How AI helps brands play the generation game
A decade ago, retailers were grappling with how to cater to millennials. Meetings were overloaded with jargonistic strategy for how best to reach this new breed of digital natives; it was all about the millennial pound. But today, many retailers have firmly turned their gaze to Gen Z, 18 to 24-year olds, who seem to be challenging today’s product offering, particularly in convenience stores. According to a report from Packaged Facts, Gen Z has influenced the rise in the production of snack and convenience items. But the snacks Gen Z wants are not the same as previous generations. Now it’s all about health. So how can convenience store retailers keep up with changing tastes and trends?
The shift in consumer trends across generations is nothing new. It doesn’t take a data analyst to tell you that our tastes, in many ways, differ from our parents and their parents before them. This is due in part to the availability of new products and our awareness of them, thanks to easy international travel and the rise of social media. But retailers can’t make assumptions about trends. Indeed, your grandma might very well want to buy a quinoa salad scattered in pomegranate seeds and a bottle of prosecco. We can’t presume anything. But one thing is for sure, retailers have to keep agile with their product assortments to meet the changing habits, and tastes, of different shopper segments. And retailers now have the benefit of vast swathes of customer data available to them in order to specifically tailor assortments at an individual store level. Using this insight, retailers can simultaneously cater to Gen Z’s habits and meet the needs of other generations too. But many retailers are daunted by the prospect of this analysis, deeming it to be an impossible feat to get right.
Using AI to understand customer behaviour
Most retailers have, in the past, managed their product assortments based purely on historical sales data. The problem with this method is that it doesn’t benefit current customers and how they’re behaving right now. Only analysing historical data can inflate stock keeping unit (SKU) counts, which can lead to inaccurate forecasts and inventory issues (such as over and out-of-stocks). And if that does happen, it won’t do anything to increase customer satisfaction or retain your customers.
By using artificial intelligence (AI), retailers can use customer data to understand current trends and even predict future behaviours to determine product assortments, demand and pricing. This means retailers have access to in-depth insight into how and why shoppers choose the products they do. Assortments and shelf plans can then be used to enhance the customer decision-making process accordingly. For example, retailers are able to determine which products should be grouped together to match shopper preferences on price, brand or flavour. And as shopper preferences will alter in different geographical locations, AI will help to localise product assortment and layout strategies. Being able to strategically manage assortments based on consumer preferences can both improve the shopping experience and grow profitability across stores.
Retailers have long struggled to manage assortments at a store level, to truly localise the shopping experience and to ensure the right customers are served the right products. The reason for this has been how time-consuming a task this is, to achieve this level of localisation. However, with AI, retailers can manage the assortments of individual stores or store groups with similar customer behaviours. For example, shops in a certain area might see a big number of baby boomers in the morning, who prefer muffins or doughnuts, while others near a university might cater primarily to Gen Z and millennials who prefer fruit or energy bars. Incorporating behavioural-based data into the assortment process, convenience stores can optimise their stores, driving more relevant item assortments to each location, while also staying aware of space and physical constraints.
Appealing to everyone
Ensuring convenience store retailers are catering to Gen Z shoppers and their growing buying power is all well and good, but what about everyone else outside this demographic? By using AI, assortments and shelf plans can offer the optimal selection in the right quantities, and, most importantly, appeal to the widest customer base possible. And the ability to remove duplicate products and introduce the ones with the highest demand that will sell to the most relevant shoppers is now a reality for retailers – whether for one store or for thousands.
In short, AI is revolutionising category management and planning and increasing efficiency. But most importantly, it’s being used to finally fully understand customer behaviour, so retailers can offer the best service possible.