectives and where the work plugs in. These and other focal points go a long way to making clients’ lives easier, and in their own way drive efficiencies by empowering the client to move big not small rocks. Clients can play a part too by doing their best to ensure all relevant decision makers and influencers, including creative and media agencies, are in the room when workshopping the results and deciding on resultant actions. This creates information cohesion and shared understanding, encourages debate and collegiality, and alone can drive uplift in quality, immediacy of action, and efficiency.
AI is transforming the research and insights world, and the future is bright because of that. It’s really important to be clear on whether you’re seeking to improve quality, make things faster, or make things cheaper, before deploying AI into any research piece -including brand and other types of tracking. Depending on the answer to this, one looks to different AI-based solutions / approaches. The blanket term ‘AI’ actually isn’t particularly useful as a descriptor. It’s more important to consider use cases and how AI can assist.
There are some very high value things one can do today in the world of tracking that clients soon will see as table stakes – particularly for larger, more comprehensive trackers. What follows isn’t intended to be exhaustive, but instead just a taster of what you should (if you’re a client-side buyer) be asking of your agency in our new world: better elicitation, faster delivery, greater accessibility to data, enhanced summarisation capability, and synthetic personification for adjunct use cases, including creative campaign testing, cog testing, and drill-down exploration.
If done well, these initiatives can serve to unlock client-side insight manager time to focus on higher value tasks such as stakeholder engagement and impact-driving efforts. Further, they ensure greater immediacy of access to stakeholders, thereby democratising insights. There is also of course less reliance on Q and unwieldy data files, not to mention manual processes. Let’s explore in some detail.
AI tools can vastly improve the elicitation process, making the journey from data collection to actionable insights faster and more accurate:
AI tools can automatically clean and format data, speed up the analysis process, and test hypotheses rapidly. This results in clients receiving high-quality insights within hours or days of fieldwork, rather than waiting weeks. AI-powered tools help sift through data to quickly uncover key insights, freeing up consultants to focus on interpretation rather than raw data analysis.
AI democratises data and information, allowing stakeholders across the client organisation to engage directly with insights without needing technical analytical expertise. With AI-powered platforms, anyone can query the data using natural language; "What factors will drive brand awareness over the next 24 months?" or "How can my brand improve its customer satisfaction scores?" This accessibility empowers teams and decision-makers to draw insights on-demand, reducing reliance on specialised analytics teams.
AI is uniquely suited to quickly process and synthesise large volumes of data. Natural language processing (NLP) tools can analyse open-ended survey responses and identify key themes in seconds, saving both time and cost. This allows for richer, more nuanced feedback, especially in large-scale tracking studies.
A powerful AI application is synthetic personification which allows researchers to engage with customer segments in real-time. For example, AI can simulate customer personas (e.g., a 36-year-old mom of two) and generate insights about their preferences, behaviours, and reactions to various stimuli like messaging or product offerings. This capability accelerates ideation and testing for campaigns, product development, and brand strategy.
In the evolving landscape of brand tracking, AI is set to become a baseline expectation especially for larger, more complex studies. Clients should begin to expect higher-quality results delivered faster and at (potentially) lower cost, or better ROI.
However, it's essential not to overlook the importance of human expertise and collaboration. While AI can significantly enhance efficiency and precision, the human element remains critical in interpreting insights, ensuring strategic relevance, and guiding decision-making at the brand level.
When seeking to transform a brand tracker using AI, it’s important to actively manage unintended consequences that can arise. Over-democratisation of data can lead to loss of narrative control and increased chances of misinterpretation. In addition, always-on stakeholder access can inadvertently lead some to ‘jump at shadows’ if results of slow-moving metrics appear to move with greater volatility than previously experienced.
Tracking studies are not just about gathering data, they are about turning data into meaningful actions. The power of AI lies in its ability to enhance the quality and speed of the insight process, but its true potential is unlocked when combined with strategic consulting and expert collaboration. Agencies that embrace both AI technologies and human expertise will be best positioned to meet the rising demands of clients in this new world of insights.
Chris Crook, Founder & Managing Partner at Nature
Alex Coningham, Senior Associate Director & Head of AI, Nature
