In the face of record-high inflation rates and strict sustainability regulations, there’s an increasing demand among smaller brands for cost-effective solutions to champion ESG. Thankfully, big data and AI offer a silver lining, enabling brands with limited budgets to find innovative paths to sustainable growth. And in a world where over 85% of the global population are connected through smartphones, data is more than just numbers—it’s a limitless tool for more agile decision making.
In this blog post, we’ve sifted through insights from industry leaders, in-depth research like that from McKinsey, and recommended two practical AI-driven methods for small brands to harness big data for sustainability.
Join us as we navigate the power of big data in championing sustainability.
1. Capitalising on Dormant Assets
Unused resources, when identified correctly, can be an unexpected goldmine. Queen of Raw’s ingenious marketplace, for instance, sells previously wasted textiles. By harnessing supply chain data, they identified and monetised valuable waste, simultaneously supporting sustainability by diminishing waste. This highlights a unique opportunity: next time you assess dormant assets or resources, consider their potential sustainable value.
2. Deepening Customer Relationships
Prominent tech companies like Apple, Dell, Amazon, and Google have committed to sustainability initiatives in recent years, largely propelled by data analytics. By analysing customer preferences and behaviours, these companies can align their sustainability efforts with customer values. Smaller brands can similarly use big data to understand their target audience better, develop eco-friendly products, and communicate their sustainability efforts effectively to build a loyal customer base.
3. Driving Eco-Friendly Innovations
Remember when McDonald’s and Starbucks jointly tackled the global cup waste issue? This collaborative push for biodegradable cup solutions arose from interpreting consumer feedback and market trends using big data, leading to more of a circular economy – rather than the linear ‘take-make-dispose’ model. Smaller brands can follow suit by utilising big data to foster eco-conscious innovations that resonate with modern consumers and differentiate them in the marketplace.
4. Fostering Brand Loyalty with ESG Initiatives
A compelling McKinsey study, encompassing five years of US sales data, illuminated a profound link between brand loyalty and ESG commitments. Brands emphasising ESG claims saw repeat purchase rates surge by up to 34%, a stark contrast to their counterparts lagging in ESG emphasis.
Therefore, there’s a suggestion here that a deeper engagement with ESG-related issues across a brand’s portfolio can significantly bolster customer allegiance toward the brand as a whole.
5. Transitioning from Reporting to Action
Traditionally, sustainability data has been used for reporting purposes. However, big data offers a pathway to transition from mere reporting to actionable insights. A fascinating comparison: streaming a 30-minute Netflix episode consumes as much energy as driving half a mile in a hybrid car to rent a DVD.
By analysing sustainability data in real-time, smaller brands can make data-driven decisions to enhance their sustainability practices continuously. This proactive approach can significantly improve a brand’s ESG performance.
Two AI-Driven Methods for Small Brands to Harness Big Data for Sustainability
Brands can now analyse their own data, however big or small, at breakneck speed, thanks to AI. You can do it both at scale and in real-time, allowing you to adjust your sustainability strategy faster than the shelf life of your actual data.
Here are two recommended methods small brands can employ to leverage big data for enhancing their sustainability practices.
1. AI-Powered Insights
There’s more to data than sheer volume; it’s about depth. Tools like Tableau GPT, powered by advanced AI algorithms, allow brands to delve deeper into their datasets. Rather than manually sifting through pages of data, brands can ask direct questions to these tools, such as “What led to the decline in sustainable product sales last quarter?” The AI then processes vast amounts of information to provide detailed insights, allowing brands to make more informed, strategic decisions.
2. Tapping into NLP for Comprehensive Analysis
While large amounts of data is rich in insights, it’s also usually varied and unstructured. Enter Natural Language Processing (NLP) tools. Platforms like Sensefolio harness the power of machine learning and NLP to dissect this unstructured data. They help brands identify emerging ESG trends, sentiments, and patterns across a broad market spectrum. By tapping into these insights, brands can tailor their sustainability initiatives in alignment with market demands, ensuring they remain at the forefront of ESG practices.
Big data’s transformative power is undeniable, offering both large conglomerates and smaller brands the insights needed to drive sustainable initiatives. The intersection of technology, data, and sustainability presents a promising frontier for brands committed to making a difference.
For those keen on delving deeper into the world of big data, events like Big Data London provide a comprehensive platform to engage with experts and like-minded professionals.
However, if you’re a brand seeking to harness the power of big data for sustainable growth, Chesamel is at your service. Our tailored data analytics solutions provide an all-encompassing view of your business, enabling you to make data-driven decisions and align with ESG standards. The journey towards sustainability is both a challenge and an opportunity, and with the right tools and insights, any brand, regardless of its size, can pave the way for a greener, more sustainable future.