
AI
To assist. Not replace.
In FMCG, it’s not just the goods that move fast. Consumer trends change rapidly, just-in-time supply chains and next-day deliveries are becoming the norm, and product innovations are expected with every seasonal update.
The reputational and material costs of failing on any of these fronts can be catastrophic, so it is unsurprising that the predictive and deep analytical powers of AI are increasingly put to use by manufacturers, advertisers and retailers.
Business decisions don’t operate in isolation: there are any number of unseen factors affecting purchasing behaviour and influencing stock control which, without AI, would go unnoticed: can last season’s run of winter coats, for example, be attributed to a particularly cold spell, media scaremongering about a “Beast from the East”, or a great marketing campaign?
To truly get the answer to questions like these – answers that could directly impact future business performance, you need to combine, and mine multiple data sets from across the business and outside. And this is where Quantum’s Artificial Intelligence can really come into its own.
Understanding what really makes customers buy products is the holy grail for many FMCG marketers. Traditional research methods such as observation, focus groups and surveys all have their flaws and are subject to various biases, and weaving together an accurate picture of behaviour across such different data collection methods may sound impossible, but it’s a task like this where AI and Deep Learning can truly add value.
By using big data algorithms, combined with visual analysis of in-store cameras, environmental factors, and an almost endless list of other criteria, AI can not only help understand why customers have bought, but can inform the placement of goods in store, the language used in ads, even the sizes and shapes of packaging for maximum uptake in future.
Your customer doesn’t care how much you know until they know how much you care.
— Damon Richards, Business Consultant
From the factory floor to your distribution centres, being able to react rapidly to change is critical to profitability in FMCG. Employing AI alongside your human teams enables you to alleviate operational bottlenecks, leverage intelligent DPA, and rapidly change inputs and processes to address a shift in demand. The moment you’re aware that Product X is shifting more units than expected in a certain configuration, AI-enabled production facilities can evaluate and action the necessary production changes to ensure that demand is met. Selling less units in the north than the south? AI can proactively re-schedule shipments and reroute vehicles to match sales.
Quantum’s AI solutions make use of state-of-the-art algorithms and self-learning neural networks to continuously build a picture of your operational processes, inputs and outputs, supply chain capabilities and your sales, to build a complete, always-updating picture of the business and how to maximise profitability. This version of BPA is the future – intelligent BPA.
With so many customers interacting with retailers and manufacturers through their laptops and smartphones, there is a clear opportunity to more accurately cater to their needs. Digital channels enable the collection of significant personal and anonymised data on your customer base to ensure that what you sell them, and what you say to them, matches what they require.
By combining datasets from major channels – from website analytics and eye tracking, through to third-party data from social platforms and other applications, it’s possible to build considerable datasets.
However, fully extracting value from that data can be more of a challenge…
Different formats and different types of data from different sources can be difficult for the human brain – and even lesser computing platforms – to interpret with any confidence.
With Deep Learning and neural networking capabilities, Quantum’s AI platform helps your advertising and product marketing teams rapidly and confidently understand your audiences, uncover new segments, and optimise messaging for each.
Manage the routine tasks by implementing this and leaving it to run for monitoring and re-checking.
A series of capabilities to support people, and complete projects and tasks quickly and accurately.
Allows challenging, mundane, and repetitive tasks to be fully automated, and self-improving, unsupervised.