How to manage assortment to cater to all generations

Gen Z is challenging today’s product offering in convenience stores. Comprising 32% of the global population, 18- to 24-year-olds have influenced the rise in production of snack and convenience items, according to a report from Packaged Facts. However, the snacks Gen Z wants are not the products of the generations before them — they’re looking for healthy options.

As consumer consumption habits continue to shift and create rifts across generational lines, convenience store retailers should consider adjusting their product assortments to meet the varied demands of changing shopper segments.

By gaining a deeper understanding of consumer preferences to tailor assortments at individual store levels, retailers can simultaneously cater to Gen Z’s habits and meet the needs of other generations.

However for most, creating tailored assortments seems to represent more work and more effort than is feasibly possible.

KEEPING PACE WITH CHANGING CONSUMER PREFERENCES

For years, retailers have managed their assortments based on historical sales data, but this method alone isn’t conducive to making decisions that will benefit current customers and increase transaction size and profitability. Relying primarily on historical sales data inflates SKU counts, causes inaccurate forecasts and leads to inventory issues (such as overstocks and out-of-stocks), leading to decreased customer satisfaction or even lost customers.

As evidenced by Gen Z’s differing habits from other generations, retailers must also be aware of customers’ product preferences and buying behaviours now and in the future — as nuanced or fast-paced as they might be. With artificial intelligence (AI), retailers can leverage customer data, understand trends and predict future behaviors for assortments, pricing, loyalty and demand.

INCORPORATING CUSTOMER DATA INTO ASSORTMENTS

Strategically managing assortments based on consumer preferences will improve the shopping experience while growing transaction sizes and profitability. AI interprets customer behaviors to give retailers in-depth understanding of how and why shoppers choose the products they purchase.

With this insight, assortments and shelf plans can then be used to enhance the customer decision process. For example, retailers can determine if energy drinks and sodas should be grouped to match shopper preferences on price, brand or flavor, which may be completely different from how they organize candy or salty snacks. What’s more, these product assortment and layout strategies can be localized to ensure that the right balance of products are present for each store.

OPTIMIZING ASSORTMENTS AT THE STORE LEVEL

Managing assortments at the store level is essential for ensuring the right customers are served the right products. But this can be hard for retailers to achieve, as the level of data analysis and decision-making involved can be time-consuming.

With AI, retailers can manage the assortments of individual stores or store groups with similar customer behaviors. For example, stores in a certain area might see a heavy number of baby boomers in the morning, who prefer muffins or doughnuts, while stores across town near the local university might experience Gen Z and millennials choosing items like fruit or energy bars.

By incorporating behavioural-based data into the assortment process, convenience store operators can optimize their store presentations, driving more relevant item assortments to each location, while also staying aware of space and physical constraints.

ASSORTMENTS THAT APPEAL TO ALL SHOPPERS

While catering to Generation Z shoppers is important for convenience store retailers, it’s also essential to remember other consumer groups who may be outside of this rising demographic. With AI, assortments and shelf plans can be delivered to offer the optimal selection in the right quantities and, most importantly, appeal to a wide consumer base.

The balance of eliminating SKUs that are duplicative and introducing meaningful products that drive frequency and transaction size across the various shoppers of a single store, or thousands of stores, requires a fresh approach that includes the sophisticated application of AI.

Kevin Sterneckert is chief marketing officer of Symphony RetailAI, a leader in artificial intelligence-enabled solutions for FMCG retailers and CPG manufacturers. Originally published at Convenience Store News.