The grocery sector is preparing for a period of unprecedented disruption as food retailers battle to discover new sources of value for consumers. Focusing on the fundamental aims of improving customer service, loyalty and integration of digital and real-life experience, retailers are seeking out ways to better understand shoppers’ buying habits and adapt their operating models to cater for customer needs.
Artificial Intelligence (AI) is becoming the new frontier for grocers looking to lead in these areas. Long a source of hype and unrealised promise for the industry, advances in data and computing power mean that AI is finally at the level of maturity to deliver on its potential. According to Accenture, 78% of consumer goods executives recognise the potential of AI to disrupt their industry and the way they engage with customers.
Capturing this power offers food retailers an opportunity to optimise their processes and use data and algorithms to gain greater efficiency and competitive advantage. Those best able to capture the value of data will experience improvements in operations, increased sales and the ability to move faster to meet consumer needs.
AI brings intelligence to all areas of grocery operations, helping businesses to learn and optimise from experience. Retailers today have access to almost unlimited computing power with which to train their AI algorithms, giving them the ability to discover trends, patterns, and correlations in their data that no human analyst could hope to discover manually. This can lead to improvements in all areas from how much stock to purchase through to how many employees should be on the shop floor at any one time.
For grocery businesses, AI can take the richness of data available and transform it into understandable insights about consumer behaviour and purchase decisions. This allows for more accurate forecasting on future resource needs and smarter decision making. Specific areas where retailers can benefit include:
Enhancing sales strategy and offering more competitive pricing
Seasonality has always been a major sales driver in retail, particularly around major calendar dates such as Easter and Christmas. For the grocery sector, taking full advantage of seasonality has often been a challenge as the extent of increased demand, particularly around ‘micro’ events (like World Chocolate Day or National Fish and Chips Day), can be hard to predict. Whereas inventory and sales database systems simply track purchases of individual products, machine learning systems allow food retailers to analyse seasonal events to a much greater degree of granularity, capitalising on buying triggers at times where historically they’ve experienced higher sales volume.
For example, Criteo data shows that alcohol sales increased 102% in December and decreased 54% in ‘Dry’ January. For Pancake Day, online sales of lemon juice increased 230% in the days leading up to the event while in the lead up to Chinese New Year, prawn cracker sales peaked by 268%. If retailers can harness these types of patterns, they can pinpoint exactly when to adjust inventory and dynamically change pricing in line with market demand
Optimising supply chain
In the grocery sector, waste has historically been a massive problem and has negatively impacted margins. The process of orchestrating the various phases involved for produce to get from origin to point of sales can be enhanced to avoid risks such as spoilage or scarcity. AI allows demand and supply to be more closely correlated. Using self-learning predictive models, food retailers can identify problems and inefficiencies in their supply chain, drilling down into specific areas such as inventory management, replenishment, promotions, loss prevention and delivery logistics, among others.
Adapting to evolving buyer behaviours
According to 2018 YouGov research, ownership of voice-activated devices in the UK doubled within a year with one in 10 households now using assistants such as Alexa and Siri. This trend has massive implications for the food retail sector; indeed, more than half of all grocery shoppers who use a smart device say they plan on making a purchase in the next six months
Use of AI voice assistance technology is helping to remove common points of friction for the grocery consumer, such as sitting at a computer, downloading mobile apps, and dealing with busy stores. The convenience factor is therefore proving an attractive feature, especially as consumers become more comfortable with using voice technology.
From the brand perspective, voice activation also changes the way they approach marketing. Rather than focusing on slotting fees or Google Ads, voice-activation search algorithms tend to favour Amazon ratings. The Wall Street Journal has noted first-time purchases on Alexa receive recommendations from Amazon in more than half of instances. Food retailers therefore need to pay closer attention to how their products are rated online to reap the benefits of this shift.
Removing friction from payment process
The process of payment has long been a major consumer frustration and an unpredictable element of entering any food retailing establishment. Self-serve options have had a massive impact, both in speeding up the process and on reducing the cost for retailers. AI is the next wave in this development, allowing a smoother flow of customer traffic by removing the cashier entirely. Amazon Go has pioneered this trend, using AI-augmented sensors and smartphone apps to make payments seamless, and we can expect it to increasingly become the norm in the coming years.
Offering smarter delivery
As consumer lifestyles change, grocery shopping is becoming less of a weekly event and more of an on-demand activity. Online delivery has become a common trend, with retailers like Ocado, Blue Apron and Hello Fresh popular among consumers. To get to the next level of service, grocers are seeking more creative and efficient ways to get products to customers. This includes robotic and autonomous delivery vehicles and drones equipped with AI. An emerging trend is the ability of consumers to combine automated delivery with smart fridges to self-replenish consumers’ stocks of staples such as milk and eggs whenever they’re running low.
Making marketing relevant
All retailers want to better understand their customers so that they can adapt their marketing approaches accordingly. In the food and drink category, consumer habits are continually changing as people become interested in alternative diets and lifestyles, such as vegan, keto and paleo. Grocers can use AI to understand these trends and make more personalised offers, optimising the marketing funnel. Efficient marketing means less discounting, and more profit.
Once the domain of sci-fi comics, AI is moving from promise to real-life implementation. The speed at which machine learning is developing is already changing operating and customer engagement models across a range of industries. In the grocery sector, the masses of data produced each year by sales and inventory can bring a seismic shift in how retailers drive more value from their existing assets. This throws the competitive landscape wide open as new market entrants challenge the dominance of supermarkets, who have typically been slow to embrace technological change.
To ride this wave, food retailers should start by determining their business objectives and working backwards through their processes and practices. By then reviewing all aspects of their business’ operations and sales model they can better assess opportunities to enhance operations with AI. This helps Identify which areas of the business are producing untapped data sources that can become areas for initial development. Likewise, it highlights which areas of the business lack data but present the sort of opportunities outlined above, helping to guide future activities.
As data heavyweights like Amazon increase their presence in the sector, this approach offers the best means for preparing for the near future, and creating a point of differentiation with competitors.
By Nicole Kivel, director, Criteo Retail Media, managing director, Northern Europe